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2020 – today
- 2024
[j43]Yutao Xie, Jun Wang, Cheng Chen, Taixin Yin, Shiyu Yang, Zhiyuan Li, Ye Zhang, Juyang Ke, Le Song, Lin Gan:
Sound identification of abnormal pig vocalizations: Enhancing livestock welfare monitoring on smart farms. Inf. Process. Manag. 61(4): 103770 (2024)- [j42]Huan Xiong
, Lei Huang, Wenston J. T. Zang, Xiantong Zhen, Guo-Sen Xie, Bin Gu, Le Song:
On the Number of Linear Regions of Convolutional Neural Networks With Piecewise Linear Activations. IEEE Trans. Pattern Anal. Mach. Intell. 46(7): 5131-5148 (2024) - [j41]Le Song, Guilong Zhu, Xiao Yin:
Evaluating the wisdom of scholar crowds from the perspective of knowledge diffusion. Scientometrics 129(9): 5103-5139 (2024) - [c193]Le Song, Zhegong Shangguan:
The Moment That The Driver Takes Over: Examining trust in full-self driving in a naturalistic and sequential approach. ECSCW 2024 - [c192]Quoc Phong Nguyen, Wan Theng Ruth Chew, Le Song, Bryan Kian Hsiang Low, Patrick Jaillet:
Optimistic Bayesian Optimization with Unknown Constraints. ICLR 2024 - [c191]Ruijia Wang, Haoran Dai, Cheng Yang, Le Song, Chuan Shi:
Advancing Molecule Invariant Representation via Privileged Substructure Identification. KDD 2024: 3188-3199 - [c190]Le Song, Zhegong Shangguan:
Multimodal Practices to Sustain Multiactivity When Live Streaming. IMX 2024: 369-374 - [d1]Le Song, Siying Lu:
Supplementary Materials. IEEE DataPort, 2024
- [i126]Bo Chen, Xingyi Cheng, Pan Li, Yangli-ao Geng, Jing Gong, Shen Li, Zhilei Bei, Xu Tan, Boyan Wang, Xin Zeng, Chiming Liu, Aohan Zeng, Yuxiao Dong, Jie Tang, Le Song:
xTrimoPGLM: Unified 100B-Scale Pre-trained Transformer for Deciphering the Language of Protein. CoRR abs/2401.06199 (2024) - [i125]Qing Li, Zhihang Hu, Yixuan Wang, Lei Li, Yimin Fan, Irwin King, Le Song, Yu Li:
Progress and Opportunities of Foundation Models in Bioinformatics. CoRR abs/2402.04286 (2024) - [i124]Bo Chen, Zhilei Bei, Xingyi Cheng, Pan Li, Jie Tang, Le Song:
MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training. CoRR abs/2406.05347 (2024) - 2023
- [j40]Libao Deng, Yuanzhu Di, Le Song, Wenyin Gong:
LTCSO/D: a large-scale tri-particle competitive swarm optimizer based on decomposition for multiobjective optimization. Appl. Intell. 53(20): 24034-24055 (2023) - [j39]Dong Liu, Biao Zhang, Jun Liu, Hui Li, Le Song, Guijun Zhang:
Assessing protein model quality based on deep graph coupled networks using protein language model. Briefings Bioinform. 25(1) (2023) - [j38]Xiaomin Fang, Fan Wang, Lihang Liu, Jingzhou He, Dayong Lin, Yingfei Xiang, Kunrui Zhu, Xiaonan Zhang, Hua Wu, Hui Li, Le Song:
A method for multiple-sequence-alignment-free protein structure prediction using a protein language model. Nat. Mac. Intell. 5(10): 1087-1096 (2023) - [j37]Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik:
Scientific discovery in the age of artificial intelligence. Nat. 620(7972): 47-60 (2023) - [c189]Dingmin Wang, Shengchao Liu, Hanchen Wang, Bernardo Cuenca Grau, Linfeng Song, Jian Tang, Le Song, Qi Liu:
An Empirical Study of Retrieval-Enhanced Graph Neural Networks. ECAI 2023: 2443-2450 - [c188]Yanfeng Zhou, Jiaxing Huang, Chenlong Wang, Le Song, Ge Yang:
XNet: Wavelet-Based Low and High Frequency Fusion Networks for Fully- and Semi-Supervised Semantic Segmentation of Biomedical Images. ICCV 2023: 21028-21039 - [c187]Jing Gong, Minsheng Hao, Xingyi Cheng, Xin Zeng, Chiming Liu, Jianzhu Ma, Xuegong Zhang, Taifeng Wang, Le Song:
xTrimoGene: An Efficient and Scalable Representation Learner for Single-Cell RNA-Seq Data. NeurIPS 2023 - [c186]Ruijia Wang, YiWu Sun, Yujie Luo, Shaochuan Li, Cheng Yang, Xingyi Cheng, Hui Li, Chuan Shi, Le Song:
Injecting Multimodal Information into Rigid Protein Docking via Bi-level Optimization. NeurIPS 2023 - [i123]Zhihang Hu, Qinze Yu, Yucheng Guo, Taifeng Wang, Irwin King, Xin Gao, Le Song, Yu Li:
Drug Synergistic Combinations Predictions via Large-Scale Pre-Training and Graph Structure Learning. CoRR abs/2301.05931 (2023) - [i122]Jing Gong, Minsheng Hao, Xingyi Cheng, Xin Zeng, Chiming Liu, Jianzhu Ma, Xuegong Zhang, Taifeng Wang, Le Song:
xTrimoGene: An Efficient and Scalable Representation Learner for Single-Cell RNA-Seq Data. CoRR abs/2311.15156 (2023) - 2022
- [j36]Le Song, Yinghong Ma:
Evaluating tacit knowledge diffusion with algebra matrix algorithm based social networks. Appl. Math. Comput. 428: 127125 (2022) - [j35]Harsh Shrivastava, Xiuwei Zhang, Le Song, Srinivas Aluru:
GRNUlar: A Deep Learning Framework for Recovering Single-Cell Gene Regulatory Networks. J. Comput. Biol. 29(1): 27-44 (2022) - [j34]Stefanos Zafeiriou, Michael M. Bronstein, Taco Cohen, Oriol Vinyals, Le Song, Jure Leskovec, Pietro Liò, Joan Bruna, Marco Gori:
Guest Editorial: Non-Euclidean Machine Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44(2): 723-726 (2022) - [c185]Rongzhi Zhang, Yue Yu, Pranav Shetty, Le Song, Chao Zhang:
Prompt-Based Rule Discovery and Boosting for Interactive Weakly-Supervised Learning. ACL (1) 2022: 745-758 - [c184]Yuchen Zhuang, Yinghao Li, Junyang Zhang, Yue Yu, Yingjun Mou, Xiang Chen, Le Song, Chao Zhang:
ReSel: N-ary Relation Extraction from Scientific Text and Tables by Learning to Retrieve and Select. EMNLP 2022: 730-744 - [c183]Weijia Ren, Fanmiao Sun, Lijia Liu, Yifan Wang, Le Song, Jingjing Shi:
Path Loss Model for Wearable Robotic Arm System at MHz Band. ICCT 2022: 1923-1926 - [c182]Sungsoo Ahn, Binghong Chen, Tianzhe Wang, Le Song:
Spanning Tree-based Graph Generation for Molecules. ICLR 2022 - [c181]Xinshi Chen, Haoran Sun, Le Song:
Provable Learning-based Algorithm For Sparse Recovery. ICLR 2022 - [c180]Shuang Li, Mingquan Feng, Lu Wang, Abdelmajid Essofi, Yufeng Cao, Junchi Yan, Le Song:
Explaining Point Processes by Learning Interpretable Temporal Logic Rules. ICLR 2022 - [c179]Kuan Wang, Yuyu Zhang, Diyi Yang, Le Song, Tao Qin:
GNN is a Counter? Revisiting GNN for Question Answering. ICLR 2022 - [c178]James Fox, Bo Zhao, Beatriz Gonzalez del Rio, Sivasankaran Rajamanickam, Rampi Ramprasad, Le Song:
Concentric Spherical Neural Network for 3D Representation Learning. IJCNN 2022: 1-8 - [c177]Yinghao Li, Le Song, Chao Zhang:
Sparse Conditional Hidden Markov Model for Weakly Supervised Named Entity Recognition. KDD 2022: 978-988 - [c176]Ruijia Wang, Xiao Wang, Chuan Shi, Le Song:
Uncovering the Structural Fairness in Graph Contrastive Learning. NeurIPS 2022 - [e1]Kamalika Chaudhuri, Stefanie Jegelka, Le Song, Csaba Szepesvári, Gang Niu, Sivan Sabato:
International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA. Proceedings of Machine Learning Research 162, PMLR 2022 [contents] - [i121]Karan Samel, Zelin Zhao, Binghong Chen, Shuang Li, Dharmashankar Subramanian, Irfan Essa, Le Song:
Learning Temporal Rules from Noisy Timeseries Data. CoRR abs/2202.05403 (2022) - [i120]Nianzu Yang, Huaijin Wu, Junchi Yan, Xiaoyong Pan, Ye Yuan, Le Song:
Molecule Generation for Drug Design: a Graph Learning Perspective. CoRR abs/2202.09212 (2022) - [i119]Rongzhi Zhang, Yue Yu, Pranav Shetty, Le Song, Chao Zhang:
PRBoost: Prompt-Based Rule Discovery and Boosting for Interactive Weakly-Supervised Learning. CoRR abs/2203.09735 (2022) - [i118]Yinghao Li, Le Song, Chao Zhang:
Sparse Conditional Hidden Markov Model for Weakly Supervised Named Entity Recognition. CoRR abs/2205.14228 (2022) - [i117]Mengyang Liu, Shanchuan Li, Xinshi Chen, Le Song:
Graph Condensation via Receptive Field Distribution Matching. CoRR abs/2206.13697 (2022) - [i116]Xiaomin Fang, Fan Wang, Lihang Liu, Jingzhou He, Dayong Lin, Yingfei Xiang, Xiaonan Zhang, Hua Wu, Hui Li, Le Song:
HelixFold-Single: MSA-free Protein Structure Prediction by Using Protein Language Model as an Alternative. CoRR abs/2207.13921 (2022) - [i115]Mengyang Liu, Haozheng Luo, Leonard Thong, Yinghao Li, Chao Zhang, Le Song:
SciAnnotate: A Tool for Integrating Weak Labeling Sources for Sequence Labeling. CoRR abs/2208.10241 (2022) - [i114]Ruijia Wang, Xiao Wang, Chuan Shi, Le Song:
Uncovering the Structural Fairness in Graph Contrastive Learning. CoRR abs/2210.03011 (2022) - [i113]Yuchen Zhuang, Yinghao Li, Jerry Junyang Cheung, Yue Yu, Yingjun Mou, Xiang Chen, Le Song, Chao Zhang:
ReSel: N-ary Relation Extraction from Scientific Text and Tables by Learning to Retrieve and Select. CoRR abs/2210.14427 (2022) - [i112]Yining Wang, Xumeng Gong, Shaochuan Li, Bing Yang, YiWu Sun, Chuan Shi, Yangang Wang, Cheng Yang, Hui Li, Le Song:
xTrimoABFold: De novo Antibody Structure Prediction without MSA. CoRR abs/2212.00735 (2022) - 2021
- [j33]Yinghong Ma, Hui Jiao, Le Song:
Tracking Attention of Social Media Event by Hidden Markov Model-Cases from Sina Weibo. IEEE Access 9: 68240-68252 (2021) - [j32]Libao Deng, Le Song, Gaoji Sun:
A Competitive Particle Swarm Algorithm Based on Vector Angles for Multi-Objective Optimization. IEEE Access 9: 89741-89756 (2021) - [j31]Mengmeng Liu, Yinghong Ma, Le Song, Changyu Liu:
Understanding the game behavior with sentiment and unequal status in cooperation network. Knowl. Based Syst. 212: 106588 (2021) - [j30]Le Song, Huan Zhu, Yelong Zheng, Meirong Zhao, Clarence Augustine Th Tee, Fengzhou Fang:
Bionic Compound Eye-Inspired High Spatial and Sensitive Tactile Sensor. IEEE Trans. Instrum. Meas. 70: 1-8 (2021) - [c175]Yinghao Li, Pranav Shetty, Lucas Liu, Chao Zhang, Le Song:
BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised Named Entity Recognition. ACL/IJCNLP (1) 2021: 6178-6190 - [c174]Weiyang Liu, Rongmei Lin, Zhen Liu, James M. Rehg, Liam Paull, Li Xiong, Le Song, Adrian Weller:
Orthogonal Over-Parameterized Training. CVPR 2021: 7251-7260 - [c173]Binghong Chen, Tianzhe Wang, Chengtao Li, Hanjun Dai, Le Song:
Molecule Optimization by Explainable Evolution. ICLR 2021 - [c172]Yuyu Zhang, Heng Chi, Binghong Chen, Tsz Ling Elaine Tang, Lucia Mirabella, Le Song, Glaucio H. Paulino:
Speeding up Computational Morphogenesis with Online Neural Synthetic Gradients. IJCNN 2021: 1-8 - [c171]Min Zhao, Xin Guo, Le Song, Baoxing Qin, Xuesong Shi, Gim Hee Lee, Guanghui Sun:
A General Framework for Lifelong Localization and Mapping in Changing Environment. IROS 2021: 3305-3312 - [c170]Sihyun Yu, Sungsoo Ahn, Le Song, Jinwoo Shin:
RoMA: Robust Model Adaptation for Offline Model-based Optimization. NeurIPS 2021: 4619-4631 - [c169]Qingru Zhang, David Wipf, Quan Gan, Le Song:
A Biased Graph Neural Network Sampler with Near-Optimal Regret. NeurIPS 2021: 8833-8844 - [c168]Xinshi Chen, Haoran Sun, Caleb Ellington, Eric P. Xing, Le Song:
Multi-task Learning of Order-Consistent Causal Graphs. NeurIPS 2021: 11083-11095 - [c167]Zelin Zhao, Karan Samel, Binghong Chen, Le Song:
ProTo: Program-Guided Transformer for Program-Guided Tasks. NeurIPS 2021: 17021-17036 - [c166]Zhaozhuo Xu, Beidi Chen, Chaojian Li, Weiyang Liu, Le Song, Yingyan Lin, Anshumali Shrivastava:
Locality Sensitive Teaching. NeurIPS 2021: 18049-18062 - [c165]Jiani Huang, Ziyang Li, Binghong Chen, Karan Samel, Mayur Naik, Le Song, Xujie Si:
Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning. NeurIPS 2021: 25134-25145 - [c164]Yuyu Zhang, Ping Nie, Arun Ramamurthy, Le Song:
Answering Any-hop Open-domain Questions with Iterative Document Reranking. SIGIR 2021: 481-490 - [c163]Ziyang Li, Aravind Machiry, Binghong Chen, Mayur Naik, Ke Wang, Le Song:
ARBITRAR: User-Guided API Misuse Detection. SP 2021: 1400-1415 - [c162]Libao Deng, Le Song, Sibo Hou, Gaoji Sun:
VaCSO: A Multi-objective Collaborative Competition Particle Swarm Algorithm Based on Vector Angles. ICSI (1) 2021: 244-253 - [i111]Qingru Zhang, David Wipf, Quan Gan, Le Song:
A Biased Graph Neural Network Sampler with Near-Optimal Regret. CoRR abs/2103.01089 (2021) - [i110]James Fox, Bo Zhao, Sivasankaran Rajamanickam, Rampi Ramprasad, Le Song:
Concentric Spherical GNN for 3D Representation Learning. CoRR abs/2103.10484 (2021) - [i109]Karan Samel, Zelin Zhao, Binghong Chen, Kuan Wang, Robin Luo, Le Song:
How to Design Sample and Computationally Efficient VQA Models. CoRR abs/2103.11537 (2021) - [i108]Yuyu Zhang, Heng Chi, Binghong Chen, Tsz Ling Elaine Tang, Lucia Mirabella, Le Song, Glaucio H. Paulino:
Speeding up Computational Morphogenesis with Online Neural Synthetic Gradients. CoRR abs/2104.12282 (2021) - [i107]Lu Wang, Xiaofu Chang, Shuang Li, Yunfei Chu, Hui Li, Wei Zhang, Xiaofeng He, Le Song, Jingren Zhou, Hongxia Yang:
TCL: Transformer-based Dynamic Graph Modelling via Contrastive Learning. CoRR abs/2105.07944 (2021) - [i106]Yinghao Li, Pranav Shetty, Lucas Liu, Chao Zhang, Le Song:
BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised Named Entity Recognition. CoRR abs/2105.12848 (2021) - [i105]Zelin Zhao, Karan Samel, Binghong Chen, Le Song:
ProTo: Program-Guided Transformer for Program-Guided Tasks. CoRR abs/2110.00804 (2021) - [i104]Kuan Wang, Yuyu Zhang, Diyi Yang, Le Song, Tao Qin:
GNN is a Counter? Revisiting GNN for Question Answering. CoRR abs/2110.03192 (2021) - [i103]Yu-Ying Liu, Alexander Moreno, Maxwell A. Xu, Shuang Li, Jena C. McDaniel, Nancy C. Brady, Agata Rozga, Fuxin Li, Le Song, James M. Rehg:
Efficient Learning and Decoding of the Continuous-Time Hidden Markov Model for Disease Progression Modeling. CoRR abs/2110.13998 (2021) - [i102]Sihyun Yu, Sungsoo Ahn, Le Song, Jinwoo Shin:
RoMA: Robust Model Adaptation for Offline Model-based Optimization. CoRR abs/2110.14188 (2021) - [i101]Xinshi Chen, Haoran Sun, Caleb Ellington, Eric P. Xing, Le Song:
Multi-task Learning of Order-Consistent Causal Graphs. CoRR abs/2111.02545 (2021) - [i100]Min Zhao, Xin Guo, Le Song, Baoxing Qin, Xuesong Shi, Gim Hee Lee, Guanghui Sun:
A General Framework for Lifelong Localization and Mapping in Changing Environment. CoRR abs/2111.10946 (2021) - [i99]Shuangjia Zheng, Ying Song, Zhang Pan, Chengtao Li, Le Song, Yuedong Yang:
Molecular Attributes Transfer from Non-Parallel Data. CoRR abs/2111.15146 (2021) - [i98]Xinshi Chen, Yan Zhu, Haowen Xu, Mengyang Liu, Liang Xiong, Muhan Zhang, Le Song:
Efficient Dynamic Graph Representation Learning at Scale. CoRR abs/2112.07768 (2021) - 2020
- [j29]Yinghong Ma, Qiaozheng Chi, Le Song:
Revealing Structural Patterns of Patent Citation by a Two-Boundary Network Model Based on USPTO Data. IEEE Access 8: 23324-23335 (2020) - [j28]Yinghong Ma, Zhaoxun Ji, Le Song:
A Two-Layer Network Model Reveals the Adhesion Scientist Career Stage and Research Topic in China. IEEE Access 8: 52726-52737 (2020) - [j27]Yelong Zheng, Hanli Zhang, Meirong Zhao, He Xin, Clarence Augustine Th Tee, Le Song:
A Multiposition Method of Viscous Measurement for Small-Volume Samples With High Viscous. IEEE Trans. Instrum. Meas. 69(7): 4995-5001 (2020) - [c161]Jian-Ya Ding, Chao Zhang, Lei Shen, Shengyin Li, Bing Wang, Yinghui Xu, Le Song:
Accelerating Primal Solution Findings for Mixed Integer Programs Based on Solution Prediction. AAAI 2020: 1452-1459 - [c160]Romain Lopez, Chenchen Li, Xiang Yan, Junwu Xiong, Michael I. Jordan, Yuan Qi, Le Song:
Cost-Effective Incentive Allocation via Structured Counterfactual Inference. AAAI 2020: 4997-5004 - [c159]Xujie Si, Aaditya Naik, Hanjun Dai, Mayur Naik, Le Song:
Code2Inv: A Deep Learning Framework for Program Verification. CAV (2) 2020: 151-164 - [c158]Xiaofu Chang, Xuqin Liu, Jianfeng Wen, Shuang Li, Yanming Fang, Le Song, Yuan Qi:
Continuous-Time Dynamic Graph Learning via Neural Interaction Processes. CIKM 2020: 145-154 - [c157]Rongmei Lin, Weiyang Liu, Zhen Liu, Chen Feng, Zhiding Yu, James M. Rehg, Li Xiong, Le Song:
Regularizing Neural Networks via Minimizing Hyperspherical Energy. CVPR 2020: 6916-6925 - [c156]Kunlong Chen, Weidi Xu, Xingyi Cheng, Zou Xiaochuan, Yuyu Zhang, Le Song, Taifeng Wang, Yuan Qi, Wei Chu:
Question Directed Graph Attention Network for Numerical Reasoning over Text. EMNLP (1) 2020: 6759-6768 - [c155]Xinshi Chen, Yu Li, Ramzan Umarov, Xin Gao, Le Song:
RNA Secondary Structure Prediction By Learning Unrolled Algorithms. ICLR 2020 - [c154]Binghong Chen, Bo Dai, Qinjie Lin, Guo Ye, Han Liu, Le Song:
Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees. ICLR 2020 - [c153]Elizabeth Dinella, Hanjun Dai, Ziyang Li, Mayur Naik, Le Song, Ke Wang:
Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs. ICLR 2020 - [c152]Hui Li, Kailiang Hu, Shaohua Zhang, Yuan Qi, Le Song:
Double Neural Counterfactual Regret Minimization. ICLR 2020 - [c151]Harsh Shrivastava, Xinshi Chen, Binghong Chen, Guanghui Lan, Srinivas Aluru, Han Liu, Le Song:
GLAD: Learning Sparse Graph Recovery. ICLR 2020 - [c150]Yuan Yang, Le Song:
Learn to Explain Efficiently via Neural Logic Inductive Learning. ICLR 2020 - [c149]Yuyu Zhang, Xinshi Chen, Yuan Yang, Arun Ramamurthy, Bo Li, Yuan Qi, Le Song:
Efficient Probabilistic Logic Reasoning with Graph Neural Networks. ICLR 2020 - [c148]Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song:
Learning To Stop While Learning To Predict. ICML 2020: 1520-1530 - [c147]Binghong Chen, Chengtao Li, Hanjun Dai, Le Song:
Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search. ICML 2020: 1608-1616 - [c146]Shuang Li, Lu Wang, Ruizhi Zhang, Xiaofu Chang, Xuqin Liu, Yao Xie, Yuan Qi, Le Song:
Temporal Logic Point Processes. ICML 2020: 5990-6000 - [c145]Xuesong Shi, Dongjiang Li, Pengpeng Zhao, Qinbin Tian, Yuxin Tian, Qiwei Long, Chunhao Zhu, Jingwei Song, Fei Qiao, Le Song, Yangquan Guo, Zhigang Wang, Yimin Zhang, Baoxing Qin, Wei Yang, Fangshi Wang, Rosa H. M. Chan, Qi She:
Are We Ready for Service Robots? The OpenLORIS-Scene Datasets for Lifelong SLAM. ICRA 2020: 3139-3145 - [c144]Xinshi Chen, Yufei Zhang, Christoph Reisinger, Le Song:
Understanding Deep Architecture with Reasoning Layer. NeurIPS 2020 - [c143]Ziqi Liu, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou, Shuang Yang, Le Song, Yuan Qi:
Bandit Samplers for Training Graph Neural Networks. NeurIPS 2020 - [c142]Yingxiang Yang, Negar Kiyavash, Le Song, Niao He:
The Devil is in the Detail: A Framework for Macroscopic Prediction via Microscopic Models. NeurIPS 2020 - [c141]Ping Nie, Yuyu Zhang, Xiubo Geng, Arun Ramamurthy, Le Song, Daxin Jiang:
DC-BERT: Decoupling Question and Document for Efficient Contextual Encoding. SIGIR 2020: 1829-1832 - [i97]Hanjun Dai, Chengtao Li, Connor W. Coley, Bo Dai, Le Song:
Retrosynthesis Prediction with Conditional Graph Logic Network. CoRR abs/2001.01408 (2020) - [i96]Yuyu Zhang, Xinshi Chen, Yuan Yang, Arun Ramamurthy, Bo Li, Yuan Qi, Le Song:
Efficient Probabilistic Logic Reasoning with Graph Neural Networks. CoRR abs/2001.11850 (2020) - [i95]Xinshi Chen, Yu Li, Ramzan Umarov, Xin Gao, Le Song:
RNA Secondary Structure Prediction By Learning Unrolled Algorithms. CoRR abs/2002.05810 (2020) - [i94]Ziqi Liu, Chaochao Chen, Xinxing Yang, Jun Zhou, Xiaolong Li, Le Song:
Heterogeneous Graph Neural Networks for Malicious Account Detection. CoRR abs/2002.12307 (2020) - [i93]Yuyu Zhang, Ping Nie, Xiubo Geng, Arun Ramamurthy, Le Song, Daxin Jiang:
DC-BERT: Decoupling Question and Document for Efficient Contextual Encoding. CoRR abs/2002.12591 (2020) - [i92]Weiyang Liu, Rongmei Lin, Zhen Liu, James M. Rehg, Li Xiong, Le Song:
Orthogonal Over-Parameterized Training. CoRR abs/2004.04690 (2020) - [i91]Chao Qu, Hui Li, Chang Liu, Junwu Xiong, James Zhang, Wei Chu, Yuan Qi, Le Song:
Intention Propagation for Multi-agent Reinforcement Learning. CoRR abs/2004.08883 (2020) - [i90]Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song:
Learning to Stop While Learning to Predict. CoRR abs/2006.05082 (2020) - [i89]Ziqi Liu, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou, Shuang Yang, Le Song, Yuan Qi:
Bandit Samplers for Training Graph Neural Networks. CoRR abs/2006.05806 (2020) - [i88]Xinshi Chen, Yufei Zhang, Christoph Reisinger, Le Song:
Understanding Deep Architectures with Reasoning Layer. CoRR abs/2006.13401 (2020) - [i87]Binghong Chen, Chengtao Li, Hanjun Dai, Le Song:
Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search. CoRR abs/2006.15820 (2020) - [i86]Kunlong Chen, Weidi Xu, Xingyi Cheng, Zou Xiaochuan, Yuyu Zhang, Le Song, Taifeng Wang, Yuan Qi, Wei Chu:
Question Directed Graph Attention Network for Numerical Reasoning over Text. CoRR abs/2009.07448 (2020) - [i85]Yuyu Zhang, Ping Nie, Arun Ramamurthy, Le Song:
DDRQA: Dynamic Document Reranking for Open-domain Multi-hop Question Answering. CoRR abs/2009.07465 (2020) - [i84]Rohit Batra, Hanjun Dai, Tran Doan Huan, Lihua Chen, Chiho Kim, Will R. Gutekunst, Le Song, Rampi Ramprasad:
Polymers for Extreme Conditions Designed Using Syntax-Directed Variational Autoencoders. CoRR abs/2011.02551 (2020)
2010 – 2019
- 2019
- [j26]Yelong Zheng, Meirong Zhao, Jile Jiang, Le Song:
Dynamic Force Transducer Calibration Based on Electrostatic Force. IEEE Access 7: 48998-49003 (2019) - [j25]Weiming Yang, Le Song, Clarence Augustine Th Tee, Yelong Zheng, Yuliang Liu:
Unsupervised Learning Grouping-Based Resampling for Particle Filters. IEEE Access 7: 127265-127275 (2019) - [j24]Shuai Xiao, Junchi Yan, Mehrdad Farajtabar, Le Song, Xiaokang Yang, Hongyuan Zha:
Learning Time Series Associated Event Sequences With Recurrent Point Process Networks. IEEE Trans. Neural Networks Learn. Syst. 30(10): 3124-3136 (2019) - [c140]Chenchen Li, Xiang Yan, Xiaotie Deng, Yuan Qi, Wei Chu, Le Song, Junlong Qiao, Jianshan He, Junwu Xiong:
Latent Dirichlet Allocation for Internet Price War. AAAI 2019: 639-646 - [c139]Ziqi Liu, Chaochao Chen, Longfei Li, Jun Zhou, Xiaolong Li, Le Song, Yuan Qi:
GeniePath: Graph Neural Networks with Adaptive Receptive Paths. AAAI 2019: 4424-4431 - [c138]Yuyu Zhang, Le Song:
Language Modeling with Shared Grammar. ACL (1) 2019: 4442-4453 - [c137]Bo Dai, Hanjun Dai, Arthur Gretton, Le Song, Dale Schuurmans, Niao He:
Kernel Exponential Family Estimation via Doubly Dual Embedding. AISTATS 2019: 2321-2330 - [c136]Libao Deng, Le Song, Ning Sun:
On-Chip Health Monitoring Based on DE-Cluster in 2.5D ICs. BIC-TA (1) 2019: 517-526 - [c135]Jianbo Chen, Le Song, Martin J. Wainwright, Michael I. Jordan:
L-Shapley and C-Shapley: Efficient Model Interpretation for Structured Data. ICLR (Poster) 2019 - [c134]Xujie Si, Yuan Yang, Hanjun Dai, Mayur Naik, Le Song:
Learning a Meta-Solver for Syntax-Guided Program Synthesis. ICLR (Poster) 2019 - [c133]Xinshi Chen, Hanjun Dai, Le Song:
Particle Flow Bayes' Rule. ICML 2019: 1022-1031 - [c132]Xinshi Chen, Shuang Li, Hui Li, Shaohua Jiang, Yuan Qi, Le Song:
Generative Adversarial User Model for Reinforcement Learning Based Recommendation System. ICML 2019: 1052-1061 - [c131]Yifeng Zhao, Xiangwei Wang, Hongxia Yang, Le Song, Jie Tang:
Large Scale Evolving Graphs with Burst Detection. IJCAI 2019: 4412-4418 - [c130]Xiao Huang, Peng Cui, Yuxiao Dong, Jundong Li, Huan Liu, Jian Pei, Le Song, Jie Tang, Fei Wang, Hongxia Yang, Wenwu Zhu:
Learning From Networks: Algorithms, Theory, and Applications. KDD 2019: 3221-3222 - [c129]Chao Qu, Shie Mannor, Huan Xu, Yuan Qi, Le Song, Junwu Xiong:
Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning. NeurIPS 2019: 1182-1191 - [c128]Weiyang Liu, Zhen Liu, James M. Rehg, Le Song:
Neural Similarity Learning. NeurIPS 2019: 5026-5037 - [c127]Hanjun Dai, Chengtao Li, Connor W. Coley, Bo Dai, Le Song:
Retrosynthesis Prediction with Conditional Graph Logic Network. NeurIPS 2019: 8870-8880 - [c126]Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, Dale Schuurmans:
Exponential Family Estimation via Adversarial Dynamics Embedding. NeurIPS 2019: 10977-10988 - [c125]Albert E. Shaw, Wei Wei, Weiyang Liu, Le Song, Bo Dai:
Meta Architecture Search. NeurIPS 2019: 11225-11235 - [i83]Chao Qu, Shie Mannor, Huan Xu, Yuan Qi, Le Song, Junwu Xiong:
Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning. CoRR abs/1901.09326 (2019) - [i82]Xinshi Chen, Hanjun Dai, Le Song:
Meta Particle Flow for Sequential Bayesian Inference. CoRR abs/1902.00640 (2019) - [i81]Romain Lopez, Chenchen Li, Xiang Yan, Junwu Xiong, Michael I. Jordan, Yuan Qi, Le Song:
Cost-Effective Incentive Allocation via Structured Counterfactual Inference. CoRR abs/1902.02495 (2019) - [i80]Binghong Chen, Bo Dai, Le Song:
Learning to Plan via Neural Exploration-Exploitation Trees. CoRR abs/1903.00070 (2019) - [i79]Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, Dale Schuurmans:
Exponential Family Estimation via Adversarial Dynamics Embedding. CoRR abs/1904.12083 (2019) - [i78]Harsh Shrivastava, Xinshi Chen, Binghong Chen, Guanghui Lan, Srinivas Aluru, Le Song:
GLAD: Learning Sparse Graph Recovery. CoRR abs/1906.00271 (2019) - [i77]Yuyu Zhang, Xinshi Chen, Yuan Yang, Arun Ramamurthy, Bo Li, Yuan Qi, Le Song:
Can Graph Neural Networks Help Logic Reasoning? CoRR abs/1906.02111 (2019) - [i76]Rongmei Lin, Weiyang Liu, Zhen Liu, Chen Feng, Zhiding Yu, James M. Rehg, Li Xiong, Le Song:
Compressive Hyperspherical Energy Minimization. CoRR abs/1906.04892 (2019) - [i75]Jian-Ya Ding, Chao Zhang, Lei Shen, Shengyin Li, Bing Wang, Yinghui Xu, Le Song:
Optimal Solution Predictions for Mixed Integer Programs. CoRR abs/1906.09575 (2019) - [i74]Yuan Yang, Le Song:
Learn to Explain Efficiently via Neural Logic Inductive Learning. CoRR abs/1910.02481 (2019) - [i73]Weiyang Liu, Zhen Liu, James M. Rehg, Le Song:
Neural Similarity Learning. CoRR abs/1910.13003 (2019) - [i72]Xuesong Shi, Dongjiang Li, Pengpeng Zhao, Qinbin Tian, Yuxin Tian, Qiwei Long, Chunhao Zhu, Jingwei Song, Fei Qiao, Le Song, Yangquan Guo, Zhigang Wang, Yimin Zhang, Baoxing Qin, Wei Yang, Fangshi Wang, Rosa H. M. Chan, Qi She:
Are We Ready for Service Robots? The OpenLORIS-Scene Datasets for Lifelong SLAM. CoRR abs/1911.05603 (2019) - 2018
- [j23]Yelong Zheng, Meirong Zhao, Peiyuan Sun, Le Song:
Optimization of Electrostatic Force System Based on Newton Interpolation Method. J. Sensors 2018: 7801597:1-7801597:7 (2018) - [c124]Kenji Kawaguchi, Bo Xie, Le Song:
Deep Semi-Random Features for Nonlinear Function Approximation. AAAI 2018: 3382-3389 - [c123]Yuyu Zhang, Hanjun Dai, Zornitsa Kozareva, Alexander J. Smola, Le Song:
Variational Reasoning for Question Answering With Knowledge Graph. AAAI 2018: 6069-6076 - [c122]Shuai Xiao, Hongteng Xu, Junchi Yan, Mehrdad Farajtabar, Xiaokang Yang, Le Song, Hongyuan Zha:
Learning Conditional Generative Models for Temporal Point Processes. AAAI 2018: 6302-6310 - [c121]Woosang Lim, Rundong Du, Bo Dai, Kyomin Jung, Le Song, Haesun Park:
Multi-scale Nystrom Method. AISTATS 2018: 68-76 - [c120]Yichen Wang, Evangelos A. Theodorou, Apurv Verma, Le Song:
A Stochastic Differential Equation Framework for Guiding Online User Activities in Closed Loop. AISTATS 2018: 1077-1086 - [c119]Ziqi Liu, Chaochao Chen, Xinxing Yang, Jun Zhou, Xiaolong Li, Le Song:
Heterogeneous Graph Neural Networks for Malicious Account Detection. CIKM 2018: 2077-2085 - [c118]Weiyang Liu, Zhen Liu, Zhiding Yu, Bo Dai, Rongmei Lin, Yisen Wang, James M. Rehg, Le Song:
Decoupled Networks. CVPR 2018: 2771-2779 - [c117]Yisen Wang, Weiyang Liu, Xingjun Ma, James Bailey, Hongyuan Zha, Le Song, Shu-Tao Xia:
Iterative Learning With Open-Set Noisy Labels. CVPR 2018: 8688-8696 - [c116]Bo Dai, Albert E. Shaw, Niao He, Lihong Li, Le Song:
Boosting the Actor with Dual Critic. ICLR (Poster) 2018 - [c115]Hanjun Dai, Yingtao Tian, Bo Dai, Steven Skiena, Le Song:
Syntax-Directed Variational Autoencoder for Structured Data. ICLR (Poster) 2018 - [c114]Jianbo Chen, Le Song, Martin J. Wainwright, Michael I. Jordan:
Learning to Explain: An Information-Theoretic Perspective on Model Interpretation. ICML 2018: 882-891 - [c113]Jianfei Chen, Jun Zhu, Le Song:
Stochastic Training of Graph Convolutional Networks with Variance Reduction. ICML 2018: 941-949 - [c112]Hanjun Dai, Zornitsa Kozareva, Bo Dai, Alexander J. Smola, Le Song:
Learning Steady-States of Iterative Algorithms over Graphs. ICML 2018: 1114-1122 - [c111]Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, Le Song:
Adversarial Attack on Graph Structured Data. ICML 2018: 1123-1132 - [c110]Bo Dai, Albert E. Shaw, Lihong Li, Lin Xiao, Niao He, Zhen Liu, Jianshu Chen, Le Song:
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation. ICML 2018: 1133-1142 - [c109]Weiyang Liu, Bo Dai, Xingguo Li, Zhen Liu, James M. Rehg, Le Song:
Towards Black-box Iterative Machine Teaching. ICML 2018: 3147-3155 - [c108]Weiyang Liu, Rongmei Lin, Zhen Liu, Lixin Liu, Zhiding Yu, Bo Dai, Le Song:
Learning towards Minimum Hyperspherical Energy. NeurIPS 2018: 6225-6236 - [c107]Xujie Si, Hanjun Dai, Mukund Raghothaman, Mayur Naik, Le Song:
Learning Loop Invariants for Program Verification. NeurIPS 2018: 7762-7773 - [c106]Bo Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao, Le Song:
Coupled Variational Bayes via Optimization Embedding. NeurIPS 2018: 9713-9723 - [c105]Shuang Li, Shuai Xiao, Shixiang Zhu, Nan Du, Yao Xie, Le Song:
Learning Temporal Point Processes via Reinforcement Learning. NeurIPS 2018: 10804-10814 - [c104]Mehrdad Farajtabar, Manuel Gomez-Rodriguez, Yichen Wang, Shuang Li, Hongyuan Zha, Le Song:
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution. WWW (Companion Volume) 2018: 473-477 - [i71]Ziqi Liu, Chaochao Chen, Longfei Li, Jun Zhou, Xiaolong Li, Le Song:
GeniePath: Graph Neural Networks with Adaptive Receptive Paths. CoRR abs/1802.00910 (2018) - [i70]Jianbo Chen, Le Song, Martin J. Wainwright, Michael I. Jordan:
Learning to Explain: An Information-Theoretic Perspective on Model Interpretation. CoRR abs/1802.07814 (2018) - [i69]Hanjun Dai, Yingtao Tian, Bo Dai, Steven Skiena, Le Song:
Syntax-Directed Variational Autoencoder for Structured Data. CoRR abs/1802.08786 (2018) - [i68]Yisen Wang, Weiyang Liu, Xingjun Ma, James Bailey, Hongyuan Zha, Le Song, Shu-Tao Xia:
Iterative Learning with Open-set Noisy Labels. CoRR abs/1804.00092 (2018) - [i67]Weiyang Liu, Zhen Liu, Zhiding Yu, Bo Dai, Rongmei Lin, Yisen Wang, James M. Rehg, Le Song:
Decoupled Networks. CoRR abs/1804.08071 (2018) - [i66]Yichen Wang, Le Song, Hongyuan Zha:
Learning to Optimize via Wasserstein Deep Inverse Optimal Control. CoRR abs/1805.08395 (2018) - [i65]Weiyang Liu, Rongmei Lin, Zhen Liu, Lixin Liu, Zhiding Yu, Bo Dai, Le Song:
Learning towards Minimum Hyperspherical Energy. CoRR abs/1805.09298 (2018) - [i64]Yuyu Zhang, Hanjun Dai, Kamil Toraman, Le Song:
KG^2: Learning to Reason Science Exam Questions with Contextual Knowledge Graph Embeddings. CoRR abs/1805.12393 (2018) - [i63]Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, Le Song:
Adversarial Attack on Graph Structured Data. CoRR abs/1806.02371 (2018) - [i62]Jianbo Chen, Le Song, Martin J. Wainwright, Michael I. Jordan:
L-Shapley and C-Shapley: Efficient Model Interpretation for Structured Data. CoRR abs/1808.02610 (2018) - [i61]Chenchen Li, Xiang Yan, Xiaotie Deng, Yuan Qi, Wei Chu, Le Song, Junlong Qiao, Jianshan He, Junwu Xiong:
Latent Dirichlet Allocation for Internet Price War. CoRR abs/1808.07621 (2018) - [i60]Bo Dai, Hanjun Dai, Arthur Gretton, Le Song, Dale Schuurmans, Niao He:
Kernel Exponential Family Estimation via Doubly Dual Embedding. CoRR abs/1811.02228 (2018) - [i59]Shuang Li, Shuai Xiao, Shixiang Zhu, Nan Du, Yao Xie, Le Song:
Learning Temporal Point Processes via Reinforcement Learning. CoRR abs/1811.05016 (2018) - [i58]Chenchen Li, Xiang Yan, Xiaotie Deng, Yuan Qi, Wei Chu, Le Song, Junlong Qiao, Jianshan He, Junwu Xiong:
A Policy Gradient Method with Variance Reduction for Uplift Modeling. CoRR abs/1811.10158 (2018) - [i57]Albert E. Shaw, Bo Dai, Weiyang Liu, Le Song:
Bayesian Meta-network Architecture Learning. CoRR abs/1812.09584 (2018) - [i56]Hui Li, Kailiang Hu, Zhibang Ge, Tao Jiang, Yuan Qi, Le Song:
Double Neural Counterfactual Regret Minimization. CoRR abs/1812.10607 (2018) - [i55]Xinshi Chen, Shuang Li, Hui Li, Shaohua Jiang, Yuan Qi, Le Song:
Neural Model-Based Reinforcement Learning for Recommendation. CoRR abs/1812.10613 (2018) - 2017
- [j22]Hanjun Dai, Ramzan Umarov, Hiroyuki Kuwahara, Yu Li, Le Song, Xin Gao:
Sequence2Vec: a novel embedding approach for modeling transcription factor binding affinity landscape. Bioinform. 33(22): 3575-3583 (2017) - [j21]Nan Du, Yingyu Liang, Maria-Florina Balcan, Manuel Gomez-Rodriguez, Hongyuan Zha, Le Song:
Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks. J. Mach. Learn. Res. 18: 2:1-2:45 (2017) - [j20]Mehrdad Farajtabar, Yichen Wang, Manuel Gomez-Rodriguez, Shuang Li, Hongyuan Zha, Le Song:
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Evolution. J. Mach. Learn. Res. 18: 41:1-41:49 (2017) - [j19]Peiyuan Sun, Meirong Zhao, Jile Jiang, Yelong Zheng, Yaqian Han, Le Song:
The Differential Method for Force Measurement Based on Electrostatic Force. J. Sensors 2017: 1857920:1-1857920:7 (2017) - [j18]Yang You, James Demmel, Kent Czechowski, Le Song, Rich Vuduc:
Design and Implementation of a Communication-Optimal Classifier for Distributed Kernel Support Vector Machines. IEEE Trans. Parallel Distributed Syst. 28(4): 974-988 (2017) - [j17]Shuang Li, Yao Xie, Mehrdad Farajtabar, Apurv Verma, Le Song:
Detecting Changes in Dynamic Events Over Networks. IEEE Trans. Signal Inf. Process. over Networks 3(2): 346-359 (2017) - [c103]Bo Xie, Yingyu Liang, Le Song:
Diverse Neural Network Learns True Target Functions. AISTATS 2017: 1216-1224 - [c102]Yichen Wang, Xiaojing Ye, Haomin Zhou, Hongyuan Zha, Le Song:
Linking Micro Event History to Macro Prediction in Point Process Models. AISTATS 2017: 1375-1384 - [c101]Bo Dai, Niao He, Yunpeng Pan, Byron Boots, Le Song:
Learning from Conditional Distributions via Dual Embeddings. AISTATS 2017: 1458-1467 - [c100]Xiaojun Xu, Chang Liu, Qian Feng, Heng Yin, Le Song, Dawn Song:
Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity Detection. CCS 2017: 363-376 - [c99]Ziqi Liu, Chaochao Chen, Jun Zhou, Xiaolong Li, Feng Xu, Tao Chen, Le Song:
POSTER: Neural Network-based Graph Embedding for Malicious Accounts Detection. CCS 2017: 2543-2545 - [c98]Weiyang Liu, Yandong Wen, Zhiding Yu, Ming Li, Bhiksha Raj, Le Song:
SphereFace: Deep Hypersphere Embedding for Face Recognition. CVPR 2017: 6738-6746 - [c97]Hanjun Dai, Bo Dai, Yan-Ming Zhang, Shuang Li, Le Song:
Recurrent Hidden Semi-Markov Model. ICLR (Poster) 2017 - [c96]Bo Dai, Ruiqi Guo, Sanjiv Kumar, Niao He, Le Song:
Stochastic Generative Hashing. ICML 2017: 913-922 - [c95]Mehrdad Farajtabar, Jiachen Yang, Xiaojing Ye, Huan Xu, Rakshit Trivedi, Elias B. Khalil, Shuang Li, Le Song, Hongyuan Zha:
Fake News Mitigation via Point Process Based Intervention. ICML 2017: 1097-1106 - [c94]Weiyang Liu, Bo Dai, Ahmad Humayun, Charlene Tay, Chen Yu, Linda B. Smith, James M. Rehg, Le Song:
Iterative Machine Teaching. ICML 2017: 2149-2158 - [c93]Rakshit Trivedi, Hanjun Dai, Yichen Wang, Le Song:
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs. ICML 2017: 3462-3471 - [c92]Yichen Wang, Grady Williams, Evangelos A. Theodorou, Le Song:
Variational Policy for Guiding Point Processes. ICML 2017: 3684-3693 - [c91]Edward Choi, Mohammad Taha Bahadori, Le Song, Walter F. Stewart, Jimeng Sun:
GRAM: Graph-based Attention Model for Healthcare Representation Learning. KDD 2017: 787-795 - [c90]Yichen Wang, Xiaojing Ye, Hongyuan Zha, Le Song:
Predicting User Activity Level In Point Processes With Mass Transport Equation. NIPS 2017: 1645-1655 - [c89]Shuai Xiao, Mehrdad Farajtabar, Xiaojing Ye, Junchi Yan, Xiaokang Yang, Le Song, Hongyuan Zha:
Wasserstein Learning of Deep Generative Point Process Models. NIPS 2017: 3247-3257 - [c88]Weiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhen Liu, Bo Dai, Tuo Zhao, Le Song:
Deep Hyperspherical Learning. NIPS 2017: 3950-3960 - [c87]Le Song, Santosh S. Vempala, John Wilmes, Bo Xie:
On the Complexity of Learning Neural Networks. NIPS 2017: 5514-5522 - [c86]Elias B. Khalil, Hanjun Dai, Yuyu Zhang, Bistra Dilkina, Le Song:
Learning Combinatorial Optimization Algorithms over Graphs. NIPS 2017: 6348-6358 - [c85]Behzad Tabibian, Isabel Valera, Mehrdad Farajtabar, Le Song, Bernhard Schölkopf, Manuel Gomez-Rodriguez:
Distilling Information Reliability and Source Trustworthiness from Digital Traces. WWW 2017: 847-855 - [p1]Yu-Ying Liu, Alexander Moreno, Shuang Li, Fuxin Li, Le Song, James M. Rehg:
Learning Continuous-Time Hidden Markov Models for Event Data. Mobile Health - Sensors, Analytic Methods, and Applications 2017: 361-387 - [i54]Bo Dai, Ruiqi Guo, Sanjiv Kumar, Niao He, Le Song:
Stochastic Generative Hashing. CoRR abs/1701.02815 (2017) - [i53]Yichen Wang, Grady Williams, Evangelos A. Theodorou, Le Song:
A Unifying Framework for Guiding Point Processes with Stochastic Intensity Functions. CoRR abs/1701.08585 (2017) - [i52]Kenji Kawaguchi, Bo Xie, Le Song:
Deep Semi-Random Features for Nonlinear Function Approximation. CoRR abs/1702.08882 (2017) - [i51]Mehrdad Farajtabar, Jiachen Yang, Xiaojing Ye, Huan Xu, Rakshit Trivedi, Elias Boutros Khalil, Shuang Li, Le Song, Hongyuan Zha:
Fake News Mitigation via Point Process Based Intervention. CoRR abs/1703.07823 (2017) - [i50]Shuai Xiao, Junchi Yan, Mehrdad Farajtabar, Le Song, Xiaokang Yang, Hongyuan Zha:
Joint Modeling of Event Sequence and Time Series with Attentional Twin Recurrent Neural Networks. CoRR abs/1703.08524 (2017) - [i49]Hanjun Dai, Elias B. Khalil, Yuyu Zhang, Bistra Dilkina, Le Song:
Learning Combinatorial Optimization Algorithms over Graphs. CoRR abs/1704.01665 (2017) - [i48]Weiyang Liu, Yandong Wen, Zhiding Yu, Ming Li, Bhiksha Raj, Le Song:
SphereFace: Deep Hypersphere Embedding for Face Recognition. CoRR abs/1704.08063 (2017) - [i47]Rakshit Trivedi, Hanjun Dai, Yichen Wang, Le Song:
Know-Evolve: Deep Reasoning in Temporal Knowledge Graphs. CoRR abs/1705.05742 (2017) - [i46]Shuai Xiao, Mehrdad Farajtabar, Xiaojing Ye, Junchi Yan, Le Song, Hongyuan Zha:
Wasserstein Learning of Deep Generative Point Process Models. CoRR abs/1705.08051 (2017) - [i45]Weiyang Liu, Bo Dai, James M. Rehg, Le Song:
Iterative Machine Teaching. CoRR abs/1705.10470 (2017) - [i44]Le Song, Santosh S. Vempala, John Wilmes, Bo Xie:
On the Complexity of Learning Neural Networks. CoRR abs/1707.04615 (2017) - [i43]Xiaojun Xu, Chang Liu, Qian Feng, Heng Yin, Le Song, Dawn Song:
Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity Detection. CoRR abs/1708.06525 (2017) - [i42]Yuyu Zhang, Hanjun Dai, Zornitsa Kozareva, Alexander J. Smola, Le Song:
Variational Reasoning for Question Answering with Knowledge Graph. CoRR abs/1709.04071 (2017) - [i41]Weiyang Liu, Bo Dai, Xingguo Li, James M. Rehg, Le Song:
Towards Black-box Iterative Machine Teaching. CoRR abs/1710.07742 (2017) - [i40]Weiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhiding Yu, Bo Dai, Tuo Zhao, Le Song:
Deep Hyperspherical Learning. CoRR abs/1711.03189 (2017) - [i39]Bo Dai, Albert E. Shaw, Niao He, Lihong Li, Le Song:
Boosting the Actor with Dual Critic. CoRR abs/1712.10282 (2017) - [i38]Bo Dai, Albert E. Shaw, Lihong Li, Lin Xiao, Niao He, Jianshu Chen, Le Song:
Smoothed Dual Embedding Control. CoRR abs/1712.10285 (2017) - 2016
- [j16]Manuel Gomez-Rodriguez, Le Song, Hadi Daneshmand, Bernhard Schölkopf:
Estimating Diffusion Networks: Recovery Conditions, Sample Complexity and Soft-thresholding Algorithm. J. Mach. Learn. Res. 17: 90:1-90:29 (2016) - [j15]MiaoMiao Cai, Wen Chen, Danan Dong, Le Song, Minghua Wang, Zhiren Wang, Feng Zhou, Zhengqi Zheng, Chao Yu:
Reduction of Kinematic Short Baseline Multipath Effects Based on Multipath Hemispherical Map. Sensors 16(10): 1677 (2016) - [j14]Manuel Gomez-Rodriguez, Le Song, Nan Du, Hongyuan Zha, Bernhard Schölkopf:
Influence Estimation and Maximization in Continuous-Time Diffusion Networks. ACM Trans. Inf. Syst. 34(2): 9:1-9:33 (2016) - [c84]Elias Boutros Khalil, Pierre Le Bodic, Le Song, George L. Nemhauser, Bistra Dilkina:
Learning to Branch in Mixed Integer Programming. AAAI 2016: 724-731 - [c83]Yu Nishiyama, Amir Afsharinejad, Shunsuke Naruse, Byron Boots, Le Song:
The Nonparametric Kernel Bayes Smoother. AISTATS 2016: 547-555 - [c82]Bo Dai, Niao He, Hanjun Dai, Le Song:
Provable Bayesian Inference via Particle Mirror Descent. AISTATS 2016: 985-994 - [c81]Yichen Wang, Bo Xie, Nan Du, Le Song:
Isotonic Hawkes Processes. ICML 2016: 2226-2234 - [c80]Hanjun Dai, Bo Dai, Le Song:
Discriminative Embeddings of Latent Variable Models for Structured Data. ICML 2016: 2702-2711 - [c79]Maria-Florina Balcan, Yingyu Liang, Le Song, David P. Woodruff, Bo Xie:
Communication Efficient Distributed Kernel Principal Component Analysis. KDD 2016: 725-734 - [c78]Nan Du, Hanjun Dai, Rakshit Trivedi, Utkarsh Upadhyay, Manuel Gomez-Rodriguez, Le Song:
Recurrent Marked Temporal Point Processes: Embedding Event History to Vector. KDD 2016: 1555-1564 - [c77]Mohammad Reza Karimi, Erfan Tavakoli, Mehrdad Farajtabar, Le Song, Manuel Gomez-Rodriguez:
Smart Broadcasting: Do You Want to be Seen? KDD 2016: 1635-1644 - [c76]Yichen Wang, Nan Du, Rakshit Trivedi, Le Song:
Coevolutionary Latent Feature Processes for Continuous-Time User-Item Interactions. NIPS 2016: 4547-4555 - [c75]Mehrdad Farajtabar, Xiaojing Ye, Sahar Harati, Le Song, Hongyuan Zha:
Multistage Campaigning in Social Networks. NIPS 2016: 4718-4726 - [c74]Hanjun Dai, Yichen Wang, Rakshit Trivedi, Le Song:
Recurrent Coevolutionary Latent Feature Processes for Continuous-Time Recommendation. DLRS@RecSys 2016: 29-34 - [i37]Hanjun Dai, Bo Dai, Le Song:
Discriminative Embeddings of Latent Variable Models for Structured Data. CoRR abs/1603.05629 (2016) - [i36]Shuang Li, Yao Xie, Mehrdad Farajtabar, Le Song:
Detecting weak changes in dynamic events over networks. CoRR abs/1603.08981 (2016) - [i35]Yichen Wang, Evangelos A. Theodorou, Apurv Verma, Le Song:
Steering Opinion Dynamics in Information Diffusion Networks. CoRR abs/1603.09021 (2016) - [i34]Mohammad Reza Karimi, Erfan Tavakoli, Mehrdad Farajtabar, Le Song, Manuel Gomez-Rodriguez:
Smart broadcasting: Do you want to be seen? CoRR abs/1605.06855 (2016) - [i33]Mehrdad Farajtabar, Xiaojing Ye, Sahar Harati, Le Song, Hongyuan Zha:
Multistage Campaigning in Social Networks. CoRR abs/1606.03816 (2016) - [i32]Bo Dai, Niao He, Yunpeng Pan, Byron Boots, Le Song:
Learning from Conditional Distributions via Dual Kernel Embeddings. CoRR abs/1607.04579 (2016) - [i31]Niao He, Zaïd Harchaoui, Yichen Wang, Le Song:
Fast and Simple Optimization for Poisson Likelihood Models. CoRR abs/1608.01264 (2016) - [i30]Hanjun Dai, Yichen Wang, Rakshit Trivedi, Le Song:
Recurrent Coevolutionary Feature Embedding Processes for Recommendation. CoRR abs/1609.03675 (2016) - [i29]Shuang Li, Yao Xie, Le Song:
Data-Driven Threshold Machine: Scan Statistics, Change-Point Detection, and Extreme Bandits. CoRR abs/1610.04599 (2016) - [i28]Behzad Tabibian, Isabel Valera, Mehrdad Farajtabar, Le Song, Bernhard Schölkopf, Manuel Gomez-Rodriguez:
Distilling Information Reliability and Source Trustworthiness from Digital Traces. CoRR abs/1610.07472 (2016) - [i27]Bo Xie, Yingyu Liang, Le Song:
Diversity Leads to Generalization in Neural Networks. CoRR abs/1611.03131 (2016) - [i26]Edward Choi, Mohammad Taha Bahadori, Le Song, Walter F. Stewart, Jimeng Sun:
GRAM: Graph-based Attention Model for Healthcare Representation Learning. CoRR abs/1611.07012 (2016) - [i25]Nan Du, Yingyu Liang, Maria-Florina Balcan, Manuel Gomez-Rodriguez, Hongyuan Zha, Le Song:
Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks. CoRR abs/1612.02712 (2016) - 2015
- [j13]Hu Gong, Yi Wang, Le Song, Fengzhou Fang:
Spiral tool path generation for diamond turning optical freeform surfaces of quasi-revolution. Comput. Aided Des. 59: 15-22 (2015) - [c73]Mehrdad Farajtabar, Manuel Gomez-Rodriguez, Mohammad Zamani, Nan Du, Hongyuan Zha, Le Song:
Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades. AISTATS 2015 - [c72]Zichao Yang, Andrew Gordon Wilson, Alexander J. Smola, Le Song:
A la Carte - Learning Fast Kernels. AISTATS 2015 - [c71]Zichao Yang, Marcin Moczulski, Misha Denil, Nando de Freitas, Alexander J. Smola, Le Song, Ziyu Wang:
Deep Fried Convnets. ICCV 2015: 1476-1483 - [c70]Edward Choi, Nan Du, Robert Chen, Le Song, Jimeng Sun:
Constructing Disease Network and Temporal Progression Model via Context-Sensitive Hawkes Process. ICDM 2015: 721-726 - [c69]Yang You, James Demmel, Kenneth Czechowski, Le Song, Richard W. Vuduc:
CA-SVM: Communication-Avoiding Support Vector Machines on Distributed Systems. IPDPS 2015: 847-859 - [c68]Nan Du, Mehrdad Farajtabar, Amr Ahmed, Alexander J. Smola, Le Song:
Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams. KDD 2015: 219-228 - [c67]Manuel Gomez-Rodriguez, Le Song:
Diffusion in Social and Information Networks: Research Problems, Probabilistic Models and Machine Learning Methods. KDD 2015: 2315-2316 - [c66]Mehrdad Farajtabar, Yichen Wang, Manuel Gomez-Rodriguez, Shuang Li, Hongyuan Zha, Le Song:
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution. NIPS 2015: 1954-1962 - [c65]Bo Xie, Yingyu Liang, Le Song:
Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients. NIPS 2015: 2341-2349 - [c64]Shuang Li, Yao Xie, Hanjun Dai, Le Song:
M-Statistic for Kernel Change-Point Detection. NIPS 2015: 3366-3374 - [c63]Nan Du, Yichen Wang, Niao He, Jimeng Sun, Le Song:
Time-Sensitive Recommendation From Recurrent User Activities. NIPS 2015: 3492-3500 - [c62]Yu-Ying Liu, Shuang Li, Fuxin Li, Le Song, James M. Rehg:
Efficient Learning of Continuous-Time Hidden Markov Models for Disease Progression. NIPS 2015: 3600-3608 - [c61]Long Q. Tran, Mehrdad Farajtabar, Le Song, Hongyuan Zha:
NetCodec: Community Detection from Individual Activities. SDM 2015: 91-99 - [c60]Amirreza Shaban, Mehrdad Farajtabar, Bo Xie, Le Song, Byron Boots:
Learning Latent Variable Models by Improving Spectral Solutions with Exterior Point Method. UAI 2015: 792-801 - [c59]Mehrdad Farajtabar, Manuel Gomez-Rodriguez, Yichen Wang, Shuang Li, Hongyuan Zha, Le Song:
Co-evolutionary Dynamics of Information Diffusion and Network Structure. WWW (Companion Volume) 2015: 619-620 - [c58]Manuel Gomez-Rodriguez, Le Song:
Diffusion in Social and Information Metworks: Research Problems; Probabilistic Models & Machine Learning Methods. WWW (Companion Volume) 2015: 1527-1528 - [i24]Mehrdad Farajtabar, Manuel Gomez-Rodriguez, Nan Du, Mohammad Zamani, Hongyuan Zha, Le Song:
Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades. CoRR abs/1501.06582 (2015) - [i23]Maria-Florina Balcan, Yingyu Liang, Le Song, David P. Woodruff, Bo Xie:
Distributed Kernel Principal Component Analysis. CoRR abs/1503.06858 (2015) - [i22]Bo Xie, Yingyu Liang, Le Song:
Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients. CoRR abs/1504.03655 (2015) - [i21]Bo Dai, Niao He, Hanjun Dai, Le Song:
Scalable Bayesian Inference via Particle Mirror Descent. CoRR abs/1506.03101 (2015) - [i20]Shuang Li, Yao Xie, Hanjun Dai, Le Song:
M-Statistic for Kernel Change-Point Detection. CoRR abs/1507.01279 (2015) - [i19]Mehrdad Farajtabar, Yichen Wang, Manuel Gomez-Rodriguez, Shuang Li, Hongyuan Zha, Le Song:
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution. CoRR abs/1507.02293 (2015) - [i18]Yao Xie, Ruiyang Song, Hanjun Dai, Qingbin Li, Le Song:
Online Supervised Subspace Tracking. CoRR abs/1509.00137 (2015) - [i17]Ali Zarezade, Ali Khodadadi, Mehrdad Farajtabar, Hamid R. Rabiee, Le Song, Hongyuan Zha:
Correlated Cascades: Compete or Cooperate. CoRR abs/1510.00936 (2015) - [i16]Mehrdad Farajtabar, Safoora Yousefi, Long Q. Tran, Le Song, Hongyuan Zha:
A Continuous-time Mutually-Exciting Point Process Framework for Prioritizing Events in Social Media. CoRR abs/1511.04145 (2015) - 2014
- [c57]Manuel Gomez-Rodriguez, Le Song, Bernhard Schölkopf:
Open Problem: Finding Good Cascade Sampling Processes for the Network Inference Problem. COLT 2014: 1276-1279 - [c56]Alekh Agarwal, Sham M. Kakade, Nikos Karampatziakis, Le Song, Gregory Valiant:
Least Squares Revisited: Scalable Approaches for Multi-class Prediction. ICML 2014: 541-549 - [c55]Le Song, Animashree Anandkumar, Bo Dai, Bo Xie:
Nonparametric Estimation of Multi-View Latent Variable Models. ICML 2014: 640-648 - [c54]Hadi Daneshmand, Manuel Gomez-Rodriguez, Le Song, Bernhard Schölkopf:
Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm. ICML 2014: 793-801 - [c53]Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song:
Influence Function Learning in Information Diffusion Networks. ICML 2014: 2016-2024 - [c52]Elias Boutros Khalil, Bistra Dilkina, Le Song:
Scalable diffusion-aware optimization of network topology. KDD 2014: 1226-1235 - [c51]Maria-Florina Balcan, Christopher Berlind, Avrim Blum, Emma Cohen, Kaushik Patnaik, Le Song:
Active Learning and Best-Response Dynamics. NIPS 2014: 2222-2230 - [c50]Mehrdad Farajtabar, Nan Du, Manuel Gomez-Rodriguez, Isabel Valera, Hongyuan Zha, Le Song:
Shaping Social Activity by Incentivizing Users. NIPS 2014: 2474-2482 - [c49]Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, Le Song:
Scalable Kernel Methods via Doubly Stochastic Gradients. NIPS 2014: 3041-3049 - [c48]Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song:
Learning Time-Varying Coverage Functions. NIPS 2014: 3374-3382 - [i15]Hadi Daneshmand, Manuel Gomez-Rodriguez, Le Song, Bernhard Schölkopf:
Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm. CoRR abs/1405.2936 (2014) - [i14]Maria-Florina Balcan, Christopher Berlind, Avrim Blum, Emma Cohen, Kaushik Patnaik, Le Song:
Active Learning and Best-Response Dynamics. CoRR abs/1406.6633 (2014) - [i13]Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, Le Song:
Scalable Kernel Methods via Doubly Stochastic Gradients. CoRR abs/1407.5599 (2014) - [i12]Mehrdad Farajtabar, Nan Du, Manuel Gomez-Rodriguez, Isabel Valera, Hongyuan Zha, Le Song:
Shaping Social Activity by Incentivizing Users. CoRR abs/1408.0406 (2014) - [i11]Zichao Yang, Alexander J. Smola, Le Song, Andrew Gordon Wilson:
A la Carte - Learning Fast Kernels. CoRR abs/1412.6493 (2014) - [i10]Zichao Yang, Marcin Moczulski, Misha Denil, Nando de Freitas, Alexander J. Smola, Le Song, Ziyu Wang:
Deep Fried Convnets. CoRR abs/1412.7149 (2014) - 2013
- [j12]Bo Xie, Boris R. Jankovic, Vladimir B. Bajic, Le Song, Xin Gao:
Poly(A) motif prediction using spectral latent features from human DNA sequences. Bioinform. 29(13): 316-325 (2013) - [j11]Le Song, Zihui Zhang, Haoyang Zhang:
A biologically-inspired embedded monitoring network system for moving target detection in panoramic view. EURASIP J. Wirel. Commun. Netw. 2013: 175 (2013) - [j10]Le Song, Zihui Zhang:
Calibration Method for Stereovision Measurement of High-Temperature Components Using Two Infrared Cameras. Int. J. Autom. Technol. 7(2): 163-170 (2013) - [j9]Kenji Fukumizu, Le Song, Arthur Gretton:
Kernel Bayes' rule: Bayesian inference with positive definite kernels. J. Mach. Learn. Res. 14(1): 3753-3783 (2013) - [j8]Le Song, Kenji Fukumizu, Arthur Gretton:
Kernel Embeddings of Conditional Distributions: A Unified Kernel Framework for Nonparametric Inference in Graphical Models. IEEE Signal Process. Mag. 30(4): 98-111 (2013) - [c47]Nan Du, Le Song, Hyenkyun Woo, Hongyuan Zha:
Uncover Topic-Sensitive Information Diffusion Networks. AISTATS 2013: 229-237 - [c46]Ke Zhou, Hongyuan Zha, Le Song:
Learning Social Infectivity in Sparse Low-rank Networks Using Multi-dimensional Hawkes Processes. AISTATS 2013: 641-649 - [c45]Mariya Ishteva, Haesun Park, Le Song:
Unfolding Latent Tree Structures using 4th Order Tensors. ICML (3) 2013: 316-324 - [c44]Le Song, Mariya Ishteva, Ankur P. Parikh, Eric P. Xing, Haesun Park:
Hierarchical Tensor Decomposition of Latent Tree Graphical Models. ICML (3) 2013: 334-342 - [c43]Ke Zhou, Hongyuan Zha, Le Song:
Learning Triggering Kernels for Multi-dimensional Hawkes Processes. ICML (3) 2013: 1301-1309 - [c42]Nan Du, Le Song, Manuel Gomez-Rodriguez, Hongyuan Zha:
Scalable Influence Estimation in Continuous-Time Diffusion Networks. NIPS 2013: 3147-3155 - [c41]Le Song, Bo Dai:
Robust Low Rank Kernel Embeddings of Multivariate Distributions. NIPS 2013: 3228-3236 - [i9]Alekh Agarwal, Sham M. Kakade, Nikos Karampatziakis, Le Song, Gregory Valiant:
Least Squares Revisited: Scalable Approaches for Multi-class Prediction. CoRR abs/1310.1949 (2013) - [i8]Le Song, Animashree Anandkumar, Bo Dai, Bo Xie:
Nonparametric Estimation of Multi-View Latent Variable Models. CoRR abs/1311.3287 (2013) - [i7]Nan Du, Le Song, Manuel Gomez-Rodriguez, Hongyuan Zha:
Scalable Influence Estimation in Continuous-Time Diffusion Networks. CoRR abs/1311.3669 (2013) - [i6]Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song:
Continuous-Time Influence Maximization for Multiple Items. CoRR abs/1312.2164 (2013) - 2012
- [j7]Le Song, Alexander J. Smola, Arthur Gretton, Justin Bedo, Karsten M. Borgwardt:
Feature Selection via Dependence Maximization. J. Mach. Learn. Res. 13: 1393-1434 (2012) - [c40]Zhongcai Pei, Le Song, Bin Chen, Xiaoqiang Guo:
Adaptive control of a quadruped robot based on Central Pattern Generators. INDIN 2012: 554-558 - [c39]Nan Du, Le Song, Alexander J. Smola, Ming Yuan:
Learning Networks of Heterogeneous Influence. NIPS 2012: 2789-2797 - [c38]Ankur P. Parikh, Le Song, Mariya Ishteva, Gabi Teodoru, Eric P. Xing:
A Spectral Algorithm for Latent Junction Trees. UAI 2012: 675-684 - [i5]Mariya Ishteva, Haesun Park, Le Song:
Unfolding Latent Tree Structures using 4th Order Tensors. CoRR abs/1210.1258 (2012) - [i4]Ankur P. Parikh, Le Song, Mariya Ishteva, Gabi Teodoru, Eric P. Xing:
A Spectral Algorithm for Latent Junction Trees. CoRR abs/1210.4884 (2012) - 2011
- [j6]Ross E. Curtis, Amos Yuen, Le Song, Anuj Goyal, Eric P. Xing:
TVNViewer: An interactive visualization tool for exploring networks that change over time or space. Bioinform. 27(13): 1880-1881 (2011) - [c37]Ankur P. Parikh, Le Song, Eric P. Xing:
A Spectral Algorithm for Latent Tree Graphical Models. ICML 2011: 1065-1072 - [c36]Kenji Fukumizu, Le Song, Arthur Gretton:
Kernel Bayes' Rule. NIPS 2011: 1737-1745 - [c35]Animashree Anandkumar, Kamalika Chaudhuri, Daniel J. Hsu, Sham M. Kakade, Le Song, Tong Zhang:
Spectral Methods for Learning Multivariate Latent Tree Structure. NIPS 2011: 2025-2033 - [c34]Le Song, Ankur P. Parikh, Eric P. Xing:
Kernel Embeddings of Latent Tree Graphical Models. NIPS 2011: 2708-2716 - [c33]Qirong Ho, Ankur P. Parikh, Le Song, Eric P. Xing:
Multiscale Community Blockmodel for Network Exploration. AISTATS 2011: 333-341 - [c32]Qirong Ho, Le Song, Eric P. Xing:
Evolving Cluster Mixed-Membership Blockmodel for Time-Evolving Networks. AISTATS 2011: 342-350 - [c31]Le Song, Arthur Gretton, Danny Bickson, Yucheng Low, Carlos Guestrin:
Kernel Belief Propagation. AISTATS 2011: 707-715 - [i3]Le Song, Arthur Gretton, Danny Bickson, Yucheng Low, Carlos Guestrin:
Kernel Belief Propagation. CoRR abs/1105.5592 (2011) - [i2]Animashree Anandkumar, Kamalika Chaudhuri, Daniel J. Hsu, Sham M. Kakade, Le Song, Tong Zhang:
Spectral Methods for Learning Multivariate Latent Tree Structure. CoRR abs/1107.1283 (2011) - 2010
- [j5]Novi Quadrianto, Alexander J. Smola, Le Song, Tinne Tuytelaars:
Kernelized Sorting. IEEE Trans. Pattern Anal. Mach. Intell. 32(10): 1809-1821 (2010) - [j4]Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei Han, Hans-Peter Kriegel, Alexander J. Smola, Le Song, Philip S. Yu, Xifeng Yan, Karsten M. Borgwardt:
Discriminative frequent subgraph mining with optimality guarantees. Stat. Anal. Data Min. 3(5): 302-318 (2010) - [c30]Le Song, Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon, Alexander J. Smola:
Hilbert Space Embeddings of Hidden Markov Models. ICML 2010: 991-998 - [c29]Xiuting Duan, Tingting He, Le Song:
Research on sentiment classification of Blog based on PMI-IR. NLPKE 2010: 1-6 - [c28]Tzu-Kuo Huang, Le Song, Jeff G. Schneider:
Learning Nonlinear Dynamic Models from Non-sequenced Data. AISTATS 2010: 350-357 - [c27]Le Song, Arthur Gretton, Carlos Guestrin:
Nonparametric Tree Graphical Models. AISTATS 2010: 765-772
2000 – 2009
- 2009
- [j3]Le Song, Mladen Kolar, Eric P. Xing:
KELLER: estimating time-varying interactions between genes. Bioinform. 25(12) (2009) - [c26]Wenjie Fu, Le Song, Eric P. Xing:
Dynamic mixed membership blockmodel for evolving networks. ICML 2009: 329-336 - [c25]Le Song, Jonathan Huang, Alexander J. Smola, Kenji Fukumizu:
Hilbert space embeddings of conditional distributions with applications to dynamical systems. ICML 2009: 961-968 - [c24]Mladen Kolar, Le Song, Eric P. Xing:
Sparsistent Learning of Varying-coefficient Models with Structural Changes. NIPS 2009: 1006-1014 - [c23]Le Song, Mladen Kolar, Eric P. Xing:
Time-Varying Dynamic Bayesian Networks. NIPS 2009: 1732-1740 - [c22]Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei Han, Hans-Peter Kriegel, Alexander J. Smola, Le Song, Philip S. Yu, Xifeng Yan, Karsten M. Borgwardt:
Near-optimal Supervised Feature Selection among Frequent Subgraphs. SDM 2009: 1076-1087 - [c21]Alexander J. Smola, Le Song, Choon Hui Teo:
Relative Novelty Detection. AISTATS 2009: 536-543 - 2008
- [c20]Le Song, Xinhua Zhang, Alexander J. Smola, Arthur Gretton, Bernhard Schölkopf:
Tailoring density estimation via reproducing kernel moment matching. ICML 2008: 992-999 - [c19]Novi Quadrianto, Le Song, Alexander J. Smola:
Kernelized Sorting. NIPS 2008: 1289-1296 - [c18]Xinhua Zhang, Le Song, Arthur Gretton, Alexander J. Smola:
Kernel Measures of Independence for non-iid Data. NIPS 2008: 1937-1944 - 2007
- [j2]Le Song, Julien Epps:
Classifying EEG for Brain-Computer Interface: Learning Optimal Filters for Dynamical System Features. Comput. Intell. Neurosci. 2007 (2007) - [c17]Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf:
A Hilbert Space Embedding for Distributions. ALT 2007: 13-31 - [c16]Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf:
A Hilbert Space Embedding for Distributions. Discovery Science 2007: 40-41 - [c15]Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt:
A dependence maximization view of clustering. ICML 2007: 815-822 - [c14]Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Justin Bedo:
Supervised feature selection via dependence estimation. ICML 2007: 823-830 - [c13]Le Song, Yuchi Lin:
Method for Automatic Image Recognition based on Algorithm Fusion. ICNC (2) 2007: 671-675 - [c12]Le Song, Yuchi Lin:
Study on the Vision Reading Algorithm based on Template Matching and Neural Network. IJCNN 2007: 967-972 - [c11]Le Song, Justin Bedo, Karsten M. Borgwardt, Arthur Gretton, Alexander J. Smola:
Gene selection via the BAHSIC family of algorithms. ISMB/ECCB (Supplement of Bioinformatics) 2007: 490-498 - [c10]Arthur Gretton, Kenji Fukumizu, Choon Hui Teo, Le Song, Bernhard Schölkopf, Alexander J. Smola:
A Kernel Statistical Test of Independence. NIPS 2007: 585-592 - [c9]Le Song, Alexander J. Smola, Karsten M. Borgwardt, Arthur Gretton:
Colored Maximum Variance Unfolding. NIPS 2007: 1385-1392 - [i1]Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Justin Bedo:
Supervised Feature Selection via Dependence Estimation. CoRR abs/0704.2668 (2007) - 2006
- [j1]Leanne M. Williams, Donna M. Palmer, Belinda J. Liddell, Le Song, Evian Gordon:
The 'when' and 'where' of perceiving signals of threat versus non-threat. NeuroImage 31(1): 458-467 (2006) - [c8]Le Song, Julien Epps:
Improving Separability of Eeg Signals During Motor Imagery With An Efficient Circular Laplacian. ICASSP (2) 2006: 1048-1051 - [c7]Le Song, Julien Epps:
Classifying EEG for brain-computer interfaces: learning optimal filters for dynamical system features. ICML 2006: 857-864 - 2005
- [c6]Lanbo Zheng, Le Song, Peter Eades:
Crossing Minimization Problems of Drawing Bipartite Graphs in Two Clusters. APVIS 2005: 33-37 - [c5]Le Song, Masahiro Takatsuka:
Real-time 3D Finger Pointing for an Augmented Desk. AUIC 2005: 99-108 - [c4]Weidong Huang, Colin Murray, Xiaobin Shen, Le Song, Ying Xin Wu, Lanbo Zheng:
Visualisation and Analysis of Network Motifs. IV 2005: 697-702 - [c3]Le Song, Evian Gordon, Elly Gysels:
Phase Synchrony Rate for the Recognition of Motor Imagery in Brain-Computer Interface. NIPS 2005: 1265-1272 - [c2]Adel Ahmed, Tim Dwyer, Seok-Hee Hong, Colin Murray, Le Song, Ying Xin Wu:
Visualisation and Analysis of Large and Complex Scale-free Networks. EuroVis 2005: 239-246 - 2004
- [c1]Adel Ahmed, Tim Dwyer, Colin Murray, Le Song, Ying Xin Wu:
WilmaScope Graph Visualisation. INFOVIS 2004
Coauthor Index
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