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2020 – today
- 2024
[c38]Xianrui Zhong, Yufeng Du, Siru Ouyang, Ming Zhong, Tingfeng Luo, Qirong Ho, Hao Peng, Heng Ji, Jiawei Han:
ActionIE: Action Extraction from Scientific Literature with Programming Languages. ACL (1) 2024: 12656-12671- [i20]Chenxu Yang, Zheng Lin, Chong Tian, Liang Pang, Lanrui Wang, Zhengyang Tong, Qirong Ho, Yanan Cao, Weiping Wang:
A Factuality and Diversity Reconciled Decoding Method for Knowledge-Grounded Dialogue Generation. CoRR abs/2407.05718 (2024) - [i19]Boyang Sun, Ignavier Ng, Guangyi Chen, Yifan Shen, Qirong Ho, Kun Zhang:
Continual Learning of Nonlinear Independent Representations. CoRR abs/2408.05788 (2024) - 2023
- [c37]Chenxu Yang, Zheng Lin, Lanrui Wang, Chong Tian, Liang Pang, Jiangnan Li, Qirong Ho, Yanan Cao, Weiping Wang:
Multi-level Adaptive Contrastive Learning for Knowledge Internalization in Dialogue Generation. EMNLP 2023: 8002-8015 - [c36]Yonghao Zhuang, Lianmin Zheng, Zhuohan Li, Eric P. Xing, Qirong Ho, Joseph Gonzalez, Ion Stoica, Hao Zhang, Hexu Zhao:
On Optimizing the Communication of Model Parallelism. MLSys 2023 - [c35]Junbo Li, Ang Li, Chong Tian, Qirong Ho, Eric P. Xing, Hongyi Wang:
FedNAR: Federated Optimization with Normalized Annealing Regularization. NeurIPS 2023 - [i18]Junbo Li, Ang Li, Chong Tian, Qirong Ho, Eric P. Xing, Hongyi Wang:
FedNAR: Federated Optimization with Normalized Annealing Regularization. CoRR abs/2310.03163 (2023) - [i17]Chenxu Yang, Zheng Lin, Lanrui Wang, Chong Tian, Liang Pang, Jiangnan Li, Qirong Ho, Yanan Cao, Weiping Wang:
Multi-level Adaptive Contrastive Learning for Knowledge Internalization in Dialogue Generation. CoRR abs/2310.08943 (2023) - 2022
- [c34]Shaoan Xie, Qirong Ho, Kun Zhang:
Unsupervised Image-to-Image Translation with Density Changing Regularization. NeurIPS 2022 - [i16]Yonghao Zhuang, Hexu Zhao, Lianmin Zheng, Zhuohan Li, Eric P. Xing, Qirong Ho, Joseph E. Gonzalez
, Ion Stoica, Hao Zhang:
On Optimizing the Communication of Model Parallelism. CoRR abs/2211.05322 (2022) - 2021
- [c33]Aurick Qiao, Sang Keun Choe, Suhas Jayaram Subramanya, Willie Neiswanger, Qirong Ho, Hao Zhang, Gregory R. Ganger, Eric P. Xing:
Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning. OSDI 2021 - 2020
- [i15]Aurick Qiao, Willie Neiswanger, Qirong Ho, Hao Zhang, Gregory R. Ganger, Eric P. Xing:
Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning. CoRR abs/2008.12260 (2020)
2010 – 2019
- 2018
- [c32]Pengtao Xie, Jin Kyu Kim, Qirong Ho, Yaoliang Yu, Eric P. Xing:
Orpheus: Efficient Distributed Machine Learning via System and Algorithm Co-design. SoCC 2018: 1-13 - [c31]Aurick Qiao, Abutalib Aghayev, Weiren Yu, Haoyang Chen, Qirong Ho, Garth A. Gibson, Eric P. Xing:
Litz: Elastic Framework for High-Performance Distributed Machine Learning. USENIX ATC 2018: 631-644 - [c30]Shizhen Xu, Hao Zhang, Graham Neubig, Wei Dai, Jin Kyu Kim, Zhijie Deng, Qirong Ho, Guangwen Yang, Eric P. Xing:
Cavs: An Efficient Runtime System for Dynamic Neural Networks. USENIX ATC 2018: 937-950 - 2017
- [c29]Sulin Liu, Sinno Jialin Pan, Qirong Ho:
Distributed Multi-Task Relationship Learning. KDD 2017: 937-946 - [c28]Hao Zhang, Zeyu Zheng, Shizhen Xu, Wei Dai, Qirong Ho, Xiaodan Liang, Zhiting Hu, Jinliang Wei, Pengtao Xie, Eric P. Xing:
Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters. USENIX ATC 2017: 181-193 - [i14]Hao Zhang, Zeyu Zheng, Shizhen Xu, Wei Dai, Qirong Ho, Xiaodan Liang, Zhiting Hu, Jinliang Wei, Pengtao Xie, Eric P. Xing:
Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters. CoRR abs/1706.03292 (2017) - [i13]Hao Zhang, Shizhen Xu, Graham Neubig, Wei Dai, Qirong Ho, Guangwen Yang, Eric P. Xing:
Cavs: A Vertex-centric Programming Interface for Dynamic Neural Networks. CoRR abs/1712.04048 (2017) - 2016
- [j3]Qirong Ho, Junming Yin, Eric P. Xing:
Latent Space Inference of Internet-Scale Networks. J. Mach. Learn. Res. 17: 78:1-78:41 (2016) - [j2]Tingting Chen, Fan Wu, Tony T. Luo, Mea Wang, Qirong Ho:
Big Data Management and Analytics for Mobile Crowd Sensing. Mob. Inf. Syst. 2016: 8731802:1-8731802:2 (2016) - [c27]Qirong Ho, Wenqing Lin, Eran Shaham, Shonali Krishnaswamy, The Anh Dang, Jingxuan Wang, Isabel Choo Zhongyan, Amy She-Nash:
A Distributed Graph Algorithm for Discovering Unique Behavioral Groups from Large-Scale Telco Data. CIKM 2016: 1353-1362 - [c26]Jin Kyu Kim, Qirong Ho, Seunghak Lee, Xun Zheng, Wei Dai, Garth A. Gibson, Eric P. Xing:
STRADS: a distributed framework for scheduled model parallel machine learning. EuroSys 2016: 5:1-5:16 - [c25]Lizi Liao, Qirong Ho, Jing Jiang, Ee-Peng Lim:
SLR: A scalable latent role model for attribute completion and tie prediction in social networks. ICDE 2016: 1062-1073 - [c24]Ali Zonoozi, Qirong Ho, Shonali Krishnaswamy, Gao Cong:
ConTrack: A Scalable Method for Tracking Multiple Concepts in Large Scale Multidimensional Data. ICDM 2016: 759-768 - [c23]Yinyan Tan, Zhe Fan, Guilin Li, Fangshan Wang, Zhengbing Li, Shikai Liu, Qiuling Pan, Eric P. Xing, Qirong Ho:
Scalable Time-Decaying Adaptive Prediction Algorithm. KDD 2016: 617-626 - [c22]Pengtao Xie, Jin Kyu Kim, Yi Zhou, Qirong Ho, Abhimanu Kumar, Yaoliang Yu, Eric P. Xing:
Lighter-Communication Distributed Machine Learning via Sufficient Factor Broadcasting. UAI 2016 - [i12]Sulin Liu, Sinno Jialin Pan, Qirong Ho:
Distributed Multi-task Relationship Learning. CoRR abs/1612.04022 (2016) - 2015
- [j1]Eric P. Xing, Qirong Ho, Wei Dai, Jin Kyu Kim, Jinliang Wei, Seunghak Lee, Xun Zheng, Pengtao Xie, Abhimanu Kumar, Yaoliang Yu:
Petuum: A New Platform for Distributed Machine Learning on Big Data. IEEE Trans. Big Data 1(2): 49-67 (2015) - [c21]Wei Dai, Abhimanu Kumar, Jinliang Wei, Qirong Ho, Garth A. Gibson, Eric P. Xing:
High-Performance Distributed ML at Scale through Parameter Server Consistency Models. AAAI 2015: 79-87 - [c20]Jinliang Wei, Wei Dai, Aurick Qiao, Qirong Ho, Henggang Cui, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, Eric P. Xing:
Managed communication and consistency for fast data-parallel iterative analytics. SoCC 2015: 381-394 - [c19]Zhiting Hu, Qirong Ho, Avinava Dubey, Eric P. Xing:
Large-scale Distributed Dependent Nonparametric Trees. ICML 2015: 1651-1659 - [c18]Eric P. Xing, Qirong Ho, Wei Dai, Jin Kyu Kim, Jinliang Wei, Seunghak Lee, Xun Zheng, Pengtao Xie, Abhimanu Kumar, Yaoliang Yu:
Petuum: A New Platform for Distributed Machine Learning on Big Data. KDD 2015: 1335-1344 - [c17]Jinhui Yuan, Fei Gao, Qirong Ho, Wei Dai, Jinliang Wei, Xun Zheng, Eric Poe Xing, Tie-Yan Liu, Wei-Ying Ma:
LightLDA: Big Topic Models on Modest Computer Clusters. WWW 2015: 1351-1361 - [i11]Pengtao Xie, Jin Kyu Kim, Yi Zhou, Qirong Ho, Abhimanu Kumar, Yaoliang Yu, Eric P. Xing:
Distributed Machine Learning via Sufficient Factor Broadcasting. CoRR abs/1511.08486 (2015) - [i10]Hao Zhang, Zhiting Hu, Jinliang Wei, Pengtao Xie, Gunhee Kim, Qirong Ho, Eric P. Xing:
Poseidon: A System Architecture for Efficient GPU-based Deep Learning on Multiple Machines. CoRR abs/1512.06216 (2015) - [i9]Eric P. Xing, Qirong Ho, Pengtao Xie, Wei Dai:
Strategies and Principles of Distributed Machine Learning on Big Data. CoRR abs/1512.09295 (2015) - 2014
- [c16]Abhimanu Kumar, Alex Beutel, Qirong Ho, Eric P. Xing:
Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data. AISTATS 2014: 531-539 - [c15]Henggang Cui, Alexey Tumanov, Jinliang Wei, Lianghong Xu, Wei Dai, Jesse Haber-Kucharsky, Qirong Ho, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, Eric P. Xing:
Exploiting iterative-ness for parallel ML computations. SoCC 2014: 5:1-5:14 - [c14]Kumar Avinava Dubey, Qirong Ho, Sinead A. Williamson, Eric P. Xing:
Dependent nonparametric trees for dynamic hierarchical clustering. NIPS 2014: 1152-1160 - [c13]Seunghak Lee, Jin Kyu Kim, Xun Zheng, Qirong Ho, Garth A. Gibson, Eric P. Xing:
On Model Parallelization and Scheduling Strategies for Distributed Machine Learning. NIPS 2014: 2834-2842 - [c12]Willie Neiswanger, Chong Wang, Qirong Ho, Eric P. Xing:
Modeling Citation Networks Using Latent Random Offsets. UAI 2014: 633-642 - [c11]Henggang Cui, James Cipar, Qirong Ho, Jin Kyu Kim, Seunghak Lee, Abhimanu Kumar, Jinliang Wei, Wei Dai, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, Eric P. Xing:
Exploiting Bounded Staleness to Speed Up Big Data Analytics. USENIX ATC 2014: 37-48 - [r1]Qirong Ho, Eric P. Xing:
Analyzing Time-Evolving Networks. Handbook of Mixed Membership Models and Their Applications 2014: 489-525 - [i8]Seunghak Lee, Jin Kyu Kim, Xun Zheng, Qirong Ho, Garth A. Gibson, Eric P. Xing:
Primitives for Dynamic Big Model Parallelism. CoRR abs/1406.4580 (2014) - [i7]Wei Dai, Abhimanu Kumar, Jinliang Wei, Qirong Ho, Garth A. Gibson, Eric P. Xing:
High-Performance Distributed ML at Scale through Parameter Server Consistency Models. CoRR abs/1410.8043 (2014) - [i6]Xun Zheng, Jin Kyu Kim, Qirong Ho, Eric P. Xing:
Model-Parallel Inference for Big Topic Models. CoRR abs/1411.2305 (2014) - [i5]Jinhui Yuan, Fei Gao, Qirong Ho, Wei Dai, Jinliang Wei, Xun Zheng, Eric P. Xing, Tie-Yan Liu, Wei-Ying Ma:
LightLDA: Big Topic Models on Modest Compute Clusters. CoRR abs/1412.1576 (2014) - 2013
- [c10]James Cipar, Qirong Ho, Jin Kyu Kim, Seunghak Lee, Gregory R. Ganger, Garth Gibson, Kimberly Keeton, Eric P. Xing:
Solving the Straggler Problem with Bounded Staleness. HotOS 2013 - [c9]Junming Yin, Qirong Ho, Eric P. Xing:
A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks. NIPS 2013: 422-430 - [c8]Qirong Ho, James Cipar, Henggang Cui, Seunghak Lee, Jin Kyu Kim, Phillip B. Gibbons, Garth A. Gibson, Gregory R. Ganger, Eric P. Xing:
More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server. NIPS 2013: 1223-1231 - [i4]Seunghak Lee, Jin Kyu Kim, Qirong Ho, Garth A. Gibson, Eric P. Xing:
Structure-Aware Dynamic Scheduler for Parallel Machine Learning. CoRR abs/1312.5766 (2013) - [i3]Wei Dai, Jinliang Wei, Xun Zheng, Jin Kyu Kim, Seunghak Lee, Junming Yin, Qirong Ho, Eric P. Xing:
Petuum: A Framework for Iterative-Convergent Distributed ML. CoRR abs/1312.7651 (2013) - [i2]Jinliang Wei, Wei Dai, Abhimanu Kumar, Xun Zheng, Qirong Ho, Eric P. Xing:
Consistent Bounded-Asynchronous Parameter Servers for Distributed ML. CoRR abs/1312.7869 (2013) - 2012
- [c7]Qirong Ho, Junming Yin, Eric P. Xing:
On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks. NIPS 2012: 2141-2149 - [c6]Qirong Ho, Jacob Eisenstein, Eric P. Xing:
Document hierarchies from text and links. WWW 2012: 739-748 - [i1]Qirong Ho, Rong Yan, Rajat Raina, Eric P. Xing:
Understanding the Interaction between Interests, Conversations and Friendships in Facebook. CoRR abs/1211.0028 (2012) - 2011
- [c5]Amr Ahmed, Qirong Ho, Jacob Eisenstein, Eric P. Xing, Alexander J. Smola, Choon Hui Teo:
Unified analysis of streaming news. WWW 2011: 267-276 - [c4]Amr Ahmed, Qirong Ho, Choon Hui Teo, Jacob Eisenstein, Alexander J. Smola, Eric P. Xing:
Online Inference for the Infinite Topic-Cluster Model: Storylines from Streaming Text. AISTATS 2011: 101-109 - [c3]Qirong Ho, Ankur P. Parikh, Le Song, Eric P. Xing:
Multiscale Community Blockmodel for Network Exploration. AISTATS 2011: 333-341 - [c2]Qirong Ho, Le Song, Eric P. Xing:
Evolving Cluster Mixed-Membership Blockmodel for Time-Evolving Networks. AISTATS 2011: 342-350
2000 – 2009
- 2009
- [c1]Qirong Ho, Weimiao Yu, Hwee Kuan Lee:
Region Graph Spectra as Geometric Global Image Features. ISVC (1) 2009: 253-264
Coauthor Index
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