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2020 – today
- 2024
[j21]Yihong Guo, Hao Liu, Yisong Yue, Anqi Liu:
Distributionally Robust Policy Evaluation under General Covariate Shift in Contextual Bandits. Trans. Mach. Learn. Res. 2024 (2024)- [c114]Alexander R. Farhang, Brendan Mulcahy, Daniel Holden, Iain Matthews, Yisong Yue:
Humanlike Behavior in a Third-Person Shooter with Imitation Learning. CoG 2024: 1-4 - [c113]Yiheng Lin, James A. Preiss, Fengze Xie, Emile Anand, Soon-Jo Chung, Yisong Yue, Adam Wierman:
Online Policy Optimization in Unknown Nonlinear Systems. COLT 2024: 3475-3522 - [c112]Ziniu Hu, Ahmet Iscen, Aashi Jain, Thomas Kipf, Yisong Yue, David A. Ross, Cordelia Schmid, Alireza Fathi:
SceneCraft: An LLM Agent for Synthesizing 3D Scenes as Blender Code. ICML 2024 - [c111]Yujia Huang, Adishree Ghatare, Yuanzhe Liu, Ziniu Hu, Qinsheng Zhang, Chandramouli Shama Sastry, Siddharth Gururani, Sageev Oore, Yisong Yue:
Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion. ICML 2024 - [c110]Francesca-Zhoufan Li, Ava P. Amini, Yisong Yue, Kevin K. Yang, Alex Xijie Lu:
Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models. ICML 2024 - [c109]Fengze Xie, Guanya Shi, Michael O'Connell, Yisong Yue, Soon-Jo Chung:
Hierarchical Meta-learning-based Adaptive Controller. ICRA 2024: 18309-10315 - [i132]Dan Zhang, Ziniu Hu, Sining Zhoubian, Zhengxiao Du, Kaiyu Yang, Zihan Wang, Yisong Yue, Yuxiao Dong, Jie Tang:
SciGLM: Training Scientific Language Models with Self-Reflective Instruction Annotation and Tuning. CoRR abs/2401.07950 (2024) - [i131]Yihong Guo, Hao Liu, Yisong Yue, Anqi Liu:
Distributionally Robust Policy Evaluation under General Covariate Shift in Contextual Bandits. CoRR abs/2401.11353 (2024) - [i130]Yujia Huang, Adishree Ghatare, Yuanzhe Liu, Ziniu Hu, Qinsheng Zhang, Chandramouli Shama Sastry, Siddharth Gururani, Sageev Oore, Yisong Yue:
Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion. CoRR abs/2402.14285 (2024) - [i129]Sabera Talukder, Yisong Yue, Georgia Gkioxari:
TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis. CoRR abs/2402.16412 (2024) - [i128]Geeling Chau, Yujin An, Ahamed Raffey Iqbal, Soon-Jo Chung, Yisong Yue, Sabera Talukder:
Generalizability Under Sensor Failure: Tokenization + Transformers Enable More Robust Latent Spaces. CoRR abs/2402.18546 (2024) - [i127]Ziniu Hu, Ahmet Iscen, Aashi Jain, Thomas Kipf, Yisong Yue, David A. Ross, Cordelia Schmid, Alireza Fathi:
SceneCraft: An LLM Agent for Synthesizing 3D Scene as Blender Code. CoRR abs/2403.01248 (2024) - [i126]Kejun Li, Jeeseop Kim, Xiaobin Xiong, Kaveh Akbari Hamed, Yisong Yue, Aaron D. Ames:
Data-Driven Predictive Control for Robust Exoskeleton Locomotion. CoRR abs/2403.15658 (2024) - [i125]Zihui Wu, Yu Sun, Yifan Chen, Bingliang Zhang, Yisong Yue, Katherine L. Bouman:
Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors. CoRR abs/2405.18782 (2024) - [i124]Min Cai, Yuchen Zhang, Shichang Zhang, Fan Yin, Difan Zou, Yisong Yue, Ziniu Hu:
Self-Control of LLM Behaviors by Compressing Suffix Gradient into Prefix Controller. CoRR abs/2406.02721 (2024) - [i123]Geeling Chau, Christopher Wang, Sabera Talukder, Vighnesh Subramaniam, Saraswati Soedarmadji, Yisong Yue, Boris Katz, Andrei Barbu:
Population Transformer: Learning Population-level Representations of Intracranial Activity. CoRR abs/2406.03044 (2024) - [i122]Dan Zhang, Sining Zhoubian, Yisong Yue, Yuxiao Dong, Jie Tang:
ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search. CoRR abs/2406.03816 (2024) - [i121]Raul Astudillo, Kejun Li, Maegan Tucker, Chu Xin Cheng, Aaron D. Ames, Yisong Yue:
Preferential Multi-Objective Bayesian Optimization. CoRR abs/2406.14699 (2024) - [i120]Zhengfei Zhang, Kishan Panaganti, Laixi Shi, Yanan Sui, Adam Wierman, Yisong Yue:
Distributionally Robust Constrained Reinforcement Learning under Strong Duality. CoRR abs/2406.15788 (2024) - [i119]Fanzeng Xia, Hao Liu, Yisong Yue, Tongxin Li:
Beyond Numeric Awards: In-Context Dueling Bandits with LLM Agents. CoRR abs/2407.01887 (2024) - [i118]Jonathan Light, Min Cai, Weiqin Chen, Guanzhi Wang, Xiusi Chen, Wei Cheng, Yisong Yue, Ziniu Hu:
Strategist: Learning Strategic Skills by LLMs via Bi-Level Tree Search. CoRR abs/2408.10635 (2024) - [i117]William D. Compton, Ivan Dario Jimenez Rodriguez, Noel Csomay-Shanklin, Yisong Yue, Aaron D. Ames:
Constructive Nonlinear Control of Underactuated Systems via Zero Dynamics Policies. CoRR abs/2408.14749 (2024) - [i116]Noel Csomay-Shanklin, William D. Compton, Ivan Dario Jimenez Rodriguez, Eric R. Ambrose, Yisong Yue, Aaron D. Ames:
Robust Agility via Learned Zero Dynamics Policies. CoRR abs/2409.06125 (2024) - [i115]Hongkai Zheng, Wenda Chu, Austin Wang, Nikola B. Kovachki, Ricardo Baptista, Yisong Yue:
Ensemble Kalman Diffusion Guidance: A Derivative-free Method for Inverse Problems. CoRR abs/2409.20175 (2024) - [i114]Christopher Yeh, Nicolas Christianson, Alan Wu, Adam Wierman, Yisong Yue:
End-to-End Conformal Calibration for Optimization Under Uncertainty. CoRR abs/2409.20534 (2024) - 2023
- [j20]Victor D. Dorobantu
, Kamyar Azizzadenesheli, Yisong Yue:
Compactly Restrictable Metric Policy Optimization Problems. IEEE Trans. Autom. Control. 68(5): 3115-3122 (2023) - [j19]Ugo Rosolia, Yuxiao Chen, Shreyansh Daftry, Masahiro Ono, Yisong Yue, Aaron D. Ames:
The Mixed-Observable Constrained Linear Quadratic Regulator Problem: The Exact Solution and Practical Algorithms. IEEE Trans. Autom. Control. 68(7): 4435-4442 (2023) - [c108]Jennifer J. Sun, Lili Karashchuk, Amil Dravid, Serim Ryou, Sonia Fereidooni, John C. Tuthill, Aggelos K. Katsaggelos, Bingni W. Brunton, Georgia Gkioxari, Ann Kennedy, Yisong Yue, Pietro Perona:
BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos. CVPR 2023: 9001-9010 - [c107]Jennifer J. Sun, Markus Marks, Andrew Wesley Ulmer, Dipam Chakraborty, Brian Geuther, Edward Hayes, Heng Jia, Vivek Kumar, Sebastian Oleszko, Zachary Partridge, Milan Peelman, Alice Robie, Catherine E. Schretter, Keith Sheppard, Chao Sun, Param Uttarwar, Julian Morgan Wagner, Erik Werner, Joseph Parker, Pietro Perona, Yisong Yue, Kristin Branson, Ann Kennedy:
MABe22: A Multi-Species Multi-Task Benchmark for Learned Representations of Behavior. ICML 2023: 32936-32990 - [c106]Cameron Voloshin, Abhinav Verma, Yisong Yue:
Eventual Discounting Temporal Logic Counterfactual Experience Replay. ICML 2023: 35137-35150 - [c105]Fengxue Zhang, Jialin Song, James C. Bowden, Alexander Ladd, Yisong Yue, Thomas Desautels, Yuxin Chen:
Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation. ICML 2023: 41579-41595 - [c104]Haoxuan Wang, Zhiding Yu, Yisong Yue, Animashree Anandkumar, Anqi Liu, Junchi Yan:
Learning Calibrated Uncertainties for Domain Shift: A Distributionally Robust Learning Approach. IJCAI 2023: 1460-1469 - [c103]Yiheng Lin, James A. Preiss, Emile Anand, Yingying Li, Yisong Yue, Adam Wierman:
Online Adaptive Policy Selection in Time-Varying Systems: No-Regret via Contractive Perturbations. NeurIPS 2023 - [c102]Christopher Yeh, Victor Li, Rajeev Datta, Julio Arroyo, Nicolas Christianson, Chi Zhang, Yize Chen, Mohammad Mehdi Hosseini, Azarang Golmohammadi, Yuanyuan Shi, Yisong Yue, Adam Wierman:
SustainGym: Reinforcement Learning Environments for Sustainable Energy Systems. NeurIPS 2023 - [i113]Cameron Voloshin, Abhinav Verma, Yisong Yue:
Eventual Discounting Temporal Logic Counterfactual Experience Replay. CoRR abs/2303.02135 (2023) - [i112]Victor D. Dorobantu, Charlotte Borcherds, Yisong Yue:
Conformal Generative Modeling on Triangulated Surfaces. CoRR abs/2303.10251 (2023) - [i111]Jeremy Bernstein, Chris Mingard, Kevin Huang, Navid Azizan, Yisong Yue:
Automatic Gradient Descent: Deep Learning without Hyperparameters. CoRR abs/2304.05187 (2023) - [i110]Fengxue Zhang, Jialin Song, James C. Bowden, Alexander Ladd, Yisong Yue, Thomas A. Desautels, Yuxin Chen:
Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation. CoRR abs/2307.13371 (2023) - [i109]Fengze Xie, Guanya Shi, Michael O'Connell, Yisong Yue, Soon-Jo Chung:
Hierarchical Meta-learning-based Adaptive Controller. CoRR abs/2311.12367 (2023) - [i108]Fengze Xie, Marcus Dominguez-Kuhne, Benjamin Rivière, Jialin Song, Wolfgang Hönig, Soon-Jo Chung, Yisong Yue:
Joint-Space Multi-Robot Motion Planning with Learned Decentralized Heuristics. CoRR abs/2311.12385 (2023) - 2022
- [j18]Andrew J. Taylor, Victor D. Dorobantu, Yisong Yue, Paulo Tabuada, Aaron D. Ames:
Sampled-Data Stabilization With Control Lyapunov Functions via Quadratically Constrained Quadratic Programs. IEEE Control. Syst. Lett. 6: 680-685 (2022) - [j17]Kejun Li, Maegan Tucker, Rachel Gehlhar, Yisong Yue, Aaron D. Ames:
Natural Multicontact Walking for Robotic Assistive Devices via Musculoskeletal Models and Hybrid Zero Dynamics. IEEE Robotics Autom. Lett. 7(2): 4283-4290 (2022) - [j16]Shreyansh Daftry, Neil Abcouwer, Tyler del Sesto, Siddarth Venkatraman, Jialin Song, Lucas Igel, Amos Byon, Ugo Rosolia, Yisong Yue, Masahiro Ono:
MLNav: Learning to Safely Navigate on Martian Terrains. IEEE Robotics Autom. Lett. 7(2): 5461-5468 (2022) - [j15]Michael O'Connell, Guanya Shi, Xichen Shi, Kamyar Azizzadenesheli, Anima Anandkumar, Yisong Yue, Soon-Jo Chung:
Neural-Fly enables rapid learning for agile flight in strong winds. Sci. Robotics 7(66) (2022) - [j14]Eric Zhan, Jennifer J. Sun, Ann Kennedy, Yisong Yue, Swarat Chaudhuri:
Unsupervised Learning of Neurosymbolic Encoders. Trans. Mach. Learn. Res. 2022 (2022) - [j13]Guanya Shi, Wolfgang Hönig, Xichen Shi, Yisong Yue, Soon-Jo Chung:
Neural-Swarm2: Planning and Control of Heterogeneous Multirotor Swarms Using Learned Interactions. IEEE Trans. Robotics 38(2): 1063-1079 (2022) - [c101]Chenkai Yu, Guanya Shi, Soon-Jo Chung, Yisong Yue, Adam Wierman:
Competitive Control with Delayed Imperfect Information. ACC 2022: 2604-2610 - [c100]Ryan K. Cosner, Yisong Yue, Aaron D. Ames:
End-to-End Imitation Learning with Safety Guarantees using Control Barrier Functions. CDC 2022: 5316-5322 - [c99]Andrew J. Taylor, Victor D. Dorobantu, Ryan K. Cosner, Yisong Yue, Aaron D. Ames:
Safety of Sampled-Data Systems with Control Barrier Functions via Approximate Discrete Time Models. CDC 2022: 7127-7134 - [c98]Aaron M. Ferber, Jialin Song, Bistra Dilkina, Yisong Yue:
Learning Pseudo-Backdoors for Mixed Integer Programs. CPAIOR 2022: 91-102 - [c97]Jennifer J. Sun, Serim Ryou, Roni H. Goldshmid, Brandon Weissbourd, John O. Dabiri, David J. Anderson, Ann Kennedy, Yisong Yue, Pietro Perona:
Self-Supervised Keypoint Discovery in Behavioral Videos. CVPR 2022: 2161-2170 - [c96]Albert Tseng, Jennifer J. Sun, Yisong Yue:
Automatic Synthesis of Diverse Weak Supervision Sources for Behavior Analysis. CVPR 2022: 2201-2210 - [c95]Alexander R. Farhang, Jeremy D. Bernstein, Kushal Tirumala, Yang Liu, Yisong Yue:
Investigating Generalization by Controlling Normalized Margin. ICML 2022: 6324-6336 - [c94]Ivan Dario Jimenez Rodriguez, Aaron D. Ames, Yisong Yue:
LyaNet: A Lyapunov Framework for Training Neural ODEs. ICML 2022: 18687-18703 - [c93]Ryan K. Cosner, Ivan D. Jimenez Rodriguez, Tamás G. Molnár, Wyatt Ubellacker, Yisong Yue, Aaron D. Ames, Katherine L. Bouman:
Self-Supervised Online Learning for Safety-Critical Control using Stereo Vision. ICRA 2022: 11487-11493 - [c92]Ryan K. Cosner, Maegan Tucker, Andrew J. Taylor, Kejun Li, Tamás G. Molnár, Wyatt Ubellacker, Anil Alan, Gábor Orosz, Yisong Yue, Aaron D. Ames:
Safety-Aware Preference-Based Learning for Safety-Critical Control. L4DC 2022: 1020-1033 - [c91]Ivan Dario Jimenez Rodriguez, Noel Csomay-Shanklin, Yisong Yue, Aaron D. Ames:
Neural Gaits: Learning Bipedal Locomotion via Control Barrier Functions and Zero Dynamics Policies. L4DC 2022: 1060-1072 - [c90]Cameron Voloshin, Hoang Minh Le, Swarat Chaudhuri, Yisong Yue:
Policy Optimization with Linear Temporal Logic Constraints. NeurIPS 2022 - [i107]Ivan Dario Jimenez Rodriguez, Aaron D. Ames, Yisong Yue:
LyaNet: A Lyapunov Framework for Training Neural ODEs. CoRR abs/2202.02526 (2022) - [i106]Ryan K. Cosner, Ivan D. Jimenez Rodriguez, Tamás G. Molnár, Wyatt Ubellacker, Yisong Yue, Aaron D. Ames, Katherine L. Bouman:
Self-Supervised Online Learning for Safety-Critical Control using Stereo Vision. CoRR abs/2203.01404 (2022) - [i105]Shreyansh Daftry, Neil Abcouwer, Tyler del Sesto, Siddarth Venkatraman, Jialin Song, Lucas Igel, Amos Byon, Ugo Rosolia, Yisong Yue, Masahiro Ono:
MLNav: Learning to Safely Navigate on Martian Terrains. CoRR abs/2203.04563 (2022) - [i104]Andrew J. Taylor, Victor D. Dorobantu, Ryan K. Cosner, Yisong Yue, Aaron D. Ames:
Safety of Sampled-Data Systems with Control Barrier Functions via Approximate Discrete Time Models. CoRR abs/2203.11470 (2022) - [i103]Ivan Dario Jimenez Rodriguez, Noel Csomay-Shanklin, Yisong Yue, Aaron D. Ames:
Neural Gaits: Learning Bipedal Locomotion via Control Barrier Functions and Zero Dynamics Policies. CoRR abs/2204.08120 (2022) - [i102]Alexander R. Farhang, Jeremy Bernstein, Kushal Tirumala, Yang Liu, Yisong Yue:
Investigating Generalization by Controlling Normalized Margin. CoRR abs/2205.03940 (2022) - [i101]Michael O'Connell, Guanya Shi, Xichen Shi, Kamyar Azizzadenesheli, Anima Anandkumar, Yisong Yue, Soon-Jo Chung:
Neural-Fly Enables Rapid Learning for Agile Flight in Strong Winds. CoRR abs/2205.06908 (2022) - [i100]Sabera Talukder, Jennifer J. Sun, Matthew Leonard, Bingni W. Brunton, Yisong Yue:
Deep Neural Imputation: A Framework for Recovering Incomplete Brain Recordings. CoRR abs/2206.08094 (2022) - [i99]Cameron Voloshin, Hoang Minh Le, Swarat Chaudhuri, Yisong Yue:
Policy Optimization with Linear Temporal Logic Constraints. CoRR abs/2206.09546 (2022) - [i98]Victor D. Dorobantu, Kamyar Azizzadenesheli, Yisong Yue:
Compactly Restrictable Metric Policy Optimization Problems. CoRR abs/2207.05850 (2022) - [i97]Jennifer J. Sun, Andrew Ulmer, Dipam Chakraborty, Brian Geuther, Edward Hayes, Heng Jia, Vivek Kumar, Zachary Partridge, Alice Robie, Catherine E. Schretter, Chao Sun, Keith Sheppard, Param Uttarwar, Pietro Perona, Yisong Yue, Kristin Branson, Ann Kennedy:
The MABe22 Benchmarks for Representation Learning of Multi-Agent Behavior. CoRR abs/2207.10553 (2022) - [i96]Maegan Tucker, Kejun Li, Yisong Yue, Aaron D. Ames:
POLAR: Preference Optimization and Learning Algorithms for Robotics. CoRR abs/2208.04404 (2022) - [i95]Jennifer J. Sun, Megan Tjandrasuwita, Atharva Sehgal, Armando Solar-Lezama, Swarat Chaudhuri, Yisong Yue, Omar Costilla-Reyes:
Neurosymbolic Programming for Science. CoRR abs/2210.05050 (2022) - [i94]Yujia Huang, Ivan Dario Jimenez Rodriguez, Huan Zhang, Yuanyuan Shi, Yisong Yue:
FI-ODE: Certified and Robust Forward Invariance in Neural ODEs. CoRR abs/2210.16940 (2022) - [i93]Jennifer J. Sun, Pierre Karashchuk, Amil Dravid, Serim Ryou, Sonia Fereidooni, John C. Tuthill, Aggelos K. Katsaggelos, Bingni W. Brunton, Georgia Gkioxari, Ann Kennedy, Yisong Yue, Pietro Perona:
BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos. CoRR abs/2212.07401 (2022) - [i92]Ryan K. Cosner, Yisong Yue, Aaron D. Ames:
End-to-End Imitation Learning with Safety Guarantees using Control Barrier Functions. CoRR abs/2212.11365 (2022) - 2021
- [j12]Andrew J. Taylor, Andrew Singletary, Yisong Yue, Aaron D. Ames:
A Control Barrier Perspective on Episodic Learning via Projection-to-State Safety. IEEE Control. Syst. Lett. 5(3): 1019-1024 (2021) - [j11]Swarat Chaudhuri, Kevin Ellis, Oleksandr Polozov, Rishabh Singh, Armando Solar-Lezama, Yisong Yue:
Neurosymbolic Programming. Found. Trends Program. Lang. 7(3): 158-243 (2021) - [j10]Michael R. Maser, Alexander Y. Cui, Serim Ryou, Travis J. DeLano, Yisong Yue, Sarah E. Reisman:
Multilabel Classification Models for the Prediction of Cross-Coupling Reaction Conditions. J. Chem. Inf. Model. 61(1): 156-166 (2021) - [j9]Yashwanth Kumar Nakka, Anqi Liu, Guanya Shi, Anima Anandkumar, Yisong Yue, Soon-Jo Chung:
Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems. IEEE Robotics Autom. Lett. 6(1): 389-396 (2021) - [j8]Yidan Qin, Max Allan, Yisong Yue, Joel W. Burdick, Mahdi Azizian:
Learning Invariant Representation of Tasks for Robust Surgical State Estimation. IEEE Robotics Autom. Lett. 6(2): 3208-3215 (2021) - [c89]Ravi Tej Akella, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Animashree Anandkumar, Yisong Yue:
Deep Bayesian Quadrature Policy Optimization. AAAI 2021: 6600-6608 - [c88]Cameron Voloshin, Nan Jiang, Yisong Yue:
Minimax Model Learning. AISTATS 2021: 1612-1620 - [c87]Eric Zhao, Anqi Liu, Animashree Anandkumar, Yisong Yue:
Active Learning under Label Shift. AISTATS 2021: 3412-3420 - [c86]Dimitar Ho, Hoang Minh Le, John Doyle, Yisong Yue:
Online Robust Control of Nonlinear Systems with Large Uncertainty. AISTATS 2021: 3475-3483 - [c85]Andrew J. Taylor, Victor D. Dorobantu, Sarah Dean, Benjamin Recht, Yisong Yue, Aaron D. Ames:
Towards Robust Data-Driven Control Synthesis for Nonlinear Systems with Actuation Uncertainty. CDC 2021: 6469-6476 - [c84]Jennifer J. Sun, Ann Kennedy, Eric Zhan, David J. Anderson, Yisong Yue, Pietro Perona:
Task Programming: Learning Data Efficient Behavior Representations. CVPR 2021: 2876-2885 - [c83]Ayya Alieva, Aiden Aceves, Jialin Song, Stephen Mayo, Yisong Yue, Yuxin Chen:
Learning to Make Decisions via Submodular Regularization. ICLR 2021 - [c82]Yang Liu, Jeremy Bernstein, Markus Meister, Yisong Yue:
Learning by Turning: Neural Architecture Aware Optimisation. ICML 2021: 6748-6758 - [c81]Kejun Li, Maegan Tucker, Erdem Biyik, Ellen R. Novoseller, Joel W. Burdick, Yanan Sui, Dorsa Sadigh, Yisong Yue, Aaron D. Ames:
ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes. ICRA 2021: 3212-3218 - [c80]Ivan D. Jimenez Rodriguez, Ugo Rosolia, Aaron D. Ames, Yisong Yue:
Learning to Control an Unstable System with One Minute of Data: Leveraging Gaussian Process Differentiation in Predictive Control. IROS 2021: 3896-3903 - [c79]Dawna Bagherian, James Gornet, Jeremy Bernstein, Yu-Li Ni, Yisong Yue, Markus Meister:
Fine-Grained System Identification of Nonlinear Neural Circuits. KDD 2021: 14-24 - [c78]Tianwei Yin, Zihui Wu, He Sun, Adrian V. Dalca, Yisong Yue, Katherine L. Bouman:
End-to-End Sequential Sampling and Reconstruction for MRI. ML4H@NeurIPS 2021: 261-281 - [c77]Guanya Shi, Kamyar Azizzadenesheli, Michael O'Connell, Soon-Jo Chung, Yisong Yue:
Meta-Adaptive Nonlinear Control: Theory and Algorithms. NeurIPS 2021: 10013-10025 - [c76]Angela F. Gao, Jorge C. Castellanos, Yisong Yue, Zachary E. Ross, Katherine L. Bouman:
DeepGEM: Generalized Expectation-Maximization for Blind Inversion. NeurIPS 2021: 11592-11603 - [c75]Joseph Marino, Alexandre Piché, Alessandro Davide Ialongo, Yisong Yue:
Iterative Amortized Policy Optimization. NeurIPS 2021: 15667-15681 - [c74]Jennifer J. Sun, Tomomi Karigo, Dipam Chakraborty, Sharada P. Mohanty, Benjamin Wild, Quan Sun, Chen Chen, David J. Anderson, Pietro Perona, Yisong Yue, Ann Kennedy:
The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions. NeurIPS Datasets and Benchmarks 2021 - [c73]Cameron Voloshin, Hoang Minh Le, Nan Jiang, Yisong Yue:
Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning. NeurIPS Datasets and Benchmarks 2021 - [c72]Aaron M. Ferber, Jialin Song, Bistra Dilkina, Yisong Yue:
Learning Pseudo-Backdoors for Mixed Integer Programs. SOCS 2021: 170-172 - [c71]Manish Prajapat, Kamyar Azizzadenesheli, Alexander Liniger, Yisong Yue, Anima Anandkumar:
Competitive policy optimization. UAI 2021: 64-74 - [i91]Anqi Liu, Hao Liu, Tongxin Li, Saeed Karimi-Bidhendi, Yisong Yue, Anima Anandkumar:
Disentangling Observed Causal Effects from Latent Confounders using Method of Moments. CoRR abs/2101.06614 (2021) - [i90]Yang Liu, Jeremy Bernstein, Markus Meister, Yisong Yue:
Learning by Turning: Neural Architecture Aware Optimisation. CoRR abs/2102.07227 (2021) - [i89]Yidan Qin, Max Allan, Yisong Yue, Joel W. Burdick, Mahdi Azizian:
Learning Invariant Representation of Tasks for Robust Surgical State Estimation. CoRR abs/2102.09119 (2021) - [i88]Jeremy Bernstein, Yisong Yue:
Computing the Information Content of Trained Neural Networks. CoRR abs/2103.01045 (2021) - [i87]Cameron Voloshin, Nan Jiang, Yisong Yue:
Minimax Model Learning. CoRR abs/2103.02084 (2021) - [i86]Andrew J. Taylor, Victor D. Dorobantu, Yisong Yue, Paulo Tabuada, Aaron D. Ames:
Sampled-Data Stabilization with Control Lyapunov Functions via Quadratically Constrained Quadratic Programs. CoRR abs/2103.03937 (2021) - [i85]Ivan D. Jimenez Rodriguez, Ugo Rosolia, Aaron D. Ames, Yisong Yue:
Learning Unstable Dynamics with One Minute of Data: A Differentiation-based Gaussian Process Approach. CoRR abs/2103.04548 (2021) - [i84]Dimitar Ho, Hoang M. Le, John C. Doyle, Yisong Yue:
Online Robust Control of Nonlinear Systems with Large Uncertainty. CoRR abs/2103.11055 (2021) - [i83]Jennifer J. Sun, Tomomi Karigo, Dipam Chakraborty, Sharada P. Mohanty, David J. Anderson, Pietro Perona, Yisong Yue, Ann Kennedy:
The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions. CoRR abs/2104.02710 (2021) - [i82]Tianwei Yin, Zihui Wu, He Sun, Adrian V. Dalca, Yisong Yue, Katherine L. Bouman:
End-to-End Sequential Sampling and Reconstruction for MR Imaging. CoRR abs/2105.06460 (2021) - [i81]Aaron M. Ferber, Jialin Song, Bistra Dilkina, Yisong Yue:
Learning Pseudo-Backdoors for Mixed Integer Programs. CoRR abs/2106.05080 (2021) - [i80]Dawna Bagherian, James Gornet, Jeremy Bernstein, Yu-Li Ni, Yisong Yue, Markus Meister:
Fine-Grained System Identification of Nonlinear Neural Circuits. CoRR abs/2106.05400 (2021) - [i79]Guanya Shi, Kamyar Azizzadenesheli, Soon-Jo Chung, Yisong Yue:
Meta-Adaptive Nonlinear Control: Theory and Algorithms. CoRR abs/2106.06098 (2021) - [i78]Megan Tjandrasuwita, Jennifer J. Sun, Ann Kennedy, Swarat Chaudhuri, Yisong Yue:
Interpreting Expert Annotation Differences in Animal Behavior. CoRR abs/2106.06114 (2021) - [i77]Eric Zhan, Jennifer J. Sun, Ann Kennedy, Yisong Yue, Swarat Chaudhuri:
Unsupervised Learning of Neurosymbolic Encoders. CoRR abs/2107.13132 (2021) - [i76]Kejun Li, Maegan Tucker, Rachel Gehlhar, Yisong Yue, Aaron D. Ames:
Natural Multicontact Walking for Robotic Assistive Devices via Musculoskeletal Models and Hybrid Zero Dynamics. CoRR abs/2109.05113 (2021) - [i75]Jeremy Bernstein, Yisong Yue:
On the Implicit Biases of Architecture & Gradient Descent. CoRR abs/2110.04274 (2021) - [i74]Albert Tseng, Jennifer J. Sun, Yisong Yue:
Automatic Synthesis of Diverse Weak Supervision Sources for Behavior Analysis. CoRR abs/2111.15186 (2021) - [i73]Jennifer J. Sun, Serim Ryou, Roni Goldshmid, Brandon Weissbourd, John O. Dabiri, David J. Anderson, Ann Kennedy, Yisong Yue, Pietro Perona:
Self-Supervised Keypoint Discovery in Behavioral Videos. CoRR abs/2112.05121 (2021) - [i72]Ryan K. Cosner, Maegan Tucker, Andrew J. Taylor, Kejun Li, Tamás G. Molnár, Wyatt Ubellacker, Anil Alan, Gábor Orosz, Yisong Yue, Aaron D. Ames:
Safety-Aware Preference-Based Learning for Safety-Critical Control. CoRR abs/2112.08516 (2021) - 2020
- [j7]Benjamin Rivière, Wolfgang Hönig, Yisong Yue, Soon-Jo Chung:
GLAS: Global-to-Local Safe Autonomy Synthesis for Multi-Robot Motion Planning With End-to-End Learning. IEEE Robotics Autom. Lett. 5(3): 4249-4256 (2020) - [c70]Jung Yeon Park, Kenneth Theo Carr, Stephan Zheng, Yisong Yue, Rose Yu:
Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis. ICML 2020: 7499-7509 - [c69]Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew J. Hausknecht:
Learning Calibratable Policies using Programmatic Style-Consistency. ICML 2020: 11001-11011 - [c68]Maegan Tucker, Ellen R. Novoseller, Claudia Kann, Yanan Sui, Yisong Yue, Joel W. Burdick, Aaron D. Ames:
Preference-Based Learning for Exoskeleton Gait Optimization. ICRA 2020: 2351-2357 - [c67]Guanya Shi, Wolfgang Hönig, Yisong Yue, Soon-Jo Chung:
Neural-Swarm: Decentralized Close-Proximity Multirotor Control Using Learned Interactions. ICRA 2020: 3241-3247 - [c66]Maegan Tucker, Myra Cheng, Ellen R. Novoseller, Richard Cheng, Yisong Yue, Joel W. Burdick, Aaron D. Ames:
Human Preference-Based Learning for High-dimensional Optimization of Exoskeleton Walking Gaits. IROS 2020: 3423-3430 - [c65]Anqi Liu, Guanya Shi, Soon-Jo Chung, Anima Anandkumar, Yisong Yue:
Robust Regression for Safe Exploration in Control. L4DC 2020: 608-619 - [c64]Andrew J. Taylor, Andrew Singletary, Yisong Yue, Aaron D. Ames:
Learning for Safety-Critical Control with Control Barrier Functions. L4DC 2020: 708-717 - [c63]Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu:
On the distance between two neural networks and the stability of learning. NeurIPS 2020 - [c62]Jeremy Bernstein, Jiawei Zhao, Markus Meister, Ming-Yu Liu, Anima Anandkumar, Yisong Yue:
Learning compositional functions via multiplicative weight updates. NeurIPS 2020 - [c61]Ameesh Shah, Eric Zhan, Jennifer J. Sun, Abhinav Verma, Yisong Yue, Swarat Chaudhuri:
Learning Differentiable Programs with Admissible Neural Heuristics. NeurIPS 2020 - [c60]Guanya Shi, Yiheng Lin, Soon-Jo Chung, Yisong Yue, Adam Wierman:
Online Optimization with Memory and Competitive Control. NeurIPS 2020 - [c59]Jialin Song, Ravi Lanka, Yisong Yue, Bistra Dilkina:
A General Large Neighborhood Search Framework for Solving Integer Linear Programs. NeurIPS 2020 - [c58]Chenkai Yu, Guanya Shi, Soon-Jo Chung, Yisong Yue, Adam Wierman:
The Power of Predictions in Online Control. NeurIPS 2020 - [c57]Ellen R. Novoseller, Yibing Wei, Yanan Sui, Yisong Yue, Joel Burdick:
Dueling Posterior Sampling for Preference-Based Reinforcement Learning. UAI 2020: 1029-1038 - [i71]Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu:
On the distance between two neural networks and the stability of learning. CoRR abs/2002.03432 (2020) - [i70]Guanya Shi, Yiheng Lin, Soon-Jo Chung, Yisong Yue, Adam Wierman:
Beyond No-Regret: Competitive Control via Online Optimization with Memory. CoRR abs/2002.05318 (2020) - [i69]Jung Yeon Park, Kenneth Theo Carr, Stephan Zheng, Yisong Yue, Rose Yu:
Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis. CoRR abs/2002.05578 (2020) - [i68]Benjamin Rivière, Wolfgang Hönig, Yisong Yue, Soon-Jo Chung:
GLAS: Global-to-Local Safe Autonomy Synthesis for Multi-Robot Motion Planning with End-to-End Learning. CoRR abs/2002.11807 (2020) - [i67]Guanya Shi, Wolfgang Hönig, Yisong Yue, Soon-Jo Chung:
Neural-Swarm: Decentralized Close-Proximity Multirotor Control Using Learned Interactions. CoRR abs/2003.02992 (2020) - [i66]Maegan Tucker, Myra Cheng, Ellen R. Novoseller, Richard Cheng, Yisong Yue, Joel W. Burdick, Aaron D. Ames:
Human Preference-Based Learning for High-dimensional Optimization of Exoskeleton Walking Gaits. CoRR abs/2003.06495 (2020) - [i65]Andrew J. Taylor, Andrew Singletary, Yisong Yue, Aaron D. Ames:
A Control Barrier Perspective on Episodic Learning via Projection-to-State Safety. CoRR abs/2003.08028 (2020) - [i64]Jialin Song, Ravi Lanka, Yisong Yue, Bistra Dilkina:
A General Large Neighborhood Search Framework for Solving Integer Programs. CoRR abs/2004.00422 (2020) - [i63]Yashwanth Kumar Nakka, Anqi Liu, Guanya Shi, Anima Anandkumar, Yisong Yue, Soon-Jo Chung:
Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems. CoRR abs/2005.04374 (2020) - [i62]Chenkai Yu, Guanya Shi, Soon-Jo Chung, Yisong Yue, Adam Wierman:
The Power of Predictions in Online Control. CoRR abs/2006.07569 (2020) - [i61]Manish Prajapat, Kamyar Azizzadenesheli, Alexander Liniger, Yisong Yue, Anima Anandkumar:
Competitive Policy Optimization. CoRR abs/2006.10611 (2020) - [i60]Jeremy Bernstein, Jiawei Zhao, Markus Meister, Ming-Yu Liu, Anima Anandkumar, Yisong Yue:
Learning compositional functions via multiplicative weight updates. CoRR abs/2006.14560 (2020) - [i59]Akash Kumar, Adish Singla, Yisong Yue, Yuxin Chen:
Average-case Complexity of Teaching Convex Polytopes via Halfspace Queries. CoRR abs/2006.14677 (2020) - [i58]Ravi Tej Akella, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Anima Anandkumar, Yisong Yue:
Deep Bayesian Quadrature Policy Optimization. CoRR abs/2006.15637 (2020) - [i57]Serim Ryou, Michael R. Maser, Alexander Y. Cui, Travis J. DeLano, Yisong Yue, Sarah E. Reisman:
Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions. CoRR abs/2007.04275 (2020) - [i56]Eric Zhao, Anqi Liu, Animashree Anandkumar, Yisong Yue:
Active Learning under Label Shift. CoRR abs/2007.08479 (2020) - [i55]Ameesh Shah, Eric Zhan, Jennifer J. Sun, Abhinav Verma, Yisong Yue, Swarat Chaudhuri:
Learning Differentiable Programs with Admissible Neural Heuristics. CoRR abs/2007.12101 (2020) - [i54]Haoxuan Wang, Anqi Liu, Zhiding Yu, Yisong Yue, Anima Anandkumar:
Distributionally Robust Learning for Unsupervised Domain Adaptation. CoRR abs/2010.05784 (2020) - [i53]Joseph Marino, Alexandre Piché, Alessandro Davide Ialongo, Yisong Yue:
Iterative Amortized Policy Optimization. CoRR abs/2010.10670 (2020) - [i52]Chenkai Yu, Guanya Shi, Soon-Jo Chung, Yisong Yue, Adam Wierman:
Competitive Control with Delayed Imperfect Information. CoRR abs/2010.11637 (2020) - [i51]Sabera Talukder, Guruprasad Raghavan, Yisong Yue:
Architecture Agnostic Neural Networks. CoRR abs/2011.02712 (2020) - [i50]Kejun Li, Maegan Tucker, Erdem Biyik, Ellen R. Novoseller, Joel W. Burdick, Yanan Sui, Dorsa Sadigh, Yisong Yue, Aaron D. Ames:
ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes. CoRR abs/2011.04812 (2020) - [i49]Neil Abcouwer, Shreyansh Daftry, Siddarth Venkatraman, Tyler del Sesto, Olivier Toupet, Ravi Lanka, Jialin Song, Yisong Yue, Masahiro Ono:
Machine Learning Based Path Planning for Improved Rover Navigation (Pre-Print Version). CoRR abs/2011.06022 (2020) - [i48]George Barnum, Sabera Talukder, Yisong Yue:
On the Benefits of Early Fusion in Multimodal Representation Learning. CoRR abs/2011.07191 (2020) - [i47]Andrew J. Taylor, Victor D. Dorobantu, Sarah Dean, Benjamin Recht, Yisong Yue, Aaron D. Ames:
Towards Robust Data-Driven Control Synthesis for Nonlinear Systems with Actuation Uncertainty. CoRR abs/2011.10730 (2020) - [i46]Jennifer J. Sun, Ann Kennedy, Eric Zhan, Yisong Yue, Pietro Perona:
Task Programming: Learning Data Efficient Behavior Representations. CoRR abs/2011.13917 (2020) - [i45]Guanya Shi, Wolfgang Hönig, Xichen Shi, Yisong Yue, Soon-Jo Chung:
Neural-Swarm2: Planning and Control of Heterogeneous Multirotor Swarms using Learned Interactions. CoRR abs/2012.05457 (2020)
2010 – 2019
- 2019
- [c56]Jialin Song, Yuxin Chen, Yisong Yue:
A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes. AISTATS 2019: 3158-3167 - [c55]Kevin K. Yang, Yuxin Chen, Alycia Lee, Yisong Yue:
Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design. AISTATS 2019: 3410-3419 - [c54]Mohamadreza Ahmadi, Bo Wu, Yuxin Chen, Yisong Yue, Ufuk Topcu:
Barrier Certificates for Assured Machine Teaching. ACC 2019: 3658-3663 - [c53]Andrew J. Taylor, Victor D. Dorobantu, Meera Krishnamoorthy, Hoang Minh Le, Yisong Yue, Aaron D. Ames:
A Control Lyapunov Perspective on Episodic Learning via Projection to State Stability. CDC 2019: 1448-1455 - [c52]Eric Zhan, Stephan Zheng, Yisong Yue, Long Sha, Patrick Lucey:
Generating Multi-Agent Trajectories using Programmatic Weak Supervision. ICLR (Poster) 2019 - [c51]Richard Cheng, Abhinav Verma, Gábor Orosz, Swarat Chaudhuri, Yisong Yue, Joel Burdick:
Control Regularization for Reduced Variance Reinforcement Learning. ICML 2019: 1141-1150 - [c50]Hoang Minh Le, Cameron Voloshin, Yisong Yue:
Batch Policy Learning under Constraints. ICML 2019: 3703-3712 - [c49]Yingshui Tan, Baihong Jin, Alexander J. Nettekoven, Yuxin Chen, Yisong Yue, Ufuk Topcu, Alberto L. Sangiovanni-Vincentelli:
An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing. ICMLA 2019: 1008-1015 - [c48]Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, Soon-Jo Chung:
Neural Lander: Stable Drone Landing Control Using Learned Dynamics. ICRA 2019: 9784-9790 - [c47]Andrew J. Taylor, Victor D. Dorobantu, Hoang Minh Le, Yisong Yue, Aaron D. Ames:
Episodic Learning with Control Lyapunov Functions for Uncertain Robotic Systems*. IROS 2019: 6878-6884 - [c46]Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla:
Teaching Multiple Concepts to a Forgetful Learner. NeurIPS 2019: 4050-4060 - [c45]Yukai Liu, Rose Yu, Stephan Zheng, Eric Zhan, Yisong Yue:
NAOMI: Non-Autoregressive Multiresolution Sequence Imputation. NeurIPS 2019: 11236-11246 - [c44]Nikhil Ghosh, Yuxin Chen, Yisong Yue:
Landmark Ordinal Embedding. NeurIPS 2019: 11502-11511 - [c43]Abhinav Verma, Hoang Minh Le, Yisong Yue, Swarat Chaudhuri:
Imitation-Projected Programmatic Reinforcement Learning. NeurIPS 2019: 15726-15737 - [c42]Jialin Song, Ravi Lanka, Yisong Yue, Masahiro Ono:
Co-training for Policy Learning. UAI 2019: 1191-1201 - [i44]Yukai Liu, Rose Yu, Stephan Zheng, Eric Zhan, Yisong Yue:
NAOMI: Non-Autoregressive Multiresolution Sequence Imputation. CoRR abs/1901.10946 (2019) - [i43]Andrew J. Taylor, Victor D. Dorobantu, Hoang Minh Le, Yisong Yue, Aaron D. Ames:
Episodic Learning with Control Lyapunov Functions for Uncertain Robotic Systems. CoRR abs/1903.01577 (2019) - [i42]Andrew J. Taylor, Victor D. Dorobantu, Meera Krishnamoorthy, Hoang Minh Le, Yisong Yue, Aaron D. Ames:
A Control Lyapunov Perspective on Episodic Learning via Projection to State Stability. CoRR abs/1903.07214 (2019) - [i41]Hoang Minh Le, Cameron Voloshin, Yisong Yue:
Batch Policy Learning under Constraints. CoRR abs/1903.08738 (2019) - [i40]Kevin K. Yang, Yuxin Chen, Alycia Lee, Yisong Yue:
Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design. CoRR abs/1904.08102 (2019) - [i39]Richard Cheng, Abhinav Verma, Gábor Orosz, Swarat Chaudhuri, Yisong Yue, Joel W. Burdick:
Control Regularization for Reduced Variance Reinforcement Learning. CoRR abs/1905.05380 (2019) - [i38]Anqi Liu, Guanya Shi, Soon-Jo Chung, Anima Anandkumar, Yisong Yue:
Robust Regression for Safe Exploration in Control. CoRR abs/1906.05819 (2019) - [i37]Jialin Song, Ravi Lanka, Yisong Yue, Masahiro Ono:
Co-training for Policy Learning. CoRR abs/1907.04484 (2019) - [i36]Abhinav Verma, Hoang Minh Le, Yisong Yue, Swarat Chaudhuri:
Imitation-Projected Policy Gradient for Programmatic Reinforcement Learning. CoRR abs/1907.05431 (2019) - [i35]Baihong Jin, Yingshui Tan, Alexander J. Nettekoven, Yuxin Chen, Ufuk Topcu, Yisong Yue, Alberto L. Sangiovanni-Vincentelli:
An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing. CoRR abs/1907.11778 (2019) - [i34]Ellen R. Novoseller, Yanan Sui, Yisong Yue, Joel W. Burdick:
Dueling Posterior Sampling for Preference-Based Reinforcement Learning. CoRR abs/1908.01289 (2019) - [i33]Maegan Tucker, Ellen R. Novoseller, Claudia Kann, Yanan Sui, Yisong Yue, Joel Burdick, Aaron D. Ames:
Preference-Based Learning for Exoskeleton Gait Optimization. CoRR abs/1909.12316 (2019) - [i32]Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew J. Hausknecht:
Learning Calibratable Policies using Programmatic Style-Consistency. CoRR abs/1910.01179 (2019) - [i31]Nikhil Ghosh, Yuxin Chen, Yisong Yue:
Landmark Ordinal Embedding. CoRR abs/1910.12379 (2019) - [i30]Anqi Liu, Hao Liu, Anima Anandkumar, Yisong Yue:
Triply Robust Off-Policy Evaluation. CoRR abs/1911.05811 (2019) - [i29]Cameron Voloshin, Hoang Minh Le, Nan Jiang, Yisong Yue:
Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning. CoRR abs/1911.06854 (2019) - [i28]Andrew J. Taylor, Andrew Singletary, Yisong Yue, Aaron D. Ames:
Learning for Safety-Critical Control with Control Barrier Functions. CoRR abs/1912.10099 (2019) - 2018
- [j6]Long Sha, Patrick Lucey, Yisong Yue, Xinyu Wei, Jennifer A. Hobbs, Charlie Rohlf, Sridha Sridharan:
Interactive Sports Analytics: An Intelligent Interface for Utilizing Trajectories for Interactive Sports Play Retrieval and Analytics. ACM Trans. Comput. Hum. Interact. 25(2): 13:1-13:32 (2018) - [c41]Akifumi Wachi, Yanan Sui, Yisong Yue, Masahiro Ono:
Safe Exploration and Optimization of Constrained MDPs Using Gaussian Processes. AAAI 2018: 6548-6556 - [c40]Yuxin Chen, Oisin Mac Aodha, Shihan Su, Pietro Perona, Yisong Yue:
Near-Optimal Machine Teaching via Explanatory Teaching Sets. AISTATS 2018: 1970-1978 - [c39]Oisin Mac Aodha, Shihan Su, Yuxin Chen, Pietro Perona, Yisong Yue:
Teaching Categories to Human Learners With Visual Explanations. CVPR 2018: 3820-3828 - [c38]Joseph Marino, Yisong Yue, Stephan Mandt:
Learning to Infer. ICLR (Workshop) 2018 - [c37]Hoang Minh Le, Nan Jiang, Alekh Agarwal, Miroslav Dudík, Yisong Yue, Hal Daumé III:
Hierarchical Imitation and Reinforcement Learning. ICML 2018: 2923-2932 - [c36]Joseph Marino, Yisong Yue, Stephan Mandt:
Iterative Amortized Inference. ICML 2018: 3400-3409 - [c35]Yanan Sui, Vincent Zhuang, Joel W. Burdick, Yisong Yue:
Stagewise Safe Bayesian Optimization with Gaussian Processes. ICML 2018: 4788-4796 - [c34]Yanan Sui, Masrour Zoghi, Katja Hofmann, Yisong Yue:
Advancements in Dueling Bandits. IJCAI 2018: 5502-5510 - [c33]Yuxin Chen, Adish Singla, Oisin Mac Aodha, Pietro Perona, Yisong Yue:
Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners. NeurIPS 2018: 1483-1493 - [c32]Joseph Marino, Milan Cvitkovic, Yisong Yue:
A General Method for Amortizing Variational Filtering. NeurIPS 2018: 7868-7879 - [i27]Yuxin Chen, Adish Singla, Oisin Mac Aodha, Pietro Perona, Yisong Yue:
Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners. CoRR abs/1802.05190 (2018) - [i26]Stephan Zheng, Rose Yu, Yisong Yue:
Multi-resolution Tensor Learning for Large-Scale Spatial Data. CoRR abs/1802.06825 (2018) - [i25]Oisin Mac Aodha, Shihan Su, Yuxin Chen, Pietro Perona, Yisong Yue:
Teaching Categories to Human Learners with Visual Explanations. CoRR abs/1802.06924 (2018) - [i24]Hoang Minh Le, Nan Jiang, Alekh Agarwal, Miroslav Dudík, Yisong Yue, Hal Daumé III:
Hierarchical Imitation and Reinforcement Learning. CoRR abs/1803.00590 (2018) - [i23]Sumanth Dathathri, Stephan Zheng, Richard M. Murray, Yisong Yue:
Detecting Adversarial Examples via Neural Fingerprinting. CoRR abs/1803.03870 (2018) - [i22]Eric Zhan, Stephan Zheng, Yisong Yue, Long Sha, Patrick Lucey:
Generative Multi-Agent Behavioral Cloning. CoRR abs/1803.07612 (2018) - [i21]Jialin Song, Ravi Lanka, Albert Zhao, Yisong Yue, Masahiro Ono:
Learning to Search via Self-Imitation. CoRR abs/1804.00846 (2018) - [i20]Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez-Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla:
Teaching Multiple Concepts to Forgetful Learners. CoRR abs/1805.08322 (2018) - [i19]Yanan Sui, Vincent Zhuang, Joel W. Burdick, Yisong Yue:
Stagewise Safe Bayesian Optimization with Gaussian Processes. CoRR abs/1806.07555 (2018) - [i18]Joseph Marino, Yisong Yue, Stephan Mandt:
Iterative Amortized Inference. CoRR abs/1807.09356 (2018) - [i17]Zachary E. Ross, Yisong Yue, Men-Andrin Meier, Egill Hauksson, Thomas H. Heaton:
PhaseLink: A Deep Learning Approach to Seismic Phase Association. CoRR abs/1809.02880 (2018) - [i16]Mohamadreza Ahmadi, Bo Wu, Yuxin Chen, Yisong Yue, Ufuk Topcu:
Barrier Certificates for Assured Machine Teaching. CoRR abs/1810.00093 (2018) - [i15]Jialin Song, Yuxin Chen, Yisong Yue:
A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes. CoRR abs/1811.00755 (2018) - [i14]Joseph Marino, Milan Cvitkovic, Yisong Yue:
A General Method for Amortizing Variational Filtering. CoRR abs/1811.05090 (2018) - [i13]Jialin Song, Yury S. Tokpanov, Yuxin Chen, Dagny Fleischman, Kate T. Fountaine, Harry A. Atwater, Yisong Yue:
Optimizing Photonic Nanostructures via Multi-fidelity Gaussian Processes. CoRR abs/1811.07707 (2018) - [i12]Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, Soon-Jo Chung:
Neural Lander: Stable Drone Landing Control using Learned Dynamics. CoRR abs/1811.08027 (2018) - 2017
- [j5]Sarah L. Taylor, Taehwan Kim, Yisong Yue, Moshe Mahler, James Krahe, Anastasio Garcia Rodriguez, Jessica K. Hodgins, Iain A. Matthews:
A deep learning approach for generalized speech animation. ACM Trans. Graph. 36(4): 93:1-93:11 (2017) - [c31]Zhiwei Deng, Rajitha Navarathna, Peter Carr, Stephan Mandt, Yisong Yue, Iain A. Matthews, Greg Mori:
Factorized Variational Autoencoders for Modeling Audience Reactions to Movies. CVPR 2017: 6014-6023 - [c30]Eyrun Eyjolfsdottir, Kristin Branson, Yisong Yue, Pietro Perona:
Learning Recurrent Representations for Hierarchical Behavior Modeling. ICLR (Poster) 2017 - [c29]Hoang Minh Le, Yisong Yue, Peter Carr, Patrick Lucey:
Coordinated Multi-Agent Imitation Learning. ICML 2017: 1995-2003 - [c28]Yanan Sui, Vincent Zhuang, Joel W. Burdick, Yisong Yue:
Multi-dueling Bandits with Dependent Arms. UAI 2017 - [i11]Hoang Minh Le, Yisong Yue, Peter Carr:
Coordinated Multi-Agent Imitation Learning. CoRR abs/1703.03121 (2017) - [i10]Yanan Sui, Vincent Zhuang, Joel W. Burdick, Yisong Yue:
Multi-dueling Bandits with Dependent Arms. CoRR abs/1705.00253 (2017) - [i9]Stephan Zheng, Yisong Yue, Patrick Lucey:
Generating Long-term Trajectories Using Deep Hierarchical Networks. CoRR abs/1706.07138 (2017) - [i8]Yanan Sui, Yisong Yue, Joel W. Burdick:
Correlational Dueling Bandits with Application to Clinical Treatment in Large Decision Spaces. CoRR abs/1707.02375 (2017) - [i7]Long Sha, Patrick Lucey, Stephan Zheng, Taehwan Kim, Yisong Yue, Sridha Sridharan:
Fine-Grained Retrieval of Sports Plays using Tree-Based Alignment of Trajectories. CoRR abs/1710.02255 (2017) - [i6]Rose Yu, Stephan Zheng, Anima Anandkumar, Yisong Yue:
Long-term Forecasting using Tensor-Train RNNs. CoRR abs/1711.00073 (2017) - 2016
- [c27]Kaushik Krishnan, Lavanya Marla, Yisong Yue:
Robust ambulance allocation using risk-based metrics. COMSNETS 2016: 1-6 - [c26]Jianhui Chen, Hoang Minh Le, Peter Carr, Yisong Yue, James J. Little:
Learning Online Smooth Predictors for Realtime Camera Planning Using Recurrent Decision Trees. CVPR 2016: 4688-4696 - [c25]Matteo Ruggero Ronchi, Joon Sik Kim, Yisong Yue:
A Rotation Invariant Latent Factor Model for Moveme Discovery from Static Poses. ICDM 2016: 1179-1184 - [c24]Hoang Minh Le, Andrew Kang, Yisong Yue, Peter Carr:
Smooth Imitation Learning for Online Sequence Prediction. ICML 2016: 680-688 - [c23]Long Sha, Patrick Lucey, Yisong Yue, Peter Carr, Charlie Rohlf, Iain A. Matthews:
Chalkboarding: A New Spatiotemporal Query Paradigm for Sports Play Retrieval. IUI 2016: 336-347 - [c22]Stephan Zheng, Yisong Yue, Jennifer A. Hobbs:
Generating Long-term Trajectories Using Deep Hierarchical Networks. NIPS 2016: 1543-1551 - [i5]Hoang Minh Le, Andrew Kang, Yisong Yue, Peter Carr:
Smooth Imitation Learning for Online Sequence Prediction. CoRR abs/1606.00968 (2016) - [i4]Matteo Ruggero Ronchi, Joon Sik Kim, Yisong Yue:
A Rotation Invariant Latent Factor Model for Moveme Discovery from Static Poses. CoRR abs/1609.07495 (2016) - [i3]Eyrun Eyjolfsdottir, Kristin Branson, Yisong Yue, Pietro Perona:
Learning recurrent representations for hierarchical behavior modeling. CoRR abs/1611.00094 (2016) - 2015
- [j4]Siyuan Liu, Yisong Yue, Ramayya Krishnan:
Non-Myopic Adaptive Route Planning in Uncertain Congestion Environments. IEEE Trans. Knowl. Data Eng. 27(9): 2438-2451 (2015) - [c21]Taehwan Kim, Yisong Yue, Sarah L. Taylor, Iain A. Matthews:
A Decision Tree Framework for Spatiotemporal Sequence Prediction. KDD 2015: 577-586 - [c20]Bryan D. He, Yisong Yue:
Smooth Interactive Submodular Set Cover. NIPS 2015: 118-126 - 2014
- [c19]Alina Bialkowski, Patrick Lucey, Peter Carr, Yisong Yue, Sridha Sridharan, Iain A. Matthews:
Identifying Team Style in Soccer Using Formations Learned from Spatiotemporal Tracking Data. ICDM Workshops 2014: 9-14 - [c18]Yisong Yue, Patrick Lucey, Peter Carr, Alina Bialkowski, Iain A. Matthews:
Learning Fine-Grained Spatial Models for Dynamic Sports Play Prediction. ICDM 2014: 670-679 - [c17]Alina Bialkowski, Patrick Lucey, Peter Carr, Yisong Yue, Sridha Sridharan, Iain A. Matthews:
Large-Scale Analysis of Soccer Matches Using Spatiotemporal Tracking Data. ICDM 2014: 725-730 - [c16]Yisong Yue, Chong Wang, Khalid El-Arini, Carlos Guestrin:
Personalized collaborative clustering. WWW 2014: 75-84 - 2013
- [c15]Stéphane Ross, Jiaji Zhou, Yisong Yue, Debadeepta Dey, Drew Bagnell:
Learning Policies for Contextual Submodular Prediction. ICML (3) 2013: 1364-1372 - [c14]Siyuan Liu, Yisong Yue, Ramayya Krishnan:
Adaptive collective routing using gaussian process dynamic congestion models. KDD 2013: 704-712 - [i2]Stéphane Ross, Jiaji Zhou, Yisong Yue, Debadeepta Dey, J. Andrew Bagnell:
Learning Policies for Contextual Submodular Prediction. CoRR abs/1305.2532 (2013) - [i1]Jiaji Zhou, Stéphane Ross, Yisong Yue, Debadeepta Dey, J. Andrew Bagnell:
Knapsack Constrained Contextual Submodular List Prediction with Application to Multi-document Summarization. CoRR abs/1308.3541 (2013) - 2012
- [j3]Yisong Yue, Josef Broder, Robert Kleinberg, Thorsten Joachims:
The K-armed dueling bandits problem. J. Comput. Syst. Sci. 78(5): 1538-1556 (2012) - [j2]Olivier Chapelle, Thorsten Joachims, Filip Radlinski, Yisong Yue:
Large-scale validation and analysis of interleaved search evaluation. ACM Trans. Inf. Syst. 30(1): 6:1-6:41 (2012) - [c13]Yisong Yue, Lavanya Marla, Ramayya Krishnan:
An Efficient Simulation-Based Approach to Ambulance Fleet Allocation and Dynamic Redeployment. AAAI 2012: 398-405 - [c12]Yisong Yue, Sue Ann Hong, Carlos Guestrin:
Hierarchical Exploration for Accelerating Contextual Bandits. ICML 2012 - 2011
- [b1]Yisong Yue:
New Learning Frameworks for Information Retrieval. Cornell University, USA, 2011 - [c11]Yisong Yue, Thorsten Joachims:
Beat the Mean Bandit. ICML 2011: 241-248 - [c10]Yisong Yue, Carlos Guestrin:
Linear Submodular Bandits and their Application to Diversified Retrieval. NIPS 2011: 2483-2491 - [c9]Filip Radlinski, Yisong Yue:
Practical online retrieval evaluation. SIGIR 2011: 1301-1302 - [c8]Christina Brandt, Thorsten Joachims, Yisong Yue, Jacob Bank:
Dynamic ranked retrieval. WSDM 2011: 247-256 - 2010
- [c7]Ainur Yessenalina, Yisong Yue, Claire Cardie:
Multi-Level Structured Models for Document-Level Sentiment Classification. EMNLP 2010: 1046-1056 - [c6]Yisong Yue, Yue Gao, Olivier Chapelle, Ya Zhang, Thorsten Joachims:
Learning more powerful test statistics for click-based retrieval evaluation. SIGIR 2010: 507-514 - [c5]Yisong Yue, Rajan Patel, Hein Roehrig:
Beyond position bias: examining result attractiveness as a source of presentation bias in clickthrough data. WWW 2010: 1011-1018
2000 – 2009
- 2009
- [j1]Thorsten Joachims, Thomas Hofmann, Yisong Yue, Chun-Nam John Yu:
Predicting structured objects with support vector machines. Commun. ACM 52(11): 97-104 (2009) - [c4]Yisong Yue, Josef Broder, Robert Kleinberg, Thorsten Joachims:
The K-armed Dueling Bandits Problem. COLT 2009 - [c3]Yisong Yue, Thorsten Joachims:
Interactively optimizing information retrieval systems as a dueling bandits problem. ICML 2009: 1201-1208 - 2008
- [c2]Yisong Yue, Thorsten Joachims:
Predicting diverse subsets using structural SVMs. ICML 2008: 1224-1231 - 2007
- [c1]Yisong Yue, Thomas Finley, Filip Radlinski, Thorsten Joachims:
A support vector method for optimizing average precision. SIGIR 2007: 271-278
Coauthor Index
Anima Anandkumar
aka: Animashree Anandkumar
aka: Animashree Anandkumar
Jeremy Bernstein
aka: Jeremy D. Bernstein
aka: Jeremy D. Bernstein
Joel W. Burdick
aka: Joel Burdick
aka: Joel Burdick
Ivan Dario Jimenez Rodriguez
aka: Ivan D. Jimenez Rodriguez
aka: Ivan D. Jimenez Rodriguez
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