Qiang Liu
Faculty
Publications
     [Expand to show all 26][Minimize]
Metric Residual Networks for Sample Efficient Goal-Conditioned Reinforcement Learning 2023
Bo Liu, Yihao Feng, Qiang Liu, and Peter Stone, In Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), Washington, DC, US, February 2023.
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach 2022
Bo Liu, Mao Ye, Stephen Wright, Peter Stone, and Qiang Liu, In Conference on Neural Information Processing Systems, 2022, New Orleans, LA, December 2022.
Continual Learning and Private Unlearning 2022
Bo Liu, Qiang Liu, and Peter Stone, In Proceedings of the 1st Conference on Lifelong Learning Agents (CoLLAs), Montreal, Canada, August 2022.
Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition 2021
Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, and Animashree Anandkumar, In Proceedings of the 38th International Conference on Machine Learning, PMLR 139, 2021 (ICML), Vienna, Austria, July 2021.
Conflict-Averse Gradient Descent for Multi-task learning 2021
Bo Liu, Xingchao Liu, Xiaojie Jin, Peter Stone, and Qiang Liu, In Conference on Neural Information Processing Systems, 2021, Virtual, December 2021.
Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks 2020
Lemeng Wu, Bo Liu, Peter Stone, and Qiang Liu, In Advances in Neural Information Processing Systems 34 (2020), Vancouver, Canada, December 2020.
A kernel Loss for Solving Bellman Equation 2019
Yihao Feng, Lihong Li, Qiang Liu, No other information
Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation 2019
Ziyang Tang*, Yihao Feng*, Lihong Li, Denny Zhou, Qiang Liu , No other information
Exploration via Hindsight Goal Generation 2019
Zhizhou Ren, Kefan Dong, Yuan Zhou, Qiang Liu, Jian Peng, No other information
Improving Neural Language Modeling via Adversarial Training 2019
Dilin Wang*, Chengyue Gong*, Qiang Liu, No other information
Learning Self-Imitating Diverse Policies 2019
Tanmay Gangwani, Qiang Liu, Jian Peng, No other information
LithoROC: Lithography Hotspot Detection with Explicit ROC Optimization 2019
Wei Ye, Yibo Lin, Meng Li, Qiang Liu, David Z Pan, No other information
Mixed Precision Neural Architecture Search for Energy Efficient Deep Learning 2019
Chengyue Gong, Zixuan Jiang, Dilin Wang, Yibo Lin, Qiang Liu, David Z Pan, No other information
Nonlinear Stein Variational Gradient Descent for Learning Diversified Mixture Models 2019
Dilin Wang, Qiang Liu, No other information
Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy 2019
Yuan Xie, Boyi Liu, Qiang Liu, Zhaoran Wang, Yuan Zhou, Jian Peng, No other information
Quantile Stein Variational Gradient Descent for Batch Bayesian Optimization 2019
Chengyue Gong, Jian Peng, Qiang Liu, No other information
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel 2019
Colin Wei, Jason D. Lee, Qiang Liu, Tengyu Ma, No other information
Splitting Steepest Descent for Growing Neural Architectures 2019
Qiang Liu, Lemeng Wu and Dilin Wang, Advances in Neural Information Processing Systems (2019), pp. 10655--10665.
Stein Variational Gradient Descent With Matrix-Valued Kernels 2019
Dilin Wang*, Ziyang Tang*, Chandrajit Bajaj, Qiang Liu, No other information
Breaking the curse of horizon: Infinite-horizon off-policy estimation 2018
Qiang Liu, Lihong Li, Ziyang Tang, Dengyong Zhou, No other information
Goodness-of-Fit Testing for Discrete Distributions via Stein Discrepancy 2018
Jiasen Yang, Qiang Liu, Vinayak Rao, Jennifer Neville , No other information
Learning to Explore via Meta-Policy Gradient 2018
Tianbing Xu, Qiang Liu, Liang Zhao, Jian Peng, No other information
Stein Variational Gradient Descent as Moment Matching 2018
Qiang Liu, Dilin Wang, No other information
Stein Variational Gradient Descent Without Gradient 2018
Jun Han, Qiang Liu, No other information
Stein Variational Message Passing for Continuous Graphical Models 2018
Dilin Wang, Zhe Zeng, Qiang Liu, No other information
Variational inference with tail-adaptive f-divergence 2018
Dilin Wang, Hao Liu, Qiang Liu, No other information
Areas of Interest
Statistical Learning
Labs
Currently affiliated with Statistical Learning and AI