Miao Liu - RankMe

75 papers A* 21A 6B 1C 2Misc 2Journal 36Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	Misc	`conf`	Contextual Value Alignment. ICASSP Pierre L. Dognin, Jesus Rios, Ronny Luss, Prasanna Sattigeri, Miao Liu, Inkit Padhi, Matthew Riemer, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf
2025	—	`conf`	Evaluating the Prompt Steerability of Large Language Models. NAACL (Long Papers) Erik Miehling, Michael Desmond, Karthikeyan Natesan Ramamurthy, Elizabeth M. Daly, Kush R. Varshney, Eitan Farchi, Pierre L. Dognin, Jesus Rios, Djallel Bouneffouf, Miao Liu, Prasanna Sattigeri
2025	—	`conf`	Position: Theory of Mind Benchmarks are Broken for Large Language Models. ICML (Position Papers) Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf, Payel Das, Miao Liu, Justin D. Weisz, Murray Campbell
2025	A	`conf`	Q-function Decomposition with Intervention Semantics for Factored Action Spaces. AISTATS Junkyu Lee, Tian Gao, Elliot Nelson, Miao Liu, Debarun Bhattacharjya, Songtao Lu
2025	J	`jnl`	Q-function Decomposition with Intervention Semantics with Factored Action Spaces. CoRR Junkyu Lee, Tian Gao, Elliot Nelson, Miao Liu, Debarun Bhattacharjya, Songtao Lu
2025	J	`jnl`	The Effectiveness of Approximate Regularized Replay for Efficient Supervised Fine-Tuning of Large Language Models. CoRR Matthew Riemer, Erik Miehling, Miao Liu, Djallel Bouneffouf, Murray Campbell
2024	J	`jnl`	ADR-BC: Adversarial Density Weighted Regression Behavior Cloning. CoRR Ziqi Zhang, Zifeng Zhuang, Donglin Wang, Jingzehua Xu, Miao Liu, Shuai Zhang
2024	J	`jnl`	Can Large Language Models Adapt to Other Agents In-Context? CoRR Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf, Payel Das, Miao Liu, Justin D. Weisz, Murray Campbell
2024	A*	`conf`	ComVas: Contextual Moral Values Alignment System. IJCAI Inkit Padhi, Pierre L. Dognin, Jesus Rios, Ronny Luss, Swapnaja Achintalwar, Matthew Riemer, Miao Liu, Prasanna Sattigeri, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf
2024	J	`jnl`	Contextual Moral Value Alignment Through Context-Based Aggregation. CoRR Pierre L. Dognin, Jesus Rios, Ronny Luss, Inkit Padhi, Matthew D. Riemer, Miao Liu, Prasanna Sattigeri, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf
2024	J	`jnl`	Evaluating the Prompt Steerability of Large Language Models. CoRR Erik Miehling, Michael Desmond, Karthikeyan Natesan Ramamurthy, Elizabeth M. Daly, Pierre L. Dognin, Jesus Rios, Djallel Bouneffouf, Miao Liu
2024	A*	`conf`	SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning. ICML Shuai Zhang, Heshan Devaka Fernando, Miao Liu, Keerthiram Murugesan, Songtao Lu, Pin-Yu Chen, Tianyi Chen, Meng Wang
2024	J	`jnl`	SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning. CoRR Shuai Zhang, Heshan Devaka Fernando, Miao Liu, Keerthiram Murugesan, Songtao Lu, Pin-Yu Chen, Tianyi Chen, Meng Wang
2024	Misc	`conf`	Variance Reduction Can Improve Trade-Off in Multi-Objective Learning. ICASSP Heshan Devaka Fernando, Lisha Chen, Songtao Lu, Pin-Yu Chen, Miao Liu, Subhajit Chaudhury, Keerthiram Murugesan, Gaowen Liu, Meng Wang, Tianyi Chen
2023	A*	`conf`	Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks. ICLR Shuai Zhang, Meng Wang, Pin-Yu Chen, Sijia Liu, Songtao Lu, Miao Liu
2023	J	`jnl`	Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks. CoRR Shuai Zhang, Meng Wang, Pin-Yu Chen, Sijia Liu, Songtao Lu, Miao Liu
2023	J	`jnl`	Learning in Factored Domains with Information-Constrained Visual Representations. CoRR Tyler Malloy, Miao Liu, Matthew D. Riemer, Tim Klinger, Gerald Tesauro, Chris R. Sims
2023	A*	`conf`	Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach. ICLR Heshan Devaka Fernando, Han Shen, Miao Liu, Subhajit Chaudhury, Keerthiram Murugesan, Tianyi Chen
2023	A*	`conf`	On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration. NeurIPS Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury
2023	J	`jnl`	On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration. CoRR Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury
2022	J	`jnl`	AI Planning Annotation for Sample Efficient Reinforcement Learning. CoRR Junkyu Lee, Michael Katz, Don Joven Agravante, Miao Liu, Tim Klinger, Murray Campbell, Shirin Sohrabi, Gerald Tesauro
2022	A*	`conf`	Context-Specific Representation Abstraction for Deep Option Learning. AAAI Marwa Abdulhai, Dong-Ki Kim, Matthew Riemer, Miao Liu, Gerald Tesauro, Jonathan P. How
2022	—	`conf`	Cost-Efficient Reinforcement Learning for Optimal Trade Execution on Dynamic Market Environment. ICAIF Di Chen, Yada Zhu, Miao Liu, Jianbo Li
2022	J	`jnl`	Game-Theoretical Perspectives on Active Equilibria: A Preferred Solution Concept over Nash Equilibria. CoRR Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster, Gerald Tesauro, Jonathan P. How
2022	A*	`conf`	IDYNO: Learning Nonparametric DAGs from Interventional Dynamic Data. ICML Tian Gao, Debarun Bhattacharjya, Elliot Nelson, Miao Liu, Yue Yu
2022	A*	`conf`	Influencing Long-Term Behavior in Multiagent Reinforcement Learning. NeurIPS Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster, Michael Everett, Chuangchuang Sun, Gerald Tesauro, Jonathan P. How
2022	J	`jnl`	Influencing Long-Term Behavior in Multiagent Reinforcement Learning. CoRR Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster, Michael Everett, Chuangchuang Sun, Gerald Tesauro, Jonathan P. How
2022	A	`conf`	Linearizing contextual bandits with latent state dynamics. UAI Elliot Nelson, Debarun Bhattacharjya, Tian Gao, Miao Liu, Djallel Bouneffouf, Pascal Poupart
2022	J	`jnl`	Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Stochastic Approach. CoRR Heshan Devaka Fernando, Han Shen, Miao Liu, Subhajit Chaudhury, Keerthiram Murugesan, Tianyi Chen
2021	A*	`conf`	A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning. ICML Dong-Ki Kim, Miao Liu, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan P. How
2021	C	`conf`	Capacity-Limited Decentralized Actor-Critic for Multi-Agent Games. CoG Tyler Malloy, Chris R. Sims, Tim Klinger, Miao Liu, Matthew Riemer, Gerald Tesauro
2021	J	`jnl`	Context-Specific Representation Abstraction for Deep Option Learning. CoRR Marwa Abdulhai, Dong-Ki Kim, Matthew Riemer, Miao Liu, Gerald Tesauro, Jonathan P. How
2021	B	`conf`	Modeling Capacity-Limited Decision Making Using a Variational Autoencoder. CogSci Tyler Malloy, Tim Klinger, Miao Liu, Gerald Tesauro, Matthew Riemer, Chris R. Sims
2021	A*	`conf`	RL Generalization in a Theory of Mind Game Through a Sleep Metaphor (Student Abstract). AAAI Tyler Malloy, Tim Klinger, Miao Liu, Gerald Tesauro, Matthew Riemer, Chris R. Sims
2020	J	`jnl`	A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning. CoRR Dong-Ki Kim, Miao Liu, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan P. How
2020	J	`jnl`	Consolidation via Policy Information Regularization in Deep RL for Multi-Agent Games. CoRR Tyler Malloy, Tim Klinger, Miao Liu, Matthew Riemer, Gerald Tesauro, Chris R. Sims
2020	J	`jnl`	Deep RL With Information Constrained Policies: Generalization in Continuous Control. CoRR Tyler Malloy, Chris R. Sims, Tim Klinger, Miao Liu, Matthew Riemer, Gerald Tesauro
2020	A	`conf`	Learning Hierarchical Teaching Policies for Cooperative Agents. AAMAS Dong-Ki Kim, Miao Liu, Shayegan Omidshafiei, Sebastian Lopez-Cot, Matthew Riemer, Golnaz Habibi, Gerald Tesauro, Sami Mourad, Murray Campbell, Jonathan P. How
2020	A*	`conf`	On the Role of Weight Sharing During Deep Option Learning. AAAI Matthew Riemer, Ignacio Cases, Clemens Rosenbaum, Miao Liu, Gerald Tesauro
2019	J	`jnl`	Automatic Pan-Tilt Camera Control for Learning Dirichlet Process Gaussian Process (DPGP) Mixture Models of Multiple Moving Targets. IEEE Trans. Autom. Control. Hongchuan Wei, Pingping Zhu, Miao Liu, Jonathan P. How, Silvia Ferrari
2019	J	`jnl`	Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning. CoRR Dong-Ki Kim, Miao Liu, Shayegan Omidshafiei, Sebastian Lopez-Cot, Matthew Riemer, Golnaz Habibi, Gerald Tesauro, Sami Mourad, Murray Campbell, Jonathan P. How
2019	—	`conf`	Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference. ICLR (Poster) Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, Gerald Tesauro
2019	A*	`conf`	Learning to Teach in Cooperative Multiagent Reinforcement Learning. AAAI Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell, Jonathan P. How
2019	J	`jnl`	On the Role of Weight Sharing During Deep Option Learning. CoRR Matthew Riemer, Ignacio Cases, Clemens Rosenbaum, Miao Liu, Gerald Tesauro
2018	—	`conf`	Eigenoption Discovery through the Deep Successor Representation. ICLR (Poster) Marlos C. Machado, Clemens Rosenbaum, Xiaoxiao Guo, Miao Liu, Gerald Tesauro, Murray Campbell
2018	A*	`conf`	Learning Abstract Options. NeurIPS Matthew Riemer, Miao Liu, Gerald Tesauro
2018	J	`jnl`	Learning Abstract Options. CoRR Matthew Riemer, Miao Liu, Gerald Tesauro
2018	J	`jnl`	Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference. CoRR Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, Gerald Tesauro
2018	J	`jnl`	Learning to Teach in Cooperative Multiagent Reinforcement Learning. CoRR Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell, Jonathan P. How
2017	A*	`conf`	Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning. ICRA Yu Fan Chen, Miao Liu, Michael Everett, Jonathan P. How
2017	J	`jnl`	Eigenoption Discovery through the Deep Successor Representation. CoRR Marlos C. Machado, Clemens Rosenbaum, Xiaoxiao Guo, Miao Liu, Gerald Tesauro, Murray Campbell
2017	J	`jnl`	Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions. CoRR Miao Liu, Kavinayan Sivakumar, Shayegan Omidshafiei, Christopher Amato, Jonathan P. How
2017	A	`conf`	Learning for multi-robot cooperation in partially observable stochastic environments with macro-actions. IROS Miao Liu, Kavinayan Sivakumar, Shayegan Omidshafiei, Christopher Amato, Jonathan P. How
2017	C	`conf`	Quickest change detection approach to optimal control in Markov decision processes with model changes. ACC Taposh Banerjee, Miao Liu, Jonathan P. How
2017	J	`jnl`	Scalable Accelerated Decentralized Multi-Robot Policy Search in Continuous Observation Spaces. CoRR Shayegan Omidshafiei, Christopher Amato, Miao Liu, Michael Everett, Jonathan P. How, John Vian
2017	A*	`conf`	Scalable accelerated decentralized multi-robot policy search in continuous observation spaces. ICRA Shayegan Omidshafiei, Christopher Amato, Miao Liu, Michael Everett, Jonathan P. How, John Vian
2017	J	`jnl`	Semantic-level Decentralized Multi-Robot Decision-Making using Probabilistic Macro-Observations. CoRR Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett T. Lopez, Christopher Amato, Miao Liu, Jonathan P. How, John Vian
2017	A*	`conf`	Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations. ICRA Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett T. Lopez, Christopher Amato, Miao Liu, Jonathan P. How, John Vian
2017	J	`jnl`	Socially Aware Motion Planning with Deep Reinforcement Learning. CoRR Yu Fan Chen, Michael Everett, Miao Liu, Jonathan P. How
2017	A	`conf`	Socially aware motion planning with deep reinforcement learning. IROS Yu Fan Chen, Michael Everett, Miao Liu, Jonathan P. How
2017	J	`jnl`	The Eigenoption-Critic Framework. CoRR Miao Liu, Marlos C. Machado, Gerald Tesauro, Murray Campbell
2016	A*	`conf`	Augmented dictionary learning for motion prediction. ICRA Yu Fan Chen, Miao Liu, Jonathan P. How
2016	J	`jnl`	Decentralized Non-communicating Multiagent Collision Avoidance with Deep Reinforcement Learning. CoRR Yu Fan Chen, Miao Liu, Michael Everett, Jonathan P. How
2016	J	`jnl`	Information value in nonparametric Dirichlet-process Gaussian-process (DPGP) mixture models. Autom. Hongchuan Wei, Wenjie Lu, Pingping Zhu, Silvia Ferrari, Miao Liu, Robert H. Klein, Shayegan Omidshafiei, Jonathan P. How
2016	A*	`conf`	Learning for Decentralized Control of Multiagent Systems in Large, Partially-Observable Stochastic Environments. AAAI Miao Liu, Christopher Amato, Emily P. Anesta, John Daniel Griffith, Jonathan P. How
2016	A	`conf`	Motion planning with diffusion maps. IROS Yu Fan Chen, Shih-Yuan Liu, Miao Liu, Justin Miller, Jonathan P. How
2016	J	`jnl`	Quickest Change Detection Approach to Optimal Control in Markov Decision Processes with Model Changes. CoRR Taposh Banerjee, Miao Liu, Jonathan P. How
2016	J	`jnl`	Reports of the AAAI 2016 Spring Symposium Series. AI Mag. Christopher Amato, Ofra Amir, Joanna Bryson, Barbara J. Grosz, Bipin Indurkhya, Emre Kiciman, Takashi Kido, William F. Lawless, Miao Liu, Braden McDorman, Ross Mead, Frans A. Oliehoek, Andrew Specian, Georgi Stojanov, Keiki Takadama
2015	A*	`conf`	Stick-Breaking Policy Learning in Dec-POMDPs. IJCAI Miao Liu, Christopher Amato, Xuejun Liao, Lawrence Carin, Jonathan P. How
2015	J	`jnl`	Stick-Breaking Policy Learning in Dec-POMDPs. CoRR Miao Liu, Christopher Amato, Xuejun Liao, Lawrence Carin, Jonathan P. How
2014	—	`—`	Efficient Bayesian Nonparametric Methods for Model-Free Reinforcement Learning in Centralized and Decentralized Sequential Environments. Miao Liu
2013	J	`jnl`	Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture CoRR Trevor Campbell, Miao Liu, Brian Kulis, Jonathan P. How
2013	—	`conf`	Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture. NIPS Trevor Campbell, Miao Liu, Brian Kulis, Jonathan P. How, Lawrence Carin
2013	A*	`conf`	Online Expectation Maximization for Reinforcement Learning in POMDPs. IJCAI Miao Liu, Xuejun Liao, Lawrence Carin
2011	A*	`conf`	The Infinite Regionalized Policy Representation. ICML Miao Liu, Xuejun Liao, Lawrence Carin