Koppel, Alec

37 publications

AISTATS 2025 Approximate Equivariance in Reinforcement Learning Jung Yeon Park, Sujay Bhatt, Sihan Zeng, Lawson L.S. Wong, Alec Koppel, Sumitra Ganesh, Robin Walters

TMLR 2025 Beyond Joint Demonstrations: Personalized Expert Guidance for Efficient Multi-Agent Reinforcement Learning Peihong Yu, Manav Mishra, Alec Koppel, Carl Busart, Priya Narayan, Dinesh Manocha, Amrit Singh Bedi, Pratap Tokekar

ICLR 2025 Collab: Controlled Decoding Using Mixture of Agents for LLM Alignment Souradip Chakraborty, Sujay Bhatt, Udari Madhushani Sehwag, Soumya Suvra Ghosal, Jiahao Qiu, Mengdi Wang, Dinesh Manocha, Furong Huang, Alec Koppel, Sumitra Ganesh

AAAI 2025 Decentralized Convergence to Equilibrium Prices in Trading Networks Edwin Lock, Benjamin Patrick Evans, Eleonora Kreacic, Sujay Bhatt, Alec Koppel, Sumitra Ganesh, Paul W. Goldberg

ICLR 2025 GenARM: Reward Guided Generation with Autoregressive Reward Model for Test-Time Alignment Yuancheng Xu, Udari Madhushani Sehwag, Alec Koppel, Sicheng Zhu, Bang An, Furong Huang, Sumitra Ganesh

AISTATS 2025 Learning in Herding Mean Field Games: Single-Loop Algorithm with Finite-Time Convergence Analysis Sihan Zeng, Sujay Bhatt, Alec Koppel, Sumitra Ganesh

NeurIPS 2025 Learning in Stackelberg Mean Field Games: A Non-Asymptotic Analysis Sihan Zeng, Benjamin Patrick Evans, Sujay Bhatt, Leo Ardon, Sumitra Ganesh, Alec Koppel

ICMLW 2024 A Policy Optimization Approach to the Solution of Unregularized Mean Field Games Sihan Zeng, Sujay Bhatt, Alec Koppel, Sumitra Ganesh

TMLR 2024 Byzantine-Resilient Decentralized Multi-Armed Bandits Jingxuan Zhu, Alec Koppel, Alvaro Velasquez, Ji Liu

ICLR 2024 Efficient Inverse Multiagent Learning Denizalp Goktas, Amy Greenwald, Sadie Zhao, Alec Koppel, Sumitra Ganesh

ICML 2024 Information-Directed Pessimism for Offline Reinforcement Learning Alec Koppel, Sujay Bhatt, Jiacheng Guo, Joe Eappen, Mengdi Wang, Sumitra Ganesh

ICML 2024 MaxMin-RLHF: Alignment with Diverse Human Preferences Souradip Chakraborty, Jiahao Qiu, Hui Yuan, Alec Koppel, Dinesh Manocha, Furong Huang, Amrit Bedi, Mengdi Wang

ICMLW 2024 MaxMin-RLHF: Towards Equitable Alignment of Large Language Models with Diverse Human Preferences Souradip Chakraborty, Jiahao Qiu, Hui Yuan, Alec Koppel, Furong Huang, Dinesh Manocha, Amrit Bedi, Mengdi Wang

JMLR 2024 On the Sample Complexity and Metastability of Heavy-Tailed Policy Search in Continuous Control Amrit Singh Bedi, Anjaly Parayil, Junyu Zhang, Mengdi Wang, Alec Koppel

ICLR 2024 PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback Souradip Chakraborty, Amrit Bedi, Alec Koppel, Huazheng Wang, Dinesh Manocha, Mengdi Wang, Furong Huang

TMLR 2024 Regularized Proportional Fairness Mechanism for Resource Allocation Without Money Sihan Zeng, Sujay Bhatt, Alec Koppel, Sumitra Ganesh

L4DC 2024 Robust Cooperative Multi-Agent Reinforcement Learning: A Mean-Field Type Game Perspective Muhammad Aneeq Uz Zaman, Mathieu Laurière, Alec Koppel, Tamer Başar

ICMLW 2024 SAIL: Self-Improving Efficient Online Alignment of Large Language Models Mucong Ding, Souradip Chakraborty, Vibhu Agrawal, Zora Che, Alec Koppel, Mengdi Wang, Amrit Bedi, Furong Huang

AISTATS 2024 Sharpened Lazy Incremental Quasi-Newton Method Aakash Sunil Lahoti, Spandan Senapati, Ketan Rajawat, Alec Koppel

ICML 2024 Towards Global Optimality for Practical Average Reward Reinforcement Learning Without Mixing Time Oracles Bhrij Patel, Wesley A Suttle, Alec Koppel, Vaneet Aggarwal, Brian M. Sadler, Dinesh Manocha, Amrit Bedi

NeurIPSW 2023 Active Learning with Missing Not at Random Outcomes Alan Mishler, Mohsen Ghassemi, Alec Koppel, Sumitra Ganesh

ICML 2023 Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic Wesley A Suttle, Amrit Bedi, Bhrij Patel, Brian M. Sadler, Alec Koppel, Dinesh Manocha

MLJ 2023 On the Sample Complexity of Actor-Critic Method for Reinforcement Learning with Function Approximation Harshat Kumar, Alec Koppel, Alejandro Ribeiro

AISTATS 2023 Oracle-Free Reinforcement Learning in Mean-Field Games Along a Single Sample Path Muhammad Aneeq Uz Zaman, Alec Koppel, Sujay Bhatt, Tamer Basar

AAAI 2023 Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning Souradip Chakraborty, Amrit Singh Bedi, Pratap Tokekar, Alec Koppel, Brian M. Sadler, Furong Huang, Dinesh Manocha

ICMLW 2023 Principal-Driven Reward Design and Agent Policy Alignment via Bilevel-RL Souradip Chakraborty, Amrit Bedi, Alec Koppel, Furong Huang, Mengdi Wang

ICML 2023 STEERING : Stein Information Directed Exploration for Model-Based Reinforcement Learning Souradip Chakraborty, Amrit Bedi, Alec Koppel, Mengdi Wang, Furong Huang, Dinesh Manocha

NeurIPS 2023 Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities Donghao Ying, Yunkai Zhang, Yuhao Ding, Alec Koppel, Javad Lavaei

AAAI 2022 Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach Qinbo Bai, Amrit Singh Bedi, Mridul Agarwal, Alec Koppel, Vaneet Aggarwal

AAAI 2022 Multi-Agent Reinforcement Learning with General Utilities via Decentralized Shadow Reward Actor-Critic Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel

ICML 2022 On the Hidden Biases of Policy Mirror Ascent in Continuous Action Spaces Amrit Singh Bedi, Souradip Chakraborty, Anjaly Parayil, Brian M Sadler, Pratap Tokekar, Alec Koppel

NeurIPSW 2022 Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning Souradip Chakraborty, Amrit Bedi, Alec Koppel, Pratap Tokekar, Furong Huang, Dinesh Manocha

ICML 2022 Sharpened Quasi-Newton Methods: Faster Superlinear Rate and Larger Local Convergence Neighborhood Qiujiang Jin, Alec Koppel, Ketan Rajawat, Aryan Mokhtari

JMLR 2020 A Class of Parallel Doubly Stochastic Algorithms for Large-Scale Learning Aryan Mokhtari, Alec Koppel, Martin Takac, Alejandro Ribeiro

L4DC 2020 Efficient Large-Scale Gaussian Process Bandits by Believing Only Informative Actions Amrit Singh Bedi, Dheeraj Peddireddy, Vaneet Aggarwal, Alec Koppel

NeurIPS 2020 Variational Policy Gradient Method for Reinforcement Learning with General Utilities Junyu Zhang, Alec Koppel, Amrit Singh Bedi, Csaba Szepesvari, Mengdi Wang

JMLR 2019 Parsimonious Online Learning with Kernels via Sparse Projections in Function Space Alec Koppel, Garrett Warnell, Ethan Stump, Alejandro Ribeiro