Alec Koppel

ORCID

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 151

Top Venues

CoRR

IEEE Trans. Signal Process.

ICASSP

ACC

Publications

Muhammad Aneeq uz Zaman, Alec Koppel, Mathieu Laurière, Tamer Basar
Independent RL for Cooperative-Competitive Agents: A Mean-Field Perspective. CoRR (2024)
Denizalp Goktas, Amy Greenwald, Sadie Zhao, Alec Koppel, Sumitra Ganesh
Efficient Inverse Multiagent Learning. ICLR (2024)
Peihong Yu, Manav Mishra, Alec Koppel, Carl E. Busart, Priya Narayan, Dinesh Manocha, Amrit S. Bedi, Pratap Tokekar
Beyond Joint Demonstrations: Personalized Expert Guidance for Efficient Multi-Agent Reinforcement Learning. CoRR (2024)
Boya Hou, Sina Sanjari, Alec Koppel, Subhonmesh Bose
Compressed Online Learning of Conditional Mean Embedding. CoRR (2024)
Souradip Chakraborty, Jiahao Qiu, Hui Yuan, Alec Koppel, Furong Huang, Dinesh Manocha, Amrit Singh Bedi, Mengdi Wang
MaxMin-RLHF: Towards Equitable Alignment of Large Language Models with Diverse Human Preferences. CoRR (2024)
Muhammad Aneeq uz Zaman, Mathieu Laurière, Alec Koppel, Tamer Basar
Robust cooperative multi-agent reinforcement learning: A mean-field type game perspective. L4DC (2024)
Alec Koppel, Joe Eappen, Sujay Bhatt, Cole Hawkins, Sumitra Ganesh
Online MCMC Thinning with Kernelized Stein Discrepancy. SIAM J. Math. Data Sci. 6 (1) (2024)
Aakash Sunil Lahoti, Spandan Senapati, Ketan Rajawat, Alec Koppel
Sharpened Lazy Incremental Quasi-Newton Method. AISTATS (2024)
Muhammad Aneeq uz Zaman, Mathieu Laurière, Alec Koppel, Tamer Basar
Robust Cooperative Multi-Agent Reinforcement Learning:A Mean-Field Type Game Perspective. CoRR (2024)
Mucong Ding, Souradip Chakraborty, Vibhu Agrawal, Zora Che, Alec Koppel, Mengdi Wang, Amrit S. Bedi, Furong Huang
SAIL: Self-Improving Efficient Online Alignment of Large Language Models. CoRR (2024)
Souradip Chakraborty, Amrit S. Bedi, Alec Koppel, Huazheng Wang, Dinesh Manocha, Mengdi Wang, Furong Huang
PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback. ICLR (2024)
Bhrij Patel, Wesley A. Suttle, Alec Koppel, Vaneet Aggarwal, Brian M. Sadler, Amrit Singh Bedi, Dinesh Manocha
Global Optimality without Mixing Time Oracles in Average-reward RL via Multi-level Actor-Critic. CoRR (2024)
Souradip Chakraborty, Amrit Singh Bedi, Kasun Weerakoon, Prithvi Poddar, Alec Koppel, Pratap Tokekar, Dinesh Manocha
Dealing with Sparse Rewards in Continuous Control Robotics via Heavy-Tailed Policy Optimization. ICRA (2023)
Yifan Yang, Alec Koppel, Zheng Zhang
A Gradient-based Approach for Online Robust Deep Neural Network Training with Noisy Labels. CoRR (2023)
Jingxuan Zhu, Alec Koppel, Alvaro Velasquez, Ji Liu
Byzantine-Resilient Decentralized Multi-Armed Bandits. CoRR (2023)
Donghao Ying, Yuhao Ding, Alec Koppel, Javad Lavaei
Scalable Multi-Agent Reinforcement Learning with General Utilities. CoRR (2023)
Muhammad Aneeq uz Zaman, Alec Koppel, Sujay Bhatt, Tamer Basar
Oracle-free Reinforcement Learning in Mean-Field Games along a Single Sample Path. AISTATS (2023)
Sihan Zeng, Sujay Bhatt, Eleonora Kreacic, Parisa Hassanzadeh, Alec Koppel, Sumitra Ganesh
Near-Optimal Fair Resource Allocation for Strategic Agents without Money: A Data-Driven Approach. CoRR (2023)
Bhrij Patel, Kasun Weerakoon, Wesley A. Suttle, Alec Koppel, Brian M. Sadler, Amrit Singh Bedi, Dinesh Manocha
Ada-NAV: Adaptive Trajectory-Based Sample Efficient Policy Learning for Robotic Navigation. CoRR (2023)
Wesley A. Suttle, Amrit Singh Bedi, Bhrij Patel, Brian M. Sadler, Alec Koppel, Dinesh Manocha
Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic. CoRR (2023)
Harshat Kumar, Alec Koppel, Alejandro Ribeiro
On the sample complexity of actor-critic method for reinforcement learning with function approximation. Mach. Learn. 112 (7) (2023)
Aakash Lahoti, Spandan Senapati, Ketan Rajawat, Alec Koppel
Sharpened Lazy Incremental Quasi-Newton Method. CoRR (2023)
Hans He, Alec Koppel, Amrit Singh Bedi, Mazen Farhood, Daniel J. Stilwell
Bi-Level Nonstationary Kernels for Online Gaussian Process Regression. CASE (2023)
Wesley A. Suttle, Amrit S. Bedi, Bhrij Patel, Brian M. Sadler, Alec Koppel, Dinesh Manocha
Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic. ICML (2023)
Zhan Gao, Aryan Mokhtari, Alec Koppel
Limited-Memory Greedy Quasi-Newton Method with Non-asymptotic Superlinear Convergence Rate. CoRR (2023)
Souradip Chakraborty, Amrit Singh Bedi, Alec Koppel, Dinesh Manocha, Huazheng Wang, Furong Huang, Mengdi Wang
Aligning Agent Policy with Externalities: Reward Design via Bilevel RL. CoRR (2023)
Souradip Chakraborty, Amrit Singh Bedi, Alec Koppel, Mengdi Wang, Furong Huang, Dinesh Manocha
STEERING: Stein Information Directed Exploration for Model-Based Reinforcement Learning. CoRR (2023)
Wesley A. Suttle, Alec Koppel, Ji Liu
Information-Directed Policy Search in Sparse-Reward Settings via the Occupancy Information Ratio. CISS (2023)
Donghao Ying, Yunkai Zhang, Yuhao Ding, Alec Koppel, Javad Lavaei
Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities. NeurIPS (2023)
Souradip Chakraborty, Amrit S. Bedi, Alec Koppel, Mengdi Wang, Furong Huang, Dinesh Manocha
STEERING : Stein Information Directed Exploration for Model-Based Reinforcement Learning. ICML (2023)
Donghao Ying, Yuhao Ding, Alec Koppel, Javad Lavaei
Scalable Multi-Agent Reinforcement Learning with General Utilities. ACC (2023)
Hans He, Alec Koppel, Amrit Singh Bedi, Daniel J. Stilwell, Mazen Farhood, Benjamin Biggs
Decentralized Multi-agent Exploration with Limited Inter-agent Communications. ICRA (2023)
Donghao Ying, Yunkai Zhang, Yuhao Ding, Alec Koppel, Javad Lavaei
Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities. CoRR (2023)
Souradip Chakraborty, Amrit Singh Bedi, Pratap Tokekar, Alec Koppel, Brian M. Sadler, Furong Huang, Dinesh Manocha
Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning. AAAI (2023)
Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel
Multi-Agent Reinforcement Learning with General Utilities via Decentralized Shadow Reward Actor-Critic. AAAI (2022)
Yulun Tian, Amrit Singh Bedi, Alec Koppel, Miguel Calvo-Fullana, David M. Rosen, Jonathan P. How
Distributed Riemannian Optimization with Lazy Communication for Collaborative Geometric Estimation. CoRR (2022)
Amrit Singh Bedi, Souradip Chakraborty, Anjaly Parayil, Brian M. Sadler, Pratap Tokekar, Alec Koppel
On the Hidden Biases of Policy Mirror Ascent in Continuous Action Spaces. ICML (2022)
Zhan Gao, Alec Koppel, Alejandro Ribeiro
Balancing Rates and Variance via Adaptive Batch-Size for Stochastic Optimization Problems. IEEE Trans. Signal Process. 70 (2022)
Amrit Singh Bedi, Chen Fan, Alec Koppel, Anit Kumar Sahu, Brian M. Sadler, Furong Huang, Dinesh Manocha
FedBC: Calibrating Global and Local Models via Federated Learning Beyond Consensus. CoRR (2022)
Qiujiang Jin, Alec Koppel, Ketan Rajawat, Aryan Mokhtari
Sharpened Quasi-Newton Methods: Faster Superlinear Rate and Larger Local Convergence Neighborhood. ICML (2022)
Hrusikesha Pradhan, Alec Koppel, Ketan Rajawat
On Submodular Set Cover Problems for Near-Optimal Online Kernel Basis Selection. ICASSP (2022)
Souradip Chakraborty, Amrit Singh Bedi, Alec Koppel, Pratap Tokekar, Dinesh Manocha
Dealing with Sparse Rewards in Continuous Control Robotics via Heavy-Tailed Policies. CoRR (2022)
James Di, Ehsan Zobeidi, Alec Koppel, Nikolay Atanasov
Distributed Gaussian Process Mapping for Robot Teams with Time-varying Communication. ACC (2022)
Abhishek Chakraborty, Ketan Rajawat, Alec Koppel
Sparse Representations of Positive Functions via First- and Second-Order Pseudo-Mirror Descent. IEEE Trans. Signal Process. 70 (2022)
Ehsan Zobeidi, Alec Koppel, Nikolay Atanasov
Dense Incremental Metric-Semantic Mapping for Multiagent Systems via Sparse Gaussian Process Regression. IEEE Trans. Robotics 38 (5) (2022)
Muhammad Aneeq uz Zaman, Alec Koppel, Sujay Bhatt, Tamer Basar
Oracle-free Reinforcement Learning in Mean-Field Games along a Single Sample Path. CoRR (2022)
Cole Hawkins, Alec Koppel, Zheng Zhang
Online, Informative MCMC Thinning with Kernelized Stein Discrepancy. CoRR (2022)
Yulun Tian, Amrit Singh Bedi, Alec Koppel, Miguel Calvo-Fullana, David M. Rosen, Jonathan P. How
Distributed Riemannian Optimization with Lazy Communication for Collaborative Geometric Estimation. IROS (2022)
Amrit Singh Bedi, Souradip Chakraborty, Anjaly Parayil, Brian M. Sadler, Pratap Tokekar, Alec Koppel
On the Hidden Biases of Policy Mirror Ascent in Continuous Action Spaces. CoRR (2022)
Souradip Chakraborty, Amrit Singh Bedi, Alec Koppel, Brian M. Sadler, Furong Huang, Pratap Tokekar, Dinesh Manocha
Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning. CoRR (2022)
Wesley A. Suttle, Alec Koppel, Ji Liu
Policy Gradient for Ratio Optimization: A Case Study. CISS (2022)
Yagiz Savas, Erfaun Noorani, Alec Koppel, John S. Baras, Ufuk Topcu, Brian M. Sadler
Collaborative one-shot beamforming under localization errors: A discrete optimization approach. Signal Process. 200 (2022)
Amrit Singh Bedi, Ketan Rajawat, Vaneet Aggarwal, Alec Koppel
Escaping Saddle Points for Successive Convex Approximation. IEEE Trans. Signal Process. 70 (2022)
Wesley A. Suttle, Alec Koppel, Ji Liu
Occupancy Information Ratio: Infinite-Horizon, Information-Directed, Parameterized Policy Search. CoRR (2022)
Alec Koppel, Amrit Singh Bedi, Bhargav Ganguly, Vaneet Aggarwal
Convergence Rates of Average-Reward Multi-agent Reinforcement Learning via Randomized Linear Programming. CDC (2022)
Qinbo Bai, Amrit Singh Bedi, Mridul Agarwal, Alec Koppel, Vaneet Aggarwal
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach. AAAI (2022)
Alec Koppel, Garrett Warnell, Ethan Stump, Peter Stone, Alejandro Ribeiro
Policy Evaluation in Continuous MDPs With Efficient Kernelized Gradient Temporal Difference. IEEE Trans. Autom. Control. 66 (4) (2021)
Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel
MARL with General Utilities via Decentralized Shadow Reward Actor-Critic. CoRR (2021)
Qinbo Bai, Amrit Singh Bedi, Mridul Agarwal, Alec Koppel, Vaneet Aggarwal
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach. CoRR (2021)
James Di, Ehsan Zobeidi, Alec Koppel, Nikolay Atanasov
Distributed Gaussian Process Mapping for Robot Teams with Time-varying Communication. CoRR (2021)
Alec Koppel, Amrit Singh Bedi, Brian M. Sadler, Víctor Elvira
Nearly Consistent Finite Particle Estimates in Streaming Importance Sampling. IEEE Trans. Signal Process. 69 (2021)
Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel
Beyond Cumulative Returns via Reinforcement Learning over State-Action Occupancy Measures. ACC (2021)
Alec Koppel, Hrusikesha Pradhan, Ketan Rajawat
Consistent online Gaussian process regression without the sample complexity bottleneck. Stat. Comput. 31 (6) (2021)
Deepak S. Kalhan, Amrit Singh Bedi, Alec Koppel, Ketan Rajawat, Hamed Hassani, Abhishek K. Gupta, Adrish Banerjee
Dynamic Online Learning via Frank-Wolfe Algorithm. IEEE Trans. Signal Process. 69 (2021)
Amrit Singh Bedi, Anjaly Parayil, Junyu Zhang, Mengdi Wang, Alec Koppel
On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control. CoRR (2021)
Ehsan Zobeidi, Alec Koppel, Nikolay Atanasov
Dense Incremental Metric-Semantic Mapping for Multi-Agent Systems via Sparse Gaussian Process Regression. CoRR (2021)
Michael E. Kepler, Alec Koppel, Amrit Singh Bedi, Daniel J. Stilwell
Wasserstein-Splitting Gaussian Process Regression for Heterogeneous Online Bayesian Inference. IROS (2021)
Amrit Singh Bedi, Alec Koppel, Mengdi Wang, Junyu Zhang
Intermittent Communications in Decentralized Shadow Reward Actor-Critic. CDC (2021)
Michael E. Kepler, Alec Koppel, Amrit Singh Bedi, Daniel J. Stilwell
Wasserstein-Splitting Gaussian Process Regression for Heterogeneous Online Bayesian Inference. CoRR (2021)
Alec Koppel, Amrit Singh Bedi, Bhargav Ganguly, Vaneet Aggarwal
Randomized Linear Programming for Tabular Average-Cost Multi-agent Reinforcement Learning. ACSCC (2021)
Abhishek Chakraborty, Ketan Rajawat, Alec Koppel
Projected Pseudo-Mirror Descent in Reproducing Kernel Hilbert Space. ACSCC (2021)
Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel
Cautious Reinforcement Learning via Distributional Risk in the Dual Domain. IEEE J. Sel. Areas Inf. Theory 2 (2) (2021)
Amrit Singh Bedi, Alec Koppel, Ketan Rajawat, Panchajanya Sanyal
Nonparametric Compositional Stochastic Optimization for Risk-Sensitive Kernel Learning. IEEE Trans. Signal Process. 69 (2021)
Anjaly Parayil, Amrit Singh Bedi, Alec Koppel
Joint Position and Beamforming Control via Alternating Nonlinear Least-Squares with a Hierarchical Gamma Prior. ACC (2021)
Erfaun Noorani, Yagiz Savas, Alec Koppel, John S. Baras, Ufuk Topcu, Brian M. Sadler
Collaborative Beamforming for Agents with Localization Errors. ACSCC (2021)
Hrusikesha Pradhan, Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
Adaptive Kernel Learning in Heterogeneous Networks. IEEE Trans. Signal Inf. Process. over Networks 7 (2021)
Sujay Bhatt, Weichao Mao, Alec Koppel, Tamer Basar
Semiparametric Information State Embedding for Policy Search under Imperfect Information. CDC (2021)
Ekaterina I. Tolstaya, Ethan Stump, Alec Koppel, Alejandro Ribeiro
Composable Learning with Sparse Kernel Representations. CoRR (2021)
Alec Koppel, Amrit S. Bedi, Vikram Krishnamurthy
A Dynamical Systems Perspective on Online Bayesian Nonparametric Estimators with Adaptive Hyperparameters. ICASSP (2021)
Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel
Cautious Reinforcement Learning via Distributional Risk in the Dual Domain. CoRR (2020)
Junyu Zhang, Alec Koppel, Amrit Singh Bedi, Csaba Szepesvári, Mengdi Wang
Variational Policy Gradient Method for Reinforcement Learning with General Utilities. NeurIPS (2020)
Aryan Mokhtari, Alec Koppel
High-Dimensional Nonconvex Stochastic Optimization by Doubly Stochastic Successive Convex Approximation. IEEE Trans. Signal Process. 68 (2020)
Alec Koppel, Amrit Singh Bedi, Ketan Rajawat, Brian M. Sadler
Optimally Compressed Nonparametric Online Learning: Tradeoffs between memory and consistency. IEEE Signal Process. Mag. 37 (3) (2020)
Nagananda K. G, Rick S. Blum, Alec Koppel
Reduced-rank Least Squares Parameter Estimation in the Presence of Byzantine Sensors. CISS (2020)
Zhan Gao, Alec Koppel, Alejandro Ribeiro
Balancing Rates and Variance via Adaptive Batch-Size for Stochastic Optimization Problems. CoRR (2020)
Amrit Singh Bedi, Alec Koppel, Ketan Rajawat, Brian M. Sadler
Trading Dynamic Regret for Model Complexity in Nonstationary Nonparametric Optimization. ACC (2020)
Yulun Tian, Alec Koppel, Amrit Singh Bedi, Jonathan P. How
Asynchronous and Parallel Distributed Pose Graph Optimization. CoRR (2020)
Yulun Tian, Alec Koppel, Amrit Singh Bedi, Jonathan P. How
Asynchronous and Parallel Distributed Pose Graph Optimization. IEEE Robotics Autom. Lett. 5 (4) (2020)
Bingjia Wang, Alec Koppel, Vikram Krishnamurthy
A Markov Decision Process Approach to Active Meta Learning. CoRR (2020)
Amrit Singh Bedi, Dheeraj Peddireddy, Vaneet Aggarwal, Alec Koppel
Efficient Large-Scale Gaussian Process Bandits by Believing only Informative Actions. L4DC (2020)
Abhishek Chakraborty, Ketan Rajawat, Alec Koppel
Sparse Representations of Positive Functions via Projected Pseudo-Mirror Descent. CoRR (2020)
Deepak S. Kalhan, Amrit S. Bedi, Alec Koppel, Ketan Rajawat, Abhishek K. Gupta, Adrish Banerjee
Projection Free Dynamic Online Learning. ICASSP (2020)
Erfaun Noorani, Yagiz Savas, Alec Koppel, John S. Baras, Ufuk Topcu, Brian M. Sadler
Distributed Beamforming for Agents with Localization Errors. CoRR (2020)
Amrit Singh Bedi, Dheeraj Peddireddy, Vaneet Aggarwal, Alec Koppel
Efficient Gaussian Process Bandits by Believing only Informative Actions. CoRR (2020)
Ehsan Zobeidi, Alec Koppel, Nikolay Atanasov
Dense Incremental Metric-Semantic Mapping via Sparse Gaussian Process Regression. IROS (2020)
Aryan Mokhtari, Alec Koppel, Martin Takác, Alejandro Ribeiro
A Class of Parallel Doubly Stochastic Algorithms for Large-Scale Learning. J. Mach. Learn. Res. 21 (2020)
Sujay Bhatt, Alec Koppel, Vikram Krishnamurthy
Policy Gradient using Weak Derivatives for Reinforcement Learning. CoRR (2020)
Zhan Gao, Alec Koppel, Alejandro Ribeiro
Balancing Rates and Variance via Adaptive Batch-Sizes in First-Order Stochastic Optimization. ICASSP (2020)
Hrusikesha Pradhan, Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
Conservative Multi-agent Online Kernel Learning in Heterogeneous Networks. ACSSC (2020)
Alec Koppel, Hrusikesha Pradhan, Ketan Rajawat
Consistent Online Gaussian Process Regression Without the Sample Complexity Bottleneck. CoRR (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Alec Koppel