Alec Koppel - RankMe

192 papers A* 19A 11C 10Misc 24Journal 104Unranked 24

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Regularized Actor-Critic Algorithm for Bi-Level Reinforcement Learning. CoRR Sihan Zeng, Sujay Bhatt, Sumitra Ganesh, Alec Koppel
2026	J	`jnl`	No One Size Fits All: QueryBandits for Hallucination Mitigation. CoRR Nicole Cho, William Watson, Alec Koppel, Sumitra Ganesh, Manuela Veloso
2025	A	`conf`	Approximate Equivariance in Reinforcement Learning. AISTATS Jung Yeon Park, Sujay Bhatt, Sihan Zeng, Lawson L. S. Wong, Alec Koppel, Sumitra Ganesh, Robin Walters
2025	—	`conf`	Automatically Stopping Bayesian Optimization under Uncertain Surrogate Model Means. CDC Hans J. He, Alec Koppel, Amrit Singh Bedi, Mazen Farhood, Daniel J. Stilwell
2025	J	`jnl`	Beyond Joint Demonstrations: Personalized Expert Guidance for Efficient Multi-Agent Reinforcement Learning. Trans. Mach. Learn. Res. Peihong Yu, Manav Mishra, Alec Koppel, Carl E. Busart, Priya Narayan, Dinesh Manocha, Amrit Singh Bedi, Pratap Tokekar
2025	A*	`conf`	Collab: Controlled Decoding using Mixture of Agents for LLM Alignment. ICLR Souradip Chakraborty, Sujay Bhatt, Udari Madhushani Sehwag, Soumya Suvra Ghosal, Jiahao Qiu, Mengdi Wang, Dinesh Manocha, Furong Huang, Alec Koppel, Sumitra Ganesh
2025	J	`jnl`	Collab: Controlled Decoding using Mixture of Agents for LLM Alignment. CoRR Souradip Chakraborty, Sujay Bhatt, Udari Madhushani Sehwag, Soumya Suvra Ghosal, Jiahao Qiu, Mengdi Wang, Dinesh Manocha, Furong Huang, Alec Koppel, Sumitra Ganesh
2025	A	`conf`	Confidence-Controlled Exploration: Efficient Sparse-Reward Policy Learning for Robot Navigation. IROS Bhrij Patel, Kasun Weerakoon, Wesley A. Suttle, Alec Koppel, Brian M. Sadler, Tianyi Zhou, Dinesh Manocha, Amrit Singh Bedi
2025	A*	`conf`	Decentralized Convergence to Equilibrium Prices in Trading Networks. AAAI Edwin Lock, Benjamin Patrick Evans, Eleonora Kreacic, Sujay Bhatt, Alec Koppel, Sumitra Ganesh, Paul W. Goldberg
2025	J	`jnl`	Decentralized Upper Confidence Bound Algorithms for Homogeneous Multi-agent Multi-armed Bandits. IEEE Trans. Autom. Control. Jingxuan Zhu, Ethan Mulle, Christopher Salomon Smith, Alec Koppel, Ji Liu
2025	J	`jnl`	Efficient Inverse Multiagent Learning. CoRR Denizalp Goktas, Amy Greenwald, Sadie Zhao, Alec Koppel, Sumitra Ganesh
2025	A*	`conf`	GenARM: Reward Guided Generation with Autoregressive Reward Model for Test-Time Alignment. ICLR Yuancheng Xu, Udari Madhushani Sehwag, Alec Koppel, Sicheng Zhu, Bang An, Furong Huang, Sumitra Ganesh
2025	A	`conf`	Learning in Herding Mean Field Games: Single-Loop Algorithm with Finite-Time Convergence Analysis. AISTATS Sihan Zeng, Sujay Bhatt, Alec Koppel, Sumitra Ganesh
2025	J	`jnl`	Learning in Stackelberg Mean Field Games: A Non-Asymptotic Analysis. CoRR Sihan Zeng, Benjamin Patrick Evans, Sujay Bhatt, Leo Ardon, Sumitra Ganesh, Alec Koppel
2025	Misc	`conf`	Partially Observable Contextual Bandits With Linear Payoffs. ICASSP Sihan Zeng, Sujay Bhatt, Alec Koppel, Sumitra Ganesh
2025	J	`jnl`	QueryBandits for Hallucination Mitigation: Exploiting Semantic Features for No-Regret Rewriting. CoRR Nicole Cho, William Watson, Alec Koppel, Sumitra Ganesh, Manuela Veloso
2025	J	`jnl`	Regret and Belief Complexity Tradeoff in Gaussian Process Bandits via Information Thresholding. IEEE Trans. Artif. Intell. Amrit Singh Bedi, Dheeraj Peddireddy, Vaneet Aggarwal, Brian M. Sadler, Alec Koppel
2025	J	`jnl`	Regularized Proportional Fairness Mechanism for Resource Allocation Without Money. CoRR Sihan Zeng, Sujay Bhatt, Alec Koppel, Sumitra Ganesh
2024	J	`jnl`	Approximate Equivariance in Reinforcement Learning. CoRR Jung Yeon Park, Sujay Bhatt, Sihan Zeng, Lawson L. S. Wong, Alec Koppel, Sumitra Ganesh, Robin Walters
2024	J	`jnl`	Beyond Joint Demonstrations: Personalized Expert Guidance for Efficient Multi-Agent Reinforcement Learning. CoRR Peihong Yu, Manav Mishra, Alec Koppel, Carl E. Busart, Priya Narayan, Dinesh Manocha, Amrit S. Bedi, Pratap Tokekar
2024	—	`conf`	Bimodal Bandits: Max-Mean Regret Minimization. IEEECONF Adit Jain, Sujay Bhatt, Vikram Krishnamurthy, Alec Koppel
2024	J	`jnl`	Byzantine-Resilient Decentralized Multi-Armed Bandits. Trans. Mach. Learn. Res. Jingxuan Zhu, Alec Koppel, Alvaro Velasquez, Ji Liu
2024	J	`jnl`	Compressed Online Learning of Conditional Mean Embedding. CoRR Boya Hou, Sina Sanjari, Alec Koppel, Subhonmesh Bose
2024	J	`jnl`	Decentralized Convergence to Equilibrium Prices in Trading Networks. CoRR Edwin Lock, Benjamin Patrick Evans, Eleonora Kreacic, Sujay Bhatt, Alec Koppel, Sumitra Ganesh, Paul W. Goldberg
2024	A*	`conf`	Efficient Inverse Multiagent Learning. ICLR Denizalp Goktas, Amy Greenwald, Sadie Zhao, Alec Koppel, Sumitra Ganesh
2024	J	`jnl`	GenARM: Reward Guided Generation with Autoregressive Reward Model for Test-time Alignment. CoRR Yuancheng Xu, Udari Madhushani Sehwag, Alec Koppel, Sicheng Zhu, Bang An, Furong Huang, Sumitra Ganesh
2024	J	`jnl`	Global Optimality without Mixing Time Oracles in Average-reward RL via Multi-level Actor-Critic. CoRR Bhrij Patel, Wesley A. Suttle, Alec Koppel, Vaneet Aggarwal, Brian M. Sadler, Amrit Singh Bedi, Dinesh Manocha
2024	J	`jnl`	Independent RL for Cooperative-Competitive Agents: A Mean-Field Perspective. CoRR Muhammad Aneeq uz Zaman, Alec Koppel, Mathieu Laurière, Tamer Basar
2024	A*	`conf`	Information-Directed Pessimism for Offline Reinforcement Learning. ICML Alec Koppel, Sujay Bhatt, Jiacheng Guo, Joe Eappen, Mengdi Wang, Sumitra Ganesh
2024	Misc	`conf`	Learning Payment-Free Resource Allocation Mechanisms. WSC Sihan Zeng, Sujay Bhatt, Eleonora Kreacic, Parisa Hassanzadeh, Alec Koppel, Sumitra Ganesh
2024	A*	`conf`	MaxMin-RLHF: Alignment with Diverse Human Preferences. ICML Souradip Chakraborty, Jiahao Qiu, Hui Yuan, Alec Koppel, Dinesh Manocha, Furong Huang, Amrit S. Bedi, Mengdi Wang
2024	J	`jnl`	MaxMin-RLHF: Towards Equitable Alignment of Large Language Models with Diverse Human Preferences. CoRR Souradip Chakraborty, Jiahao Qiu, Hui Yuan, Alec Koppel, Furong Huang, Dinesh Manocha, Amrit Singh Bedi, Mengdi Wang
2024	—	`conf`	Multi-layer Default Risk Contagion in Inter-banking Networks. CDC Xiaoqi Bi, Alec Koppel, Carolyn L. Beck
2024	J	`jnl`	Occupancy Information Ratio: Infinite-Horizon, Information-Directed, Parameterized Policy Search. SIAM J. Control. Optim. Wesley A. Suttle, Alec Koppel, Ji Liu
2024	J	`jnl`	On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control. J. Mach. Learn. Res. Amrit Singh Bedi, Anjaly Parayil, Junyu Zhang, Mengdi Wang, Alec Koppel
2024	J	`jnl`	Online MCMC Thinning with Kernelized Stein Discrepancy. SIAM J. Math. Data Sci. Alec Koppel, Joe Eappen, Sujay Bhatt, Cole Hawkins, Sumitra Ganesh
2024	A*	`conf`	PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback. ICLR Souradip Chakraborty, Amrit Singh Bedi, Alec Koppel, Huazheng Wang, Dinesh Manocha, Mengdi Wang, Furong Huang
2024	J	`jnl`	Partially Observable Contextual Bandits with Linear Payoffs. CoRR Sihan Zeng, Sujay Bhatt, Alec Koppel, Sumitra Ganesh
2024	J	`jnl`	Regularized Proportional Fairness Mechanism for Resource Allocation Without Money. Trans. Mach. Learn. Res. Sihan Zeng, Sujay Bhatt, Alec Koppel, Sumitra Ganesh
2024	J	`jnl`	Robust Cooperative Multi-Agent Reinforcement Learning:A Mean-Field Type Game Perspective. CoRR Muhammad Aneeq uz Zaman, Mathieu Laurière, Alec Koppel, Tamer Basar
2024	—	`conf`	Robust cooperative multi-agent reinforcement learning: A mean-field type game perspective. L4DC Muhammad Aneeq uz Zaman, Mathieu Laurière, Alec Koppel, Tamer Basar
2024	J	`jnl`	SAIL: Self-Improving Efficient Online Alignment of Large Language Models. CoRR Mucong Ding, Souradip Chakraborty, Vibhu Agrawal, Zora Che, Alec Koppel, Mengdi Wang, Amrit S. Bedi, Furong Huang
2024	A	`conf`	Sharpened Lazy Incremental Quasi-Newton Method. AISTATS Aakash Sunil Lahoti, Spandan Senapati, Ketan Rajawat, Alec Koppel
2024	A*	`conf`	Towards Global Optimality for Practical Average Reward Reinforcement Learning without Mixing Time Oracles. ICML Bhrij Patel, Wesley A. Suttle, Alec Koppel, Vaneet Aggarwal, Brian M. Sadler, Dinesh Manocha, Amrit S. Bedi
2023	J	`jnl`	A Gradient-based Approach for Online Robust Deep Neural Network Training with Noisy Labels. CoRR Yifan Yang, Alec Koppel, Zheng Zhang
2023	J	`jnl`	Ada-NAV: Adaptive Trajectory-Based Sample Efficient Policy Learning for Robotic Navigation. CoRR Bhrij Patel, Kasun Weerakoon, Wesley A. Suttle, Alec Koppel, Brian M. Sadler, Amrit Singh Bedi, Dinesh Manocha
2023	J	`jnl`	Aligning Agent Policy with Externalities: Reward Design via Bilevel RL. CoRR Souradip Chakraborty, Amrit Singh Bedi, Alec Koppel, Dinesh Manocha, Huazheng Wang, Furong Huang, Mengdi Wang
2023	A*	`conf`	Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic. ICML Wesley A. Suttle, Amrit S. Bedi, Bhrij Patel, Brian M. Sadler, Alec Koppel, Dinesh Manocha
2023	J	`jnl`	Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic. CoRR Wesley A. Suttle, Amrit Singh Bedi, Bhrij Patel, Brian M. Sadler, Alec Koppel, Dinesh Manocha
2023	—	`conf`	Bi-Level Nonstationary Kernels for Online Gaussian Process Regression. CASE Hans He, Alec Koppel, Amrit Singh Bedi, Mazen Farhood, Daniel J. Stilwell
2023	J	`jnl`	Byzantine-Resilient Decentralized Multi-Armed Bandits. CoRR Jingxuan Zhu, Alec Koppel, Alvaro Velasquez, Ji Liu
2023	A*	`conf`	Dealing with Sparse Rewards in Continuous Control Robotics via Heavy-Tailed Policy Optimization. ICRA Souradip Chakraborty, Amrit Singh Bedi, Kasun Weerakoon, Prithvi Poddar, Alec Koppel, Pratap Tokekar, Dinesh Manocha
2023	A*	`conf`	Decentralized Multi-agent Exploration with Limited Inter-agent Communications. ICRA Hans He, Alec Koppel, Amrit Singh Bedi, Daniel J. Stilwell, Mazen Farhood, Benjamin Biggs
2023	Misc	`conf`	Information-Directed Policy Search in Sparse-Reward Settings via the Occupancy Information Ratio. CISS Wesley A. Suttle, Alec Koppel, Ji Liu
2023	J	`jnl`	Limited-Memory Greedy Quasi-Newton Method with Non-asymptotic Superlinear Convergence Rate. CoRR Zhan Gao, Aryan Mokhtari, Alec Koppel
2023	J	`jnl`	Near-Optimal Fair Resource Allocation for Strategic Agents without Money: A Data-Driven Approach. CoRR Sihan Zeng, Sujay Bhatt, Eleonora Kreacic, Parisa Hassanzadeh, Alec Koppel, Sumitra Ganesh
2023	J	`jnl`	On the sample complexity of actor-critic method for reinforcement learning with function approximation. Mach. Learn. Harshat Kumar, Alec Koppel, Alejandro Ribeiro
2023	A	`conf`	Oracle-free Reinforcement Learning in Mean-Field Games along a Single Sample Path. AISTATS Muhammad Aneeq uz Zaman, Alec Koppel, Sujay Bhatt, Tamer Basar
2023	A*	`conf`	Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning. AAAI Souradip Chakraborty, Amrit Singh Bedi, Pratap Tokekar, Alec Koppel, Brian M. Sadler, Furong Huang, Dinesh Manocha
2023	A*	`conf`	STEERING : Stein Information Directed Exploration for Model-Based Reinforcement Learning. ICML Souradip Chakraborty, Amrit S. Bedi, Alec Koppel, Mengdi Wang, Furong Huang, Dinesh Manocha
2023	J	`jnl`	STEERING: Stein Information Directed Exploration for Model-Based Reinforcement Learning. CoRR Souradip Chakraborty, Amrit Singh Bedi, Alec Koppel, Mengdi Wang, Furong Huang, Dinesh Manocha
2023	C	`conf`	Scalable Multi-Agent Reinforcement Learning with General Utilities. ACC Donghao Ying, Yuhao Ding, Alec Koppel, Javad Lavaei
2023	J	`jnl`	Scalable Multi-Agent Reinforcement Learning with General Utilities. CoRR Donghao Ying, Yuhao Ding, Alec Koppel, Javad Lavaei
2023	A*	`conf`	Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities. NeurIPS Donghao Ying, Yunkai Zhang, Yuhao Ding, Alec Koppel, Javad Lavaei
2023	J	`jnl`	Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities. CoRR Donghao Ying, Yunkai Zhang, Yuhao Ding, Alec Koppel, Javad Lavaei
2023	J	`jnl`	Sharpened Lazy Incremental Quasi-Newton Method. CoRR Aakash Lahoti, Spandan Senapati, Ketan Rajawat, Alec Koppel
2022	A*	`conf`	Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach. AAAI Qinbo Bai, Amrit Singh Bedi, Mridul Agarwal, Alec Koppel, Vaneet Aggarwal
2022	J	`jnl`	Balancing Rates and Variance via Adaptive Batch-Size for Stochastic Optimization Problems. IEEE Trans. Signal Process. Zhan Gao, Alec Koppel, Alejandro Ribeiro
2022	J	`jnl`	Collaborative one-shot beamforming under localization errors: A discrete optimization approach. Signal Process. Yagiz Savas, Erfaun Noorani, Alec Koppel, John S. Baras, Ufuk Topcu, Brian M. Sadler
2022	—	`conf`	Convergence Rates of Average-Reward Multi-agent Reinforcement Learning via Randomized Linear Programming. CDC Alec Koppel, Amrit Singh Bedi, Bhargav Ganguly, Vaneet Aggarwal
2022	J	`jnl`	Dealing with Sparse Rewards in Continuous Control Robotics via Heavy-Tailed Policies. CoRR Souradip Chakraborty, Amrit Singh Bedi, Alec Koppel, Pratap Tokekar, Dinesh Manocha
2022	J	`jnl`	Dense Incremental Metric-Semantic Mapping for Multiagent Systems via Sparse Gaussian Process Regression. IEEE Trans. Robotics Ehsan Zobeidi, Alec Koppel, Nikolay Atanasov
2022	C	`conf`	Distributed Gaussian Process Mapping for Robot Teams with Time-varying Communication. ACC James Di, Ehsan Zobeidi, Alec Koppel, Nikolay Atanasov
2022	A	`conf`	Distributed Riemannian Optimization with Lazy Communication for Collaborative Geometric Estimation. IROS Yulun Tian, Amrit Singh Bedi, Alec Koppel, Miguel Calvo-Fullana, David M. Rosen, Jonathan P. How
2022	J	`jnl`	Distributed Riemannian Optimization with Lazy Communication for Collaborative Geometric Estimation. CoRR Yulun Tian, Amrit Singh Bedi, Alec Koppel, Miguel Calvo-Fullana, David M. Rosen, Jonathan P. How
2022	J	`jnl`	Escaping Saddle Points for Successive Convex Approximation. IEEE Trans. Signal Process. Amrit Singh Bedi, Ketan Rajawat, Vaneet Aggarwal, Alec Koppel
2022	J	`jnl`	FedBC: Calibrating Global and Local Models via Federated Learning Beyond Consensus. CoRR Amrit Singh Bedi, Chen Fan, Alec Koppel, Anit Kumar Sahu, Brian M. Sadler, Furong Huang, Dinesh Manocha
2022	A*	`conf`	Multi-Agent Reinforcement Learning with General Utilities via Decentralized Shadow Reward Actor-Critic. AAAI Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel
2022	J	`jnl`	Occupancy Information Ratio: Infinite-Horizon, Information-Directed, Parameterized Policy Search. CoRR Wesley A. Suttle, Alec Koppel, Ji Liu
2022	Misc	`conf`	On Submodular Set Cover Problems for Near-Optimal Online Kernel Basis Selection. ICASSP Hrusikesha Pradhan, Alec Koppel, Ketan Rajawat
2022	A*	`conf`	On the Hidden Biases of Policy Mirror Ascent in Continuous Action Spaces. ICML Amrit Singh Bedi, Souradip Chakraborty, Anjaly Parayil, Brian M. Sadler, Pratap Tokekar, Alec Koppel
2022	J	`jnl`	On the Hidden Biases of Policy Mirror Ascent in Continuous Action Spaces. CoRR Amrit Singh Bedi, Souradip Chakraborty, Anjaly Parayil, Brian M. Sadler, Pratap Tokekar, Alec Koppel
2022	J	`jnl`	Online, Informative MCMC Thinning with Kernelized Stein Discrepancy. CoRR Cole Hawkins, Alec Koppel, Zheng Zhang
2022	J	`jnl`	Oracle-free Reinforcement Learning in Mean-Field Games along a Single Sample Path. CoRR Muhammad Aneeq uz Zaman, Alec Koppel, Sujay Bhatt, Tamer Basar
2022	Misc	`conf`	Policy Gradient for Ratio Optimization: A Case Study. CISS Wesley A. Suttle, Alec Koppel, Ji Liu
2022	J	`jnl`	Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning. CoRR Souradip Chakraborty, Amrit Singh Bedi, Alec Koppel, Brian M. Sadler, Furong Huang, Pratap Tokekar, Dinesh Manocha
2022	A*	`conf`	Sharpened Quasi-Newton Methods: Faster Superlinear Rate and Larger Local Convergence Neighborhood. ICML Qiujiang Jin, Alec Koppel, Ketan Rajawat, Aryan Mokhtari
2022	J	`jnl`	Sparse Representations of Positive Functions via First- and Second-Order Pseudo-Mirror Descent. IEEE Trans. Signal Process. Abhishek Chakraborty, Ketan Rajawat, Alec Koppel
2021	Misc	`conf`	A Dynamical Systems Perspective on Online Bayesian Nonparametric Estimators with Adaptive Hyperparameters. ICASSP Alec Koppel, Amrit S. Bedi, Vikram Krishnamurthy
2021	J	`jnl`	Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach. CoRR Qinbo Bai, Amrit Singh Bedi, Mridul Agarwal, Alec Koppel, Vaneet Aggarwal
2021	J	`jnl`	Adaptive Kernel Learning in Heterogeneous Networks. IEEE Trans. Signal Inf. Process. over Networks Hrusikesha Pradhan, Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
2021	C	`conf`	Beyond Cumulative Returns via Reinforcement Learning over State-Action Occupancy Measures. ACC Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel
2021	J	`jnl`	Cautious Reinforcement Learning via Distributional Risk in the Dual Domain. IEEE J. Sel. Areas Inf. Theory Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel
2021	—	`conf`	Collaborative Beamforming for Agents with Localization Errors. ACSCC Erfaun Noorani, Yagiz Savas, Alec Koppel, John S. Baras, Ufuk Topcu, Brian M. Sadler
2021	J	`jnl`	Composable Learning with Sparse Kernel Representations. CoRR Ekaterina I. Tolstaya, Ethan Stump, Alec Koppel, Alejandro Ribeiro
2021	J	`jnl`	Consistent online Gaussian process regression without the sample complexity bottleneck. Stat. Comput. Alec Koppel, Hrusikesha Pradhan, Ketan Rajawat
2021	J	`jnl`	Dense Incremental Metric-Semantic Mapping for Multi-Agent Systems via Sparse Gaussian Process Regression. CoRR Ehsan Zobeidi, Alec Koppel, Nikolay Atanasov
2021	J	`jnl`	Distributed Gaussian Process Mapping for Robot Teams with Time-varying Communication. CoRR James Di, Ehsan Zobeidi, Alec Koppel, Nikolay Atanasov
2021	J	`jnl`	Dynamic Online Learning via Frank-Wolfe Algorithm. IEEE Trans. Signal Process. Deepak S. Kalhan, Amrit Singh Bedi, Alec Koppel, Ketan Rajawat, Hamed Hassani, Abhishek K. Gupta, Adrish Banerjee
2021	—	`conf`	Intermittent Communications in Decentralized Shadow Reward Actor-Critic. CDC Amrit Singh Bedi, Alec Koppel, Mengdi Wang, Junyu Zhang
2021	C	`conf`	Joint Position and Beamforming Control via Alternating Nonlinear Least-Squares with a Hierarchical Gamma Prior. ACC Anjaly Parayil, Amrit Singh Bedi, Alec Koppel
2021	J	`jnl`	MARL with General Utilities via Decentralized Shadow Reward Actor-Critic. CoRR Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel
2021	J	`jnl`	Nearly Consistent Finite Particle Estimates in Streaming Importance Sampling. IEEE Trans. Signal Process. Alec Koppel, Amrit Singh Bedi, Brian M. Sadler, Víctor Elvira
2021	J	`jnl`	Nonparametric Compositional Stochastic Optimization for Risk-Sensitive Kernel Learning. IEEE Trans. Signal Process. Amrit Singh Bedi, Alec Koppel, Ketan Rajawat, Panchajanya Sanyal
2021	J	`jnl`	On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control. CoRR Amrit Singh Bedi, Anjaly Parayil, Junyu Zhang, Mengdi Wang, Alec Koppel
2021	J	`jnl`	Policy Evaluation in Continuous MDPs With Efficient Kernelized Gradient Temporal Difference. IEEE Trans. Autom. Control. Alec Koppel, Garrett Warnell, Ethan Stump, Peter Stone, Alejandro Ribeiro
2021	—	`conf`	Projected Pseudo-Mirror Descent in Reproducing Kernel Hilbert Space. ACSCC Abhishek Chakraborty, Ketan Rajawat, Alec Koppel
2021	—	`conf`	Randomized Linear Programming for Tabular Average-Cost Multi-agent Reinforcement Learning. ACSCC Alec Koppel, Amrit Singh Bedi, Bhargav Ganguly, Vaneet Aggarwal
2021	—	`conf`	Semiparametric Information State Embedding for Policy Search under Imperfect Information. CDC Sujay Bhatt, Weichao Mao, Alec Koppel, Tamer Basar
2021	A	`conf`	Wasserstein-Splitting Gaussian Process Regression for Heterogeneous Online Bayesian Inference. IROS Michael E. Kepler, Alec Koppel, Amrit Singh Bedi, Daniel J. Stilwell
2021	J	`jnl`	Wasserstein-Splitting Gaussian Process Regression for Heterogeneous Online Bayesian Inference. CoRR Michael E. Kepler, Alec Koppel, Amrit Singh Bedi, Daniel J. Stilwell
2020	J	`jnl`	A Class of Parallel Doubly Stochastic Algorithms for Large-Scale Learning. J. Mach. Learn. Res. Aryan Mokhtari, Alec Koppel, Martin Takác, Alejandro Ribeiro
2020	J	`jnl`	A Markov Decision Process Approach to Active Meta Learning. CoRR Bingjia Wang, Alec Koppel, Vikram Krishnamurthy
2020	J	`jnl`	Asynchronous and Parallel Distributed Pose Graph Optimization. CoRR Yulun Tian, Alec Koppel, Amrit Singh Bedi, Jonathan P. How
2020	J	`jnl`	Asynchronous and Parallel Distributed Pose Graph Optimization. IEEE Robotics Autom. Lett. Yulun Tian, Alec Koppel, Amrit Singh Bedi, Jonathan P. How
2020	J	`jnl`	Balancing Rates and Variance via Adaptive Batch-Size for Stochastic Optimization Problems. CoRR Zhan Gao, Alec Koppel, Alejandro Ribeiro
2020	Misc	`conf`	Balancing Rates and Variance via Adaptive Batch-Sizes in First-Order Stochastic Optimization. ICASSP Zhan Gao, Alec Koppel, Alejandro Ribeiro
2020	J	`jnl`	Cautious Reinforcement Learning via Distributional Risk in the Dual Domain. CoRR Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel
2020	Misc	`conf`	Conservative Multi-agent Online Kernel Learning in Heterogeneous Networks. ACSSC Hrusikesha Pradhan, Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
2020	J	`jnl`	Consistent Online Gaussian Process Regression Without the Sample Complexity Bottleneck. CoRR Alec Koppel, Hrusikesha Pradhan, Ketan Rajawat
2020	A	`conf`	Dense Incremental Metric-Semantic Mapping via Sparse Gaussian Process Regression. IROS Ehsan Zobeidi, Alec Koppel, Nikolay Atanasov
2020	J	`jnl`	Distributed Beamforming for Agents with Localization Errors. CoRR Erfaun Noorani, Yagiz Savas, Alec Koppel, John S. Baras, Ufuk Topcu, Brian M. Sadler
2020	J	`jnl`	Efficient Gaussian Process Bandits by Believing only Informative Actions. CoRR Amrit Singh Bedi, Dheeraj Peddireddy, Vaneet Aggarwal, Alec Koppel
2020	—	`conf`	Efficient Large-Scale Gaussian Process Bandits by Believing only Informative Actions. L4DC Amrit Singh Bedi, Dheeraj Peddireddy, Vaneet Aggarwal, Alec Koppel
2020	J	`jnl`	Global Convergence of Policy Gradient Methods to (Almost) Locally Optimal Policies. SIAM J. Control. Optim. Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Basar
2020	J	`jnl`	High-Dimensional Nonconvex Stochastic Optimization by Doubly Stochastic Successive Convex Approximation. IEEE Trans. Signal Process. Aryan Mokhtari, Alec Koppel
2020	J	`jnl`	Optimally Compressed Nonparametric Online Learning: Tradeoffs between memory and consistency. IEEE Signal Process. Mag. Alec Koppel, Amrit Singh Bedi, Ketan Rajawat, Brian M. Sadler
2020	J	`jnl`	Policy Gradient using Weak Derivatives for Reinforcement Learning. CoRR Sujay Bhatt, Alec Koppel, Vikram Krishnamurthy
2020	Misc	`conf`	Projection Free Dynamic Online Learning. ICASSP Deepak S. Kalhan, Amrit S. Bedi, Alec Koppel, Ketan Rajawat, Abhishek K. Gupta, Adrish Banerjee
2020	Misc	`conf`	Reduced-rank Least Squares Parameter Estimation in the Presence of Byzantine Sensors. CISS Nagananda K. G, Rick S. Blum, Alec Koppel
2020	J	`jnl`	Sparse Representations of Positive Functions via Projected Pseudo-Mirror Descent. CoRR Abhishek Chakraborty, Ketan Rajawat, Alec Koppel
2020	C	`conf`	Trading Dynamic Regret for Model Complexity in Nonstationary Nonparametric Optimization. ACC Amrit Singh Bedi, Alec Koppel, Ketan Rajawat, Brian M. Sadler
2020	A*	`conf`	Variational Policy Gradient Method for Reinforcement Learning with General Utilities. NeurIPS Junyu Zhang, Alec Koppel, Amrit Singh Bedi, Csaba Szepesvári, Mengdi Wang
2020	J	`jnl`	Variational Policy Gradient Method for Reinforcement Learning with General Utilities. CoRR Junyu Zhang, Alec Koppel, Amrit Singh Bedi, Csaba Szepesvári, Mengdi Wang
2019	J	`jnl`	Approximate Shannon Sampling in Importance Sampling: Nearly Consistent Finite Particle Estimates. CoRR Alec Koppel, Amrit Singh Bedi, Victor Elvira, Brian M. Sadler
2019	J	`jnl`	Asynchronous Online Learning in Multi-Agent Systems With Proximity Constraints. IEEE Trans. Signal Inf. Process. over Networks Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
2019	J	`jnl`	Asynchronous Saddle Point Algorithm for Stochastic Optimization in Heterogeneous Networks. IEEE Trans. Signal Process. Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
2019	Misc	`conf`	Compressed Streaming Importance Sampling for Efficient Representations of Localization Distributions. ACSSC Amrit Singh Bedi, Alec Koppel, Brian M. Sadler, Víctor Elvira
2019	C	`conf`	Consistent Online Gaussian Process Regression Without the Sample Complexity Bottleneck. ACC Alec Koppel
2019	C	`conf`	Controlling the Bias-Variance Tradeoff via Coherent Risk for Robust Learning with Kernels. ACC Alec Koppel, Amrit S. Bedi, Ketan Rajawat
2019	—	`conf`	Convergence and Iteration Complexity of Policy Gradient Method for Infinite-horizon Reinforcement Learning. CDC Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Basar
2019	—	`conf`	Distributed Online Learning over Time-varying Graphs via Proximal Gradient Descent. CDC Rishabh Dixit, Amrit Singh Bedi, Ketan Rajawat, Alec Koppel
2019	J	`jnl`	Global Convergence of Policy Gradient Methods to (Almost) Locally Optimal Policies. CoRR Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Basar
2019	J	`jnl`	Nonstationary Nonparametric Online Learning: Balancing Dynamic Regret and Model Parsimony. CoRR Amrit Singh Bedi, Alec Koppel, Ketan Rajawat, Brian M. Sadler
2019	J	`jnl`	On the Sample Complexity of Actor-Critic Method for Reinforcement Learning with Function Approximation. CoRR Harshat Kumar, Alec Koppel, Alejandro Ribeiro
2019	J	`jnl`	Optimally Compressed Nonparametric Online Learning. CoRR Alec Koppel, Amrit Singh Bedi, Ketan Rajawat, Brian M. Sadler
2019	J	`jnl`	Parsimonious Online Learning with Kernels via Sparse Projections in Function Space. J. Mach. Learn. Res. Alec Koppel, Garrett Warnell, Ethan Stump, Alejandro Ribeiro
2019	—	`conf`	Policy Gradient using Weak Derivatives for Reinforcement Learning. CDC Sujay Bhatt, Alec Koppel, Vikram Krishnamurthy
2019	Misc	`conf`	Policy Gradient using Weak Derivatives for Reinforcement Learning. CISS Sujay Bhatt, Alec Koppel, Vikram Krishnamurthy
2019	Misc	`conf`	Policy Search in Infinite-Horizon Discounted Reinforcement Learning: Advances through Connections to Non-Convex Optimization : Invited Presentation. CISS Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Basar
2019	J	`jnl`	Projected Stochastic Primal-Dual Method for Constrained Online Learning With Kernels. IEEE Trans. Signal Process. Alec Koppel, Kaiqing Zhang, Hao Zhu, Tamer Basar
2018	—	`conf`	Asynchronous Saddle Point Method: Interference Management Through Pricing. CDC Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
2018	A	`conf`	Composable Learning with Sparse Kernel Representations. IROS Ekaterina I. Tolstaya, Ethan Stump, Alec Koppel, Alejandro Ribeiro
2018	J	`jnl`	Decentralized Online Learning With Kernels. IEEE Trans. Signal Process. Alec Koppel, Santiago Paternain, Cédric Richard, Alejandro Ribeiro
2018	Misc	`conf`	Decentralized Online Nonparametric Learning. ACSSC Alec Koppel, Santiago Paternain, Cédric Richard, Alejandro Ribeiro
2018	—	`conf`	Exact Nonparametric Decentralized Online Optimization. GlobalSIP Hrusikesha Pradhan, Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
2018	C	`conf`	Nonparametric Stochastic Compositional Gradient Descent for Q-Learning in Continuous Markov Decision Problems. ACC Ekaterina I. Tolstaya, Alec Koppel, Ethan Stump, Alejandro Ribeiro
2018	J	`jnl`	Nonparametric Stochastic Compositional Gradient Descent for Q-Learning in Continuous Markov Decision Problems. CoRR Alec Koppel, Ekaterina I. Tolstaya, Ethan Stump, Alejandro Ribeiro
2018	—	`conf`	On Stream-Centric Learning for Internet of Battlefield Things. AAAI Spring Symposia Brian Jalaian, Alec Koppel, Andre Harrison, James Michaelis, Stephen Russell
2018	Misc	`conf`	Parallel Stochastic Successive Convex Approximation Method for Large-Scale Dictionary Learning. ICASSP Alec Koppel, Aryan Mokhtari, Alejandro Ribeiro
2018	—	`conf`	Projected Stochastic Primal-Dual Method for Constrained Online Learning with Kernels. CDC Kaiqing Zhang, Hao Zhu, Tamer Basar, Alec Koppel
2017	C	`conf`	A variational approach to dual methods for constrained convex optimization. ACC Mahyar Fazlyab, Alec Koppel, Victor M. Preciado, Alejandro Ribeiro
2017	Misc	`conf`	Beyond consensus and synchrony in decentralized online optimization using saddle point method. ACSSC Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
2017	J	`jnl`	D4L: Decentralized Dynamic Discriminative Dictionary Learning. IEEE Trans. Signal Inf. Process. over Networks Alec Koppel, Garrett Warnell, Ethan Stump, Alejandro Ribeiro
2017	J	`jnl`	Decentralized Online Learning with Kernels. CoRR Alec Koppel, Santiago Paternain, Cédric Richard, Alejandro Ribeiro
2017	J	`jnl`	Decentralized Prediction-Correction Methods for Networked Time-Varying Convex Optimization. IEEE Trans. Autom. Control. Andrea Simonetto, Alec Koppel, Aryan Mokhtari, Geert Leus, Alejandro Ribeiro
2017	—	`conf`	Decentralized efficient nonparametric stochastic optimization. GlobalSIP Alec Koppel, Santiago Paternain, Cédric Richard, Alejandro Ribeiro
2017	Misc	`conf`	Large-scale nonconvex stochastic optimization by Doubly Stochastic Successive Convex approximation. ICASSP Aryan Mokhtari, Alec Koppel, Gesualdo Scutari, Alejandro Ribeiro
2017	Misc	`conf`	Parsimonious Online Learning with Kernels via sparse projections in function space. ICASSP Alec Koppel, Garrett Warnell, Ethan Stump, Alejandro Ribeiro
2017	J	`jnl`	Proximity Without Consensus in Online Multiagent Optimization. IEEE Trans. Signal Process. Alec Koppel, Brian M. Sadler, Alejandro Ribeiro
2016	J	`jnl`	A Class of Parallel Doubly Stochastic Algorithms for Large-Scale Learning. CoRR Aryan Mokhtari, Alec Koppel, Alejandro Ribeiro
2016	J	`jnl`	A Class of Prediction-Correction Methods for Time-Varying Convex Optimization. IEEE Trans. Signal Process. Andrea Simonetto, Aryan Mokhtari, Alec Koppel, Geert Leus, Alejandro Ribeiro
2016	—	`conf`	A Quasi-newton prediction-correction method for decentralized dynamic convex optimization. ECC Andrea Simonetto, Alec Koppel, Aryan Mokhtari, Geert Leus, Alejandro Ribeiro
2016	J	`jnl`	Decentralized Dynamic Discriminative Dictionary Learning. CoRR Alec Koppel, Garrett Warnell, Ethan Stump, Alejandro Ribeiro
2016	J	`jnl`	Decentralized Prediction-Correction Methods for Networked Time-Varying Convex Optimization. CoRR Andrea Simonetto, Alec Koppel, Aryan Mokhtari, Geert Leus, Alejandro Ribeiro
2016	—	`conf`	Decentralized online optimization with heterogeneous data sources. GlobalSIP Alec Koppel, Brian M. Sadler, Alejandro Ribeiro
2016	J	`jnl`	Doubly Random Parallel Stochastic Methods for Large Scale Learning. CoRR Aryan Mokhtari, Alec Koppel, Alejandro Ribeiro
2016	C	`conf`	Doubly random parallel stochastic methods for large scale learning. ACC Aryan Mokhtari, Alec Koppel, Alejandro Ribeiro
2016	Misc	`conf`	Doubly stochastic algorithms for large-scale optimization. ACSSC Alec Koppel, Aryan Mokhtari, Alejandro Ribeiro
2016	A	`conf`	Online learning for characterizing unknown environments in ground robotic vehicle models. IROS Alec Koppel, Jonathan Fink, Garrett Warnell, Ethan Stump, Alejandro Ribeiro
2016	J	`jnl`	Parsimonious Online Learning with Kernels via Sparse Projections in Function Space. CoRR Alec Koppel, Garrett Warnell, Ethan Stump, Alejandro Ribeiro
2016	J	`jnl`	Proximity Without Consensus in Online Multi-Agent Optimization. CoRR Alec Koppel, Brian M. Sadler, Alejandro Ribeiro
2016	Misc	`conf`	Proximity without consensus in online multi-agent optimization. ICASSP Alec Koppel, Brian M. Sadler, Alejandro Ribeiro
2015	J	`jnl`	A Class of Prediction-Correction Methods for Time-Varying Convex Optimization. CoRR Andrea Simonetto, Aryan Mokhtari, Alec Koppel, Geert Leus, Alejandro Ribeiro
2015	J	`jnl`	A Saddle Point Algorithm for Networked Online Convex Optimization. IEEE Trans. Signal Process. Alec Koppel, Felicia Y. Jakubiec, Alejandro Ribeiro
2015	—	`conf`	A decentralized prediction-correction method for networked time-varying convex optimization. CAMSAP Andrea Simonetto, Aryan Mokhtari, Alec Koppel, Geert Leus, Alejandro Ribeiro
2015	A	`conf`	D4L: Decentralized dynamic discriminative dictionary learning. IROS Alec Koppel, Garrett Warnell, Ethan Stump, Alejandro Ribeiro
2015	Misc	`conf`	Prediction-correction methods for time-varying convex optimization. ACSSC Andrea Simonetto, Alec Koppel, Aryan Mokhtari, Geert Leus, Alejandro Ribeiro
2015	Misc	`conf`	Regret bounds of a distributed saddle point algorithm. ICASSP Alec Koppel, Felicia Y. Jakubiec, Alejandro Ribeiro
2015	—	`conf`	Target tracking with dynamic convex optimization. GlobalSIP Alec Koppel, Andrea Simonetto, Aryan Mokhtari, Geert Leus, Alejandro Ribeiro
2015	Misc	`conf`	Task-driven dictionary learning in distributed online settings. ACSSC Alec Koppel, Garrett Warned, Ethan Stump
2014	Misc	`conf`	A saddle point algorithm for networked online convex optimization. ICASSP Alec Koppel, Felicia Y. Jakubiec, Alejandro Ribeiro