Alec Koppel
Orcid: 0000-0003-2447-2873
According to our database1,
Alec Koppel
authored at least 121 papers
between 2015 and 2024.
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Bibliography
2024
SIAM J. Math. Data Sci., March, 2024
Global Optimality without Mixing Time Oracles in Average-reward RL via Multi-level Actor-Critic.
CoRR, 2024
CoRR, 2024
Beyond Joint Demonstrations: Personalized Expert Guidance for Efficient Multi-Agent Reinforcement Learning.
CoRR, 2024
MaxMin-RLHF: Towards Equitable Alignment of Large Language Models with Diverse Human Preferences.
CoRR, 2024
2023
On the sample complexity of actor-critic method for reinforcement learning with function approximation.
Mach. Learn., July, 2023
Near-Optimal Fair Resource Allocation for Strategic Agents without Money: A Data-Driven Approach.
CoRR, 2023
Limited-Memory Greedy Quasi-Newton Method with Non-asymptotic Superlinear Convergence Rate.
CoRR, 2023
Ada-NAV: Adaptive Trajectory-Based Sample Efficient Policy Learning for Robotic Navigation.
CoRR, 2023
A Gradient-based Approach for Online Robust Deep Neural Network Training with Noisy Labels.
CoRR, 2023
Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the IEEE International Conference on Robotics and Automation, 2023
Dealing with Sparse Rewards in Continuous Control Robotics via Heavy-Tailed Policy Optimization.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023
Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic.
Proceedings of the International Conference on Machine Learning, 2023
STEERING : Stein Information Directed Exploration for Model-Based Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023
Information-Directed Policy Search in Sparse-Reward Settings via the Occupancy Information Ratio.
Proceedings of the 57th Annual Conference on Information Sciences and Systems, 2023
Proceedings of the 19th IEEE International Conference on Automation Science and Engineering, 2023
Proceedings of the American Control Conference, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Balancing Rates and Variance via Adaptive Batch-Size for Stochastic Optimization Problems.
IEEE Trans. Signal Process., 2022
Sparse Representations of Positive Functions via First- and Second-Order Pseudo-Mirror Descent.
IEEE Trans. Signal Process., 2022
IEEE Trans. Signal Process., 2022
Dense Incremental Metric-Semantic Mapping for Multiagent Systems via Sparse Gaussian Process Regression.
IEEE Trans. Robotics, 2022
Collaborative one-shot beamforming under localization errors: A discrete optimization approach.
Signal Process., 2022
CoRR, 2022
Dealing with Sparse Rewards in Continuous Control Robotics via Heavy-Tailed Policies.
CoRR, 2022
Occupancy Information Ratio: Infinite-Horizon, Information-Directed, Parameterized Policy Search.
CoRR, 2022
Distributed Riemannian Optimization with Lazy Communication for Collaborative Geometric Estimation.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022
Sharpened Quasi-Newton Methods: Faster Superlinear Rate and Larger Local Convergence Neighborhood.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the IEEE International Conference on Acoustics, 2022
Proceedings of the 56th Annual Conference on Information Sciences and Systems, 2022
Convergence Rates of Average-Reward Multi-agent Reinforcement Learning via Randomized Linear Programming.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022
Distributed Gaussian Process Mapping for Robot Teams with Time-varying Communication.
Proceedings of the American Control Conference, 2022
Multi-Agent Reinforcement Learning with General Utilities via Decentralized Shadow Reward Actor-Critic.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
IEEE Trans. Signal Process., 2021
Nonparametric Compositional Stochastic Optimization for Risk-Sensitive Kernel Learning.
IEEE Trans. Signal Process., 2021
IEEE Trans. Signal Inf. Process. over Networks, 2021
Policy Evaluation in Continuous MDPs With Efficient Kernelized Gradient Temporal Difference.
IEEE Trans. Autom. Control., 2021
Consistent online Gaussian process regression without the sample complexity bottleneck.
Stat. Comput., 2021
IEEE J. Sel. Areas Inf. Theory, 2021
On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control.
CoRR, 2021
Dense Incremental Metric-Semantic Mapping for Multi-Agent Systems via Sparse Gaussian Process Regression.
CoRR, 2021
Wasserstein-Splitting Gaussian Process Regression for Heterogeneous Online Bayesian Inference.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021
A Dynamical Systems Perspective on Online Bayesian Nonparametric Estimators with Adaptive Hyperparameters.
Proceedings of the IEEE International Conference on Acoustics, 2021
Semiparametric Information State Embedding for Policy Search under Imperfect Information.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021
Beyond Cumulative Returns via Reinforcement Learning over State-Action Occupancy Measures.
Proceedings of the 2021 American Control Conference, 2021
Joint Position and Beamforming Control via Alternating Nonlinear Least-Squares with a Hierarchical Gamma Prior.
Proceedings of the 2021 American Control Conference, 2021
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021
Randomized Linear Programming for Tabular Average-Cost Multi-agent Reinforcement Learning.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021
2020
High-Dimensional Nonconvex Stochastic Optimization by Doubly Stochastic Successive Convex Approximation.
IEEE Trans. Signal Process., 2020
Optimally Compressed Nonparametric Online Learning: Tradeoffs between memory and consistency.
IEEE Signal Process. Mag., 2020
SIAM J. Control. Optim., 2020
IEEE Robotics Autom. Lett., 2020
J. Mach. Learn. Res., 2020
CoRR, 2020
Variational Policy Gradient Method for Reinforcement Learning with General Utilities.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Efficient Large-Scale Gaussian Process Bandits by Believing only Informative Actions.
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
Balancing Rates and Variance via Adaptive Batch-Sizes in First-Order Stochastic Optimization.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
Reduced-rank Least Squares Parameter Estimation in the Presence of Byzantine Sensors.
Proceedings of the 54th Annual Conference on Information Sciences and Systems, 2020
Trading Dynamic Regret for Model Complexity in Nonstationary Nonparametric Optimization.
Proceedings of the 2020 American Control Conference, 2020
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020
2019
Projected Stochastic Primal-Dual Method for Constrained Online Learning With Kernels.
IEEE Trans. Signal Process., 2019
Asynchronous Saddle Point Algorithm for Stochastic Optimization in Heterogeneous Networks.
IEEE Trans. Signal Process., 2019
IEEE Trans. Signal Inf. Process. over Networks, 2019
J. Mach. Learn. Res., 2019
Approximate Shannon Sampling in Importance Sampling: Nearly Consistent Finite Particle Estimates.
CoRR, 2019
Nonstationary Nonparametric Online Learning: Balancing Dynamic Regret and Model Parsimony.
CoRR, 2019
Policy Search in Infinite-Horizon Discounted Reinforcement Learning: Advances through Connections to Non-Convex Optimization : Invited Presentation.
Proceedings of the 53rd Annual Conference on Information Sciences and Systems, 2019
Convergence and Iteration Complexity of Policy Gradient Method for Infinite-horizon Reinforcement Learning.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019
Proceedings of the 58th IEEE Conference on Decision and Control, 2019
Proceedings of the 58th IEEE Conference on Decision and Control, 2019
Controlling the Bias-Variance Tradeoff via Coherent Risk for Robust Learning with Kernels.
Proceedings of the 2019 American Control Conference, 2019
Consistent Online Gaussian Process Regression Without the Sample Complexity Bottleneck.
Proceedings of the 2019 American Control Conference, 2019
Compressed Streaming Importance Sampling for Efficient Representations of Localization Distributions.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019
2018
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018
Parallel Stochastic Successive Convex Approximation Method for Large-Scale Dictionary Learning.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018
Proceedings of the 57th IEEE Conference on Decision and Control, 2018
Nonparametric Stochastic Compositional Gradient Descent for Q-Learning in Continuous Markov Decision Problems.
Proceedings of the 2018 Annual American Control Conference, 2018
Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018
Proceedings of the 2018 AAAI Spring Symposia, 2018
2017
IEEE Trans. Signal Process., 2017
IEEE Trans. Signal Inf. Process. over Networks, 2017
Decentralized Prediction-Correction Methods for Networked Time-Varying Convex Optimization.
IEEE Trans. Autom. Control., 2017
Large-scale nonconvex stochastic optimization by Doubly Stochastic Successive Convex approximation.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017
Proceedings of the 2017 American Control Conference, 2017
Beyond consensus and synchrony in decentralized online optimization using saddle point method.
Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017
2016
IEEE Trans. Signal Process., 2016
CoRR, 2016
Online learning for characterizing unknown environments in ground robotic vehicle models.
Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016
A Quasi-newton prediction-correction method for decentralized dynamic convex optimization.
Proceedings of the 15th European Control Conference, 2016
Proceedings of the 2016 American Control Conference, 2016
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016
2015
IEEE Trans. Signal Process., 2015
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015
Proceedings of the 2015 IEEE Global Conference on Signal and Information Processing, 2015
A decentralized prediction-correction method for networked time-varying convex optimization.
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015
Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, 2015
Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, 2015