Amrit S. Bedi
Orcid: 0000-0002-8807-2695
According to our database1,
Amrit S. Bedi
authored at least 96 papers
between 2016 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2024
Global Optimality without Mixing Time Oracles in Average-reward RL via Multi-level Actor-Critic.
CoRR, 2024
Beyond Joint Demonstrations: Personalized Expert Guidance for Efficient Multi-Agent Reinforcement Learning.
CoRR, 2024
On the Safety Concerns of Deploying LLMs/VLMs in Robotics: Highlighting the Risks and Vulnerabilities.
CoRR, 2024
MaxMin-RLHF: Towards Equitable Alignment of Large Language Models with Diverse Human Preferences.
CoRR, 2024
CoRR, 2024
2023
REBEL: A Regularization-Based Solution for Reward Overoptimization in Reinforcement Learning from Human Feedback.
CoRR, 2023
CoRR, 2023
RealFM: A Realistic Mechanism to Incentivize Data Contribution and Device Participation.
CoRR, 2023
LANCAR: Leveraging Language for Context-Aware Robot Locomotion in Unstructured Environments.
CoRR, 2023
On the Global Convergence of Natural Actor-Critic with Two-layer Neural Network Parametrization.
CoRR, 2023
iPLAN: Intent-Aware Planning in Heterogeneous Traffic via Distributed Multi-Agent Reinforcement Learning.
CoRR, 2023
Ada-NAV: Adaptive Trajectory-Based Sample Efficient Policy Learning for Robotic Navigation.
CoRR, 2023
RE-MOVE: An Adaptive Policy Design Approach for Dynamic Environments via Language-Based Feedback.
CoRR, 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
RTAW: An Attention Inspired Reinforcement Learning Method for Multi-Robot Task Allocation in Warehouse Environments.
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
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Intent-Aware Planning in Heterogeneous Traffic via Distributed Multi-Agent Reinforcement Learning.
Proceedings of the Conference on Robot Learning, 2023
Proceedings of the 19th IEEE International Conference on Automation Science and Engineering, 2023
Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Conservative Natural Policy Gradient Primal-Dual Algorithm.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
IEEE Trans. Signal Process., 2022
CoRR, 2022
Dealing with Sparse Rewards in Continuous Control Robotics via Heavy-Tailed Policies.
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
DC-MRTA: Decentralized Multi-Robot Task Allocation and Navigation in Complex Environments.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022
FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Machine Learning, 2022
HTRON: Efficient Outdoor Navigation with Sparse Rewards via Heavy Tailed Adaptive Reinforce Algorithm.
Proceedings of the Conference on Robot Learning, 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
Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 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 Process., 2021
IEEE Trans. Signal Inf. Process. over Networks, 2021
Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning.
IEEE Trans. Commun., 2021
IEEE Trans. Autom. Control., 2021
IEEE J. Sel. Areas Inf. Theory, 2021
On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control.
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
Energy-Efficient and Federated Meta-Learning via Projected Stochastic Gradient Ascent.
Proceedings of the IEEE Global Communications Conference, 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
Conservative Stochastic Optimization: $\mathcal{O}(T^{-1/2})$ Optimality Gap with Zero Constraint Violation.
Proceedings of the 2021 American Control Conference, 2021
Randomized Linear Programming for Tabular Average-Cost Multi-agent Reinforcement Learning.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021
2020
Online Trajectory Optimization Using Inexact Gradient Feedback for Time-Varying Environments.
IEEE Trans. Signal Process., 2020
Optimally Compressed Nonparametric Online Learning: Tradeoffs between memory and consistency.
IEEE Signal Process. Mag., 2020
IEEE Robotics Autom. Lett., 2020
J. Mach. Learn. Res., 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 2020 IEEE International Conference on Acoustics, 2020
Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
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
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
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
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
Compressed Streaming Importance Sampling for Efficient Representations of Localization Distributions.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019
2018
Asynchronous Incremental Stochastic Dual Descent Algorithm for Network Resource Allocation.
IEEE Trans. Signal Process., 2018
IEEE Trans. Commun., 2018
IEEE J. Sel. Top. Signal Process., 2018
Proceedings of the 2018 IEEE Wireless Communications and Networking Conference, 2018
Proceedings of the 2018 International Conference on Signal Processing and Communications (SPCOM), 2018
Proceedings of the 2018 IEEE Conference on Computer Communications, 2018
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
Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018
Proceedings of the IEEE International Conference on Advanced Networks and Telecommunications Systems, 2018
2017
Proceedings of the IEEE International Conference on Communications, 2017
Proceedings of the 2017 IEEE International Conference on Communications Workshops, 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 Commun. Lett., 2016
Proceedings of the 2016 IEEE Global Communications Conference, 2016