Amrit Singh Bedi

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 97

Top Topics

Gaussian Process

Policy Gradient

Reinforcement Learning

Top Venues

IEEE Trans. Signal Process.

Publications

Xiyang Wu, Ruiqi Xian, Tianrui Guan, Jing Liang, Souradip Chakraborty, Fuxiao Liu, Brian M. Sadler, Dinesh Manocha, Amrit Singh Bedi
On the Safety Concerns of Deploying LLMs/VLMs in Robotics: Highlighting the Risks and Vulnerabilities. CoRR (2024)
Xingpeng Sun, Haoming Meng, Souradip Chakraborty, Amrit Singh Bedi, Aniket Bera
Beyond Text: Improving LLM's Decision Making for Robot Navigation via Vocal Cues. CoRR (2024)
Marco Bornstein, Amrit Singh Bedi, Abdirisak Mohamed, Furong Huang
FACT or Fiction: Can Truthful Mechanisms Eliminate Federated Free Riding? CoRR (2024)
Mudit Gaur, Amrit Singh Bedi, Di Wang, Vaneet Aggarwal
Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization. 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)
Bhrij Patel, Vishnu Sashank Dorbala, Dinesh Manocha, Amrit Singh Bedi
Embodied Question Answering via Multi-LLM Systems. CoRR (2024)
Utsav Singh, Souradip Chakraborty, Wesley A. Suttle, Brian M. Sadler, Vinay P. Namboodiri, Amrit Singh Bedi
DIPPER: Direct Preference Optimization to Accelerate Primitive-Enabled Hierarchical Reinforcement Learning. CoRR (2024)
Vishnu Sashank Dorbala, Bhrij Patel, Amrit Singh Bedi, Dinesh Manocha
Right Place, Right Time! Towards ObjectNav for Non-Stationary Goals. CoRR (2024)
Utsav Singh, Wesley A. Suttle, Brian M. Sadler, Vinay P. Namboodiri, Amrit Singh Bedi
PIPER: Primitive-Informed Preference-based Hierarchical Reinforcement Learning via Hindsight Relabeling. CoRR (2024)
Souradip Chakraborty, Soumya Suvra Ghosal, Ming Yin, Dinesh Manocha, Mengdi Wang, Amrit Singh Bedi, Furong Huang
Transfer Q Star: Principled Decoding for LLM Alignment. CoRR (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)
Chak Lam Shek, Xiyang Wu, Dinesh Manocha, Pratap Tokekar, Amrit Singh Bedi
LANCAR: Leveraging Language for Context-Aware Robot Locomotion in Unstructured Environments. CoRR (2023)
Souradip Chakraborty, Kasun Weerakoon, Prithvi Poddar, Pratap Tokekar, Amrit Singh Bedi, Dinesh Manocha
RE-MOVE: An Adaptive Policy Design Approach for Dynamic Environments via Language-Based Feedback. CoRR (2023)
Aakriti Agrawal, Amrit Singh Bedi, Dinesh Manocha
RTAW: An Attention Inspired Reinforcement Learning Method for Multi-Robot Task Allocation in Warehouse Environments. ICRA (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)
Hans He, Alec Koppel, Amrit Singh Bedi, Mazen Farhood, Daniel J. Stilwell
Bi-Level Nonstationary Kernels for Online Gaussian Process Regression. CASE (2023)
Souradip Chakraborty, Amisha Bhaskar, Anukriti Singh, Pratap Tokekar, Dinesh Manocha, Amrit Singh Bedi
REBEL: A Regularization-Based Solution for Reward Overoptimization in Reinforcement Learning from Human Feedback. 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)
Mudit Gaur, Amrit Singh Bedi, Di Wang, Vaneet Aggarwal
On the Global Convergence of Natural Actor-Critic with Two-layer Neural Network Parametrization. CoRR (2023)
Xiyang Wu, Rohan Chandra, Tianrui Guan, Amrit Singh Bedi, Dinesh Manocha
iPLAN: Intent-Aware Planning in Heterogeneous Traffic via Distributed Multi-Agent Reinforcement Learning. CoRR (2023)
Qinbo Bai, Amrit Singh Bedi, Vaneet Aggarwal
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Conservative Natural Policy Gradient Primal-Dual Algorithm. AAAI (2023)
Souradip Chakraborty, Amrit Singh Bedi, Sicheng Zhu, Bang An, Dinesh Manocha, Furong Huang
On the Possibilities of AI-Generated Text Detection. CoRR (2023)
Soumya Suvra Ghosal, Souradip Chakraborty, Jonas Geiping, Furong Huang, Dinesh Manocha, Amrit Singh Bedi
Towards Possibilities & Impossibilities of AI-generated Text Detection: A Survey. CoRR (2023)
Marco Bornstein, Amrit Singh Bedi, Anit Kumar Sahu, Furqan Khan, Furong Huang
RealFM: A Realistic Mechanism to Incentivize Data Contribution and Device Participation. CoRR (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)
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)
Anis Elgabli, Chaouki Ben Issaid, Amrit Singh Bedi, Ketan Rajawat, Mehdi Bennis, Vaneet Aggarwal
FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning. ICML (2022)
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)
Marco Bornstein, Tahseen Rabbani, Evan Wang, Amrit Singh Bedi, Furong Huang
SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication. CoRR (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)
Zeeshan Akhtar, Amrit Singh Bedi, Srujan Teja Thomdapu, Ketan Rajawat
Projection-Free Stochastic Bi-Level Optimization. IEEE Trans. Signal Process. 70 (2022)
Senthil Hariharan Arul, Amrit Singh Bedi, Dinesh Manocha
DMCA: Dense Multi-agent Navigation using Attention and Communication. CoRR (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)
Aakriti Agrawal, Senthil Hariharan Arul, Amrit Singh Bedi, Dinesh Manocha
DC-MRTA: Decentralized Multi-Robot Task Allocation and Navigation in Complex Environments. IROS (2022)
Qinbo Bai, Amrit Singh Bedi, Vaneet Aggarwal
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Conservative Natural Policy Gradient Primal-Dual Algorithm. CoRR (2022)
Aakriti Agrawal, Amrit Singh Bedi, Dinesh Manocha
RTAW: An Attention Inspired Reinforcement Learning Method for Multi-Robot Task Allocation in Warehouse Environments. 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)
Amrit Singh Bedi, Ketan Rajawat, Vaneet Aggarwal, Alec Koppel
Escaping Saddle Points for Successive Convex Approximation. IEEE Trans. Signal Process. 70 (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)
Kasun Weerakoon, Souradip Chakraborty, Nare Karapetyan, Adarsh Jagan Sathyamoorthy, Amrit Singh Bedi, Dinesh Manocha
HTRON: Efficient Outdoor Navigation with Sparse Rewards via Heavy Tailed Adaptive Reinforce Algorithm. CoRR (2022)
Aakriti Agrawal, Senthil Hariharan Arul, Amrit Singh Bedi, Dinesh Manocha
DC-MRTA: Decentralized Multi-Robot Task Allocation and Navigation in Complex Environments. CoRR (2022)
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)
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)
Zeeshan Akhtar, Amrit Singh Bedi, Ketan Rajawat
Conservative Stochastic Optimization With Expectation Constraints. IEEE Trans. Signal Process. 69 (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)
Rishabh Dixit, Amrit Singh Bedi, Ketan Rajawat
Online Learning Over Dynamic Graphs via Distributed Proximal Gradient Algorithm. IEEE Trans. Autom. Control. 66 (11) (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)
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)
Anis Elgabli, Jihong Park, Amrit Singh Bedi, Chaouki Ben Issaid, Mehdi Bennis, Vaneet Aggarwal
Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning. IEEE Trans. Commun. 69 (1) (2021)
Alec Koppel, Amrit Singh Bedi, Bhargav Ganguly, Vaneet Aggarwal
Randomized Linear Programming for Tabular Average-Cost Multi-agent Reinforcement Learning. 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)
Zeeshan Akhtar, Amrit Singh Bedi, Ketan Rajawat
Conservative Stochastic Optimization: $\mathcal{O}(T^{-1/2})$ Optimality Gap with Zero Constraint Violation. ACC (2021)
Zeeshan Akhtar, Amrit Singh Bedi, Srujan Teja Thomdapu, Ketan Rajawat
Projection-Free Algorithm for Stochastic Bi-level Optimization. CoRR (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)
Hrusikesha Pradhan, Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
Adaptive Kernel Learning in Heterogeneous Networks. IEEE Trans. Signal Inf. Process. over Networks 7 (2021)
Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel
Cautious Reinforcement Learning via Distributional Risk in the Dual Domain. CoRR (2020)
Zeeshan Akhtar, Amrit Singh Bedi, Ketan Rajawat
Conservative Stochastic Optimization with Expectation Constraints. 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)
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)
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)
Amrit Singh Bedi, Dheeraj Peddireddy, Vaneet Aggarwal, Alec Koppel
Efficient Large-Scale Gaussian Process Bandits by Believing only Informative Actions. L4DC (2020)
Amrit Singh Bedi, Dheeraj Peddireddy, Vaneet Aggarwal, Alec Koppel
Efficient Gaussian Process Bandits by Believing only Informative Actions. CoRR (2020)
Hrusikesha Pradhan, Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
Conservative Multi-agent Online Kernel Learning in Heterogeneous Networks. ACSSC (2020)
Mohan Krishna Nutalapati, Amrit Singh Bedi, Ketan Rajawat, Marceau Coupechoux
Online Trajectory Optimization Using Inexact Gradient Feedback for Time-Varying Environments. IEEE Trans. Signal Process. 68 (2020)
Junyu Zhang, Alec Koppel, Amrit Singh Bedi, Csaba Szepesvári, Mengdi Wang
Variational Policy Gradient Method for Reinforcement Learning with General Utilities. CoRR (2020)
Rishabh Dixit, Amrit Singh Bedi, Ruchi Tripathi, Ketan Rajawat
Online Learning With Inexact Proximal Online Gradient Descent Algorithms. IEEE Trans. Signal Process. 67 (5) (2019)
Amrit Singh Bedi, Alec Koppel, Brian M. Sadler, Víctor Elvira
Compressed Streaming Importance Sampling for Efficient Representations of Localization Distributions. ACSSC (2019)
Rishabh Dixit, Amrit Singh Bedi, Ketan Rajawat
Online Learning over Dynamic Graphs via Distributed Proximal Gradient Algorithm. CoRR (2019)
Rishabh Dixit, Amrit Singh Bedi, Ketan Rajawat, Alec Koppel
Distributed Online Learning over Time-varying Graphs via Proximal Gradient Descent. CDC (2019)
Amrit Singh Bedi, Alec Koppel, Ketan Rajawat, Brian M. Sadler
Nonstationary Nonparametric Online Learning: Balancing Dynamic Regret and Model Parsimony. CoRR (2019)
Alec Koppel, Amrit Singh Bedi, Victor Elvira, Brian M. Sadler
Approximate Shannon Sampling in Importance Sampling: Nearly Consistent Finite Particle Estimates. CoRR (2019)
Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
Asynchronous Online Learning in Multi-Agent Systems With Proximity Constraints. IEEE Trans. Signal Inf. Process. over Networks 5 (3) (2019)
Alec Koppel, Amrit Singh Bedi, Ketan Rajawat, Brian M. Sadler
Optimally Compressed Nonparametric Online Learning. CoRR (2019)
Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
Asynchronous Saddle Point Algorithm for Stochastic Optimization in Heterogeneous Networks. IEEE Trans. Signal Process. 67 (7) (2019)
Amrit Singh Bedi, Ketan Rajawat
Wireless network optimization via stochastic sub-gradient descent: Rate analysis. WCNC (2018)
Amrit Singh Bedi, Ketan Rajawat
Network Resource Allocation via Stochastic Subgradient Descent: Convergence Rate. IEEE Trans. Commun. 66 (5) (2018)
Hrusikesha Pradhan, Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
Exact Nonparametric Decentralized Online Optimization. GlobalSIP (2018)
Amrit Singh Bedi, Paban Sarma, Ketan Rajawat
Adversarial Multi-Agent Target Tracking with Inexact Online Gradient Descent. ICASSP (2018)
Rishabh Dixit, Amrit Singh Bedi, Ruchi Tripathi, Ketan Rajawat
Time Varying optimization via Inexact Proximal Online Gradient Descent. ACSSC (2018)
Amrit Singh Bedi, Hrusikesha Pradhan, Ketan Rajawat
Decentralized Asynchronous Stochastic Gradient Descent: Convergence Rate Analysis. SPCOM (2018)
Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
Asynchronous Saddle Point Method: Interference Management Through Pricing. CDC (2018)
Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
Beyond consensus and synchrony in decentralized online optimization using saddle point method. ACSSC (2017)