Kumar, Akshat

43 publications

NeurIPS 2025 IOSTOM: Offline Imitation Learning from Observations via State Transition Occupancy Matching Quang Anh Pham, Janaka Chathuranga Brahmanage, Tien Anh Mai, Akshat Kumar

AAAI 2025 Leveraging Constraint Violation Signals for Action Constrained Reinforcement Learning Janaka Chathuranga Brahmanage, Jiajing Ling, Akshat Kumar

AAAI 2025 Offline Safe Reinforcement Learning Using Trajectory Classification Ze Gong, Akshat Kumar, Pradeep Varakantham

ICLRW 2025 TraCeS: Trajectory Based Credit Assignment from Sparse Safety Feedback Siow Meng Low, Akshat Kumar

ICML 2024 Unified Training of Universal Time Series Forecasting Transformers Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, Doyen Sahoo

NeurIPS 2023 FlowPG: Action-Constrained Policy Gradient with Normalizing Flows Janaka Brahmanage, Jiajing Ling, Akshat Kumar

ICML 2023 Learning Deep Time-Index Models for Time Series Forecasting Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven Hoi

AAAI 2023 Planning and Learning for Non-Markovian Negative Side Effects Using Finite State Controllers Aishwarya Srivastava, Sandhya Saisubramanian, Praveen Paruchuri, Akshat Kumar, Shlomo Zilberstein

AAAI 2023 Scalable and Globally Optimal Generalized L₁ K-Center Clustering via Constraint Generation in Mixed Integer Linear Programming Aravinth Chembu, Scott Sanner, Hassan Khurram, Akshat Kumar

ICLR 2022 CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven Hoi

ECML-PKDD 2022 Constrained Multiagent Reinforcement Learning for Large Agent Population Jiajing Ling, Arambam James Singh, Nguyen Duc Thien, Akshat Kumar

AAAI 2022 Sample-Efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs Siow Meng Low, Akshat Kumar, Scott Sanner

IJCAI 2022 Using Constraint Programming and Graph Representation Learning for Generating Interpretable Cloud Security Policies Mikhail Kazdagli, Mohit Tiwari, Akshat Kumar

IJCAI 2019 Decision Making for Improving Maritime Traffic Safety Using Constraint Programming Saumya Bhatnagar, Akshat Kumar, Hoong Chuin Lau

IJCAI 2019 Multiagent Decision Making and Learning in Urban Environments Akshat Kumar

AAAI 2019 Multiagent Decision Making for Maritime Traffic Management Arambam James Singh, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau

AAAI 2019 Successor Features Based Multi-Agent RL for Event-Based Decentralized MDPs Tarun Gupta, Akshat Kumar, Praveen Paruchuri

NeurIPS 2018 Credit Assignment for Collective Multiagent RL with Global Rewards Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau

AAAI 2018 Integrated Cooperation and Competition in Multi-Agent Decision-Making Kyle Hollins Wray, Akshat Kumar, Shlomo Zilberstein

AAAI 2018 Planning and Learning for Decentralized MDPs with Event Driven Rewards Tarun Gupta, Akshat Kumar, Praveen Paruchuri

AAAI 2018 Resource-Constrained Scheduling for Maritime Traffic Management Lucas Agussurja, Akshat Kumar, Hoong Chuin Lau

AAAI 2017 Collective Multiagent Sequential Decision Making Under Uncertainty Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau

AAAI 2017 Decentralized Planning in Stochastic Environments with Submodular Rewards Rajiv Ranjan Kumar, Pradeep Varakantham, Akshat Kumar

NeurIPS 2017 Policy Gradient with Value Function Approximation for Collective Multiagent Planning Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau

AAAI 2017 Robust Optimization for Tree-Structured Stochastic Network Design XiaoJian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein

AISTATS 2016 Approximate Inference Using DC Programming for Collective Graphical Models Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau, Daniel Sheldon

AAAI 2016 Robust Decision Making for Stochastic Network Design Akshat Kumar, Arambam James Singh, Pradeep Varakantham, Daniel Sheldon

AAAI 2016 Shortest Path Based Decision Making Using Probabilistic Inference Akshat Kumar

ICML 2015 Message Passing for Collective Graphical Models Tao Sun, Dan Sheldon, Akshat Kumar

IJCAI 2015 Probabilistic Inference Based Message-Passing for Resource Constrained DCOPs Supriyo Ghosh, Akshat Kumar, Pradeep Varakantham

JAIR 2015 Probabilistic Inference Techniques for Scalable Multiagent Decision Making Akshat Kumar, Shlomo Zilberstein, Marc Toussaint

ICML 2013 Approximate Inference in Collective Graphical Models Daniel Sheldon, Tao Sun, Akshat Kumar, Tom Dietterich

IJCAI 2013 Automated Generation of Interaction Graphs for Value-Factored Dec-POMDPs William Yeoh, Akshat Kumar, Shlomo Zilberstein

UAI 2013 Collective Diffusion over Networks: Models and Inference Akshat Kumar, Daniel Sheldon, Biplav Srivastava

IJCAI 2013 Parameter Learning for Latent Network Diffusion XiaoJian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein

AAAI 2012 Lagrangian Relaxation Techniques for Scalable Spatial Conservation Planning Akshat Kumar, XiaoJian Wu, Shlomo Zilberstein

AISTATS 2012 Message-Passing Algorithms for MAP Estimation Using DC Programming Akshat Kumar, Shlomo Zilberstein, Marc Toussaint

UAI 2011 Message-Passing Algorithms for Quadratic Programming Formulations of MAP Estimation Akshat Kumar, Shlomo Zilberstein

IJCAI 2011 Scalable Multiagent Planning Using Probabilistic Inference Akshat Kumar, Shlomo Zilberstein, Marc Toussaint

UAI 2010 Anytime Planning for Decentralized POMDPs Using Expectation Maximization Akshat Kumar, Shlomo Zilberstein

NeurIPS 2010 MAP Estimation for Graphical Models by Likelihood Maximization Akshat Kumar, Shlomo Zilberstein

IJCAI 2009 Event-Detecting Multi-Agent MDPs: Complexity and Constant-Factor Approximations Akshat Kumar, Shlomo Zilberstein

AAAI 2008 H-DPOP: Using Hard Constraints for Search Space Pruning in DCOP Akshat Kumar, Adrian Petcu, Boi Faltings