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Akshat Kumar

24 papers · 2010–2025 · 6 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (11) 🐝 Cross-Pollinator (14) 🌈 Renaissance Researcher (8) πŸƒ Academic Marathon (15) 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (6) πŸ† Keyword Champion πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (99) πŸ’Ž Century Club (24) πŸ”₯ Unstoppable (5) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer

Conferences

AAAI (7) IJCAI (6) ICML (4) NIPS (4) AISTATS (2) ICLR (1)

Top co-authors

Shlomo Zilberstein (5) Hoong Chuin Lau (5) Chenghao Liu (3) Doyen Sahoo (3) Duc Thien Nguyen (3) Gerald Woo (3) Daniel Sheldon (3) Scott Sanner (2) Steven Hoi (2) Tao Sun (2)

Keywords

policy gradient (4) message passing (3) approximate inference (3) multi-agent system (3) reinforcement learning (3) policy optimization (2) collective graphical model (2) multi-agent reinforcement learning (2) graphical model (2) safe reinforcement learning (2) normalizing flow (2) policy learning (2) map inference (2) constraint satisfaction (2) constraint programming (2) graph representation learning (1) em algorithm (1) offline reinforcement learning (1) belief propagation (1) sample efficiency (1)

Papers

Leveraging Constraint Violation Signals for Action Constrained Reinforcement Learning AAAI 2025
Offline Safe Reinforcement Learning Using Trajectory Classification AAAI 2025
Unified Training of Universal Time Series Forecasting Transformers ICML 2024
Planning and Learning for Non-markovian Negative Side Effects Using Finite State Controllers AAAI 2023
FlowPG: Action-constrained Policy Gradient with Normalizing Flows NIPS 2023
Scalable and Globally Optimal Generalized L₁ K-center Clustering via Constraint Generation in Mixed Integer Linear Programming AAAI 2023
Learning Deep Time-index Models for Time Series Forecasting ICML 2023
Sample-Efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs AAAI 2022
Using Constraint Programming and Graph Representation Learning for Generating Interpretable Cloud Security Policies IJCAI 2022
CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting ICLR 2022
Multiagent Decision Making For Maritime Traffic Management AAAI 2019
Multiagent Decision Making and Learning in Urban Environments IJCAI 2019
Decision Making for Improving Maritime Traffic Safety Using Constraint Programming IJCAI 2019
Successor Features Based Multi-Agent RL for Event-Based Decentralized MDPs AAAI 2019
Credit Assignment For Collective Multiagent RL With Global Rewards NIPS 2018
Policy Gradient With Value Function Approximation For Collective Multiagent Planning NIPS 2017
Approximate Inference Using DC Programming For Collective Graphical Models AISTATS 2016
Probabilistic Inference Based Message-Passing for Resource Constrained DCOPs IJCAI 2015
Message Passing for Collective Graphical Models ICML 2015
Parameter Learning for Latent Network Diffusion IJCAI 2013
Approximate Inference in Collective Graphical Models ICML 2013
Automated Generation of Interaction Graphs for Value-Factored Decentralized POMDPs IJCAI 2013
Message-Passing Algorithms for MAP Estimation Using DC Programming AISTATS 2012
MAP Estimation for Graphical Models by Likelihood Maximization NIPS 2010