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← Authors

Akshat Kumar

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

Achievements

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+10 more ↓ 🌍 Conference Polyglot (6) πŸ—ΊοΈ Taxonomy Completionist (11) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer πŸƒ Academic Marathon (15)
🧭 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