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Akshat Kumar

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

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+8 more ↓ πŸ—ΊοΈ Taxonomy Completionist (49) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Full πŸŒ‰ Interdisciplinary Bridge Β· Silver 🐣 Hot Topic Early Bird
πŸ† Keyword Champion πŸ† Grand Slam 🌈 Renaissance Researcher (6) πŸ”₯ Unstoppable Β· Bronze πŸš€ Conference Pioneer πŸ’Ž Century Club Β· Bronze πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (109)

Venues

AAAI (7) IJCAI (6) ICML (4) NeurIPS (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)

Research topics

Machine Learning (17) Artificial Intelligence (13) Reinforcement Learning (9) Core AI (9) Learning Types Β· Machine Learning (8) Core Methods (7) Methods (7) Optimization & Theory (6) Deep Learning (5) Mathematics & Optimization (5) Applications (5) Learning Types Β· Deep Learning (4) Optimization (4) Bayesian & Probabilistic (3) Data Science & Analytics (2)

Keywords

policy gradient (4) approximate inference (3) message passing (3) multi-agent system (3) reinforcement learning (3) action-constrained reinforcement learning (2) safe reinforcement learning (2) policy learning (2) multi-agent reinforcement learning (2) policy optimization (2) collective graphical model (2) graphical model (2) map inference (2) time series forecasting (2) normalizing flow (2) constraint programming (2) constraint satisfaction (2) belief propagation (1) convex optimization (1) transfer learning (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 FlowPG: Action-constrained Policy Gradient with Normalizing Flows NeurIPS 2023 Learning Deep Time-index Models for Time Series Forecasting ICML 2023 Planning and Learning for Non-markovian Negative Side Effects Using Finite State Controllers AAAI 2023 Scalable and Globally Optimal Generalized L₁ K-center Clustering via Constraint Generation in Mixed Integer Linear Programming AAAI 2023 CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting ICLR 2022 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 Decision Making for Improving Maritime Traffic Safety Using Constraint Programming IJCAI 2019 Multiagent Decision Making and Learning in Urban Environments IJCAI 2019 Multiagent Decision Making For Maritime Traffic Management AAAI 2019 Successor Features Based Multi-Agent RL for Event-Based Decentralized MDPs AAAI 2019 Credit Assignment For Collective Multiagent RL With Global Rewards NeurIPS 2018 Policy Gradient With Value Function Approximation For Collective Multiagent Planning NeurIPS 2017 Approximate Inference Using DC Programming For Collective Graphical Models AISTATS 2016 Message Passing for Collective Graphical Models ICML 2015 Probabilistic Inference Based Message-Passing for Resource Constrained DCOPs IJCAI 2015 Approximate Inference in Collective Graphical Models ICML 2013 Automated Generation of Interaction Graphs for Value-Factored Decentralized POMDPs IJCAI 2013 Parameter Learning for Latent Network Diffusion IJCAI 2013 Message-Passing Algorithms for MAP Estimation Using DC Programming AISTATS 2012 MAP Estimation for Graphical Models by Likelihood Maximization NeurIPS 2010