Omer Gottesman
16 papers · 2018–2025 · 6 venues · across top CS/AI venues
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Achievements
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Research topics
Machine Learning
(14)
Reinforcement Learning
(13)
Methods
(13)
Learning Types Β· Machine Learning
(8)
Artificial Intelligence
(7)
Core AI
(7)
Optimization & Theory
(7)
Core Methods
(4)
Deep Learning
(2)
Applications
(2)
Mathematics & Optimization
(1)
Application Areas
(1)
Learning Paradigms
(1)
Learning Types Β· Deep Learning
(1)
Mathematics
(1)
Keywords
reinforcement learning
(5)
off-policy evaluation
(3)
markov decision process
(2)
deep reinforcement learning
(2)
causal inference
(2)
importance sampling
(2)
state representation
(2)
continuous control
(2)
temporal difference learning
(2)
value function
(2)
hierarchical reinforcement learning
(1)
tensor decomposition
(1)
neural network optimization
(1)
iterative optimization
(1)
convergence analysis
(1)
causal reasoning
(1)
dynamic programming
(1)
nonparametric model
(1)
manifold learning
(1)
offline reinforcement learning
(1)
Papers
Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces
ICLR 2025
Decision-Focused Model-based Reinforcement Learning for Reward Transfer
MLHC 2024
Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy
NeurIPS 2024
Coarse-Grained Smoothness for Reinforcement Learning in Metric Spaces
AISTATS 2023
Effectively Learning Initiation Sets in Hierarchical Reinforcement Learning
NeurIPS 2023
Performance Bounds for Model and Policy Transfer in Hidden-parameter MDPs
ICLR 2023
TD Convergence: An Optimization Perspective
NeurIPS 2023
Faster Deep Reinforcement Learning with Slower Online Network
NeurIPS 2022
Optimistic Initialization for Exploration in Continuous Control
AAAI 2022
Learning Markov State Abstractions for Deep Reinforcement Learning
NeurIPS 2021
State Relevance for Off-Policy Evaluation
ICML 2021
Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions
ICML 2020
Learning to search efficiently for causally near-optimal treatments
NeurIPS 2020
Combining parametric and nonparametric models for off-policy evaluation
ICML 2019
Representation Balancing MDPs for Off-policy Policy Evaluation
NeurIPS 2018
Weighted Tensor Decomposition for Learning Latent Variables with Partial Data
AISTATS 2018