Marc G. Bellemare
25 papers · 2015–2024 · 7 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (28) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Keyword Trendsetter Combo
(3)
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Grand Slam
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Deep Specialist
(15)
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Keyword Champion
(3)
π§
Keyword Pioneer
π
Trend Setter
β‘
Prolific Year Β· Productive
ποΈ
Keyword Collector
(108)
π₯
Unstoppable Β· Bronze
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Century Club Β· Bronze
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Conference Pioneer
Top co-authors
Research topics
Reinforcement Learning
(22)
Machine Learning
(21)
Methods
(18)
Learning Types Β· Machine Learning
(12)
Optimization & Theory
(12)
Applications
(10)
Deep Learning
(9)
Learning Types Β· Deep Learning
(8)
Core Methods
(7)
Artificial Intelligence
(6)
Core AI
(6)
Mathematics & Optimization
(2)
Natural Language Processing
(1)
Architectures
(1)
Generation
(1)
Keywords
reinforcement learning
(7)
distributional reinforcement learning
(7)
deep reinforcement learning
(7)
representation learning
(6)
value function
(5)
return distribution
(3)
exploration bonus
(3)
convergence guarantee
(3)
markov decision process
(3)
atari game
(3)
successor representation
(2)
auxiliary task
(2)
convergence analysis
(2)
sample efficiency
(2)
function approximation
(2)
policy optimization
(2)
policy iteration
(2)
state representation
(2)
sparse reward
(2)
count-based exploration
(2)
Papers
Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning
NeurIPS 2024
An Analysis of Quantile Temporal-Difference Learning
JMLR 2024
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces
AISTATS 2023
Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement Learning
ICML 2022
On the Generalization of Representations in Reinforcement Learning
AISTATS 2022
Metrics and Continuity in Reinforcement Learning
AAAI 2021
The Value-Improvement Path: Towards Better Representations for Reinforcement Learning
AAAI 2021
A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms
AISTATS 2020
Algorithmic Improvements for Deep Reinforcement Learning Applied to Interactive Fiction
AAAI 2020
Count-Based Exploration with the Successor Representation
AAAI 2020
On Bonus Based Exploration Methods In The Arcade Learning Environment
ICLR 2020
Representations for Stable Off-Policy Reinforcement Learning
ICML 2020
A Comparative Analysis of Expected and Distributional Reinforcement Learning
AAAI 2019
An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents
IJCAI 2019
DeepMDP: Learning Continuous Latent Space Models for Representation Learning
ICML 2019
Distributional reinforcement learning with linear function approximation
AISTATS 2019
Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift
AAAI 2019
Statistics and Samples in Distributional Reinforcement Learning
ICML 2019
The Value Function Polytope in Reinforcement Learning
ICML 2019
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents (Extended Abstract)
IJCAI 2018
A Distributional Perspective on Reinforcement Learning
ICML 2017
A Laplacian Framework for Option Discovery in Reinforcement Learning
ICML 2017
Automated Curriculum Learning for Neural Networks
ICML 2017
Count-Based Exploration with Neural Density Models
ICML 2017
Count-Based Frequency Estimation with Bounded Memory
IJCAI 2015