Marcus Hutter
44 papers · 2003–2025 · 11 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+17 more ↓ Show less ↑
๐ฃ Hot Topic Early Bird ๐บ๏ธ Taxonomy Completionist (13) ๐งญ Keyword Pioneer ๐ Interdisciplinary Bridge ๐ Conference Polyglot (11)
๐
Interdisciplinary Bridge
๐
Cross-Pollinator
(13)
๐บ๏ธ
Taxonomy Completionist
(13)
๐
Keyword Trendsetter Combo
(5)
๐บ
Lone Wolf
(3)
๐
Grand Slam
๐ฑ
Topic Pioneer
๐
Keyword Champion
๐
Triple Crown
๐ฌ
Deep Specialist
(16)
๐งฌ
Topic Evolution
๐
Trend Setter
๐
Conference Pioneer
๐๏ธ
Keyword Collector
(165)
โก
Prolific Year
(5)
๐ฅ
Unstoppable
(13)
๐
Century Club
(44)
Conferences
IJCAI (9)
ICML (6)
NIPS (6)
AAAI (5)
ICLR (5)
JMLR (4)
COLT (3)
ACML (2)
AISTATS (2)
CVPR (1)
UAI (1)
Top co-authors
Research topics
Keywords
reinforcement learning
(11)
online learning
(5)
bayesian inference
(4)
sequence prediction
(3)
markov decision process
(3)
learning theory
(3)
risk management
(2)
credit assignment
(2)
stochastic environment
(2)
temporal difference learning
(2)
information theory
(2)
uncertainty estimation
(2)
ai safety
(2)
convergence analysis
(2)
imitation learning
(2)
probabilistic modeling
(2)
catastrophic forgetting
(2)
policy learning
(2)
stochastic process
(2)
artificial general intelligence
(2)
Papers
RL, but donโt do anything I wouldnโt do
UAI 2025
Dynamic Knowledge Injection for AIXI Agents
AAAI 2024
Distributional Bellman Operators over Mean Embeddings
ICML 2024
Learning Universal Predictors
ICML 2024
Language Modeling Is Compression
ICLR 2024
Levin Tree Search with Context Models
IJCAI 2023
Self-Predictive Universal AI
NIPS 2023
Universal Agent Mixtures and the Geometry of Intelligence
AISTATS 2023
Evaluating Representations with Readout Model Switching
ICLR 2023
Sequential Learning of Neural Networks for Prequential MDL
ICLR 2023
Neural Networks and the Chomsky Hierarchy
ICLR 2023
Atari-5: Distilling the Arcade Learning Environment down to Five Games
ICML 2023
Memory-Based Meta-Learning on Non-Stationary Distributions
ICML 2023
Fully General Online Imitation Learning
JMLR 2022
On the Role of Neural Collapse in Transfer Learning
ICLR 2022
Exact Reduction of Huge Action Spaces in General Reinforcement Learning
AAAI 2021
Counterfactual Credit Assignment in Model-Free Reinforcement Learning
ICML 2021
Gated Linear Networks
AAAI 2021
Logarithmic Pruning is All You Need
NIPS 2020
A Combinatorial Perspective on Transfer Learning
NIPS 2020
Pessimism About Unknown Unknowns Inspires Conservatism
COLT 2020
Asymptotically Unambitious Artificial General Intelligence
AAAI 2020
Online Learning in Contextual Bandits using Gated Linear Networks
NIPS 2020
Conditions on Features for Temporal Difference-Like Methods to Converge
IJCAI 2019
Performance Guarantees for Homomorphisms beyond Markov Decision Processes
AAAI 2019
A Strongly Asymptotically Optimal Agent in General Environments
IJCAI 2019
On Q-learning Convergence for Non-Markov Decision Processes
IJCAI 2018
AGI Safety Literature Review
IJCAI 2018
On Thompson Sampling and Asymptotic Optimality
IJCAI 2017
Count-Based Exploration in Feature Space for Reinforcement Learning
IJCAI 2017
Universal Reinforcement Learning Algorithms: Survey and Experiments
IJCAI 2017
Loss Bounds and Time Complexity for Speed Priors
AISTATS 2016
Discriminative Hierarchical Rank Pooling for Activity Recognition
CVPR 2016
Rationality, Optimism and Guarantees in General Reinforcement Learning
JMLR 2015
Online Learning of k-CNF Boolean Functions
IJCAI 2015
Bad Universal Priors and Notions of Optimality
COLT 2015
Reinforcement learning with value advice
ACML 2014
Sparse Adaptive Dirichlet-Multinomial-like Processes
COLT 2013
The Sample-Complexity of General Reinforcement Learning
ICML 2013
Q-learning for history-based reinforcement learning
ACML 2013
Discrete MDL Predicts in Total Variation
NIPS 2009
Temporal Difference Updating without a Learning Rate
NIPS 2007
Adaptive Online Prediction by Following the Perturbed Leader
JMLR 2005
Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet
JMLR 2003