Optimal Design for Reward Modeling in RLHF
Paper
•
2410.17055
•
Published
AI & ML interests
None defined yet.
Recent Activity
View all activity
misovalko
authored
20
papers
18 days ago
Sharp Deviations Bounds for Dirichlet Weighted Sums with Application to analysis of Bayesian algorithms
Paper
•
2304.03056
•
Published
KL-Entropy-Regularized RL with a Generative Model is Minimax Optimal
Paper
•
2205.14211
•
Published
Local and adaptive mirror descents in extensive-form games
Paper
•
2309.00656
•
Published
Model-free Posterior Sampling via Learning Rate Randomization
Paper
•
2310.18186
•
Published
Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments
Paper
•
2211.10515
•
Published
DoMo-AC: Doubly Multi-step Off-policy Actor-Critic Algorithm
Paper
•
2305.18501
•
Published
A New Bound on the Cumulant Generating Function of Dirichlet Processes
Paper
•
2409.18621
•
Published
VA-learning as a more efficient alternative to Q-learning
Paper
•
2305.18161
•
Published
Generalized Preference Optimization: A Unified Approach to Offline Alignment
Paper
•
2402.05749
•
Published
Preference Optimization with Multi-Sample Comparisons
Paper
•
2410.12138
•
Published
RL-finetuning LLMs from on- and off-policy data with a single algorithm
Paper
•
2503.19612
•
Published
A Provably Efficient Sample Collection Strategy for Reinforcement Learning
Paper
•
2007.06437
•
Published
Model-Free Learning for Two-Player Zero-Sum Partially Observable Markov Games with Perfect Recall
Paper
•
2106.06279
•
Published
Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy Evaluation
Paper
•
2106.13125
•
Published
Broaden Your Views for Self-Supervised Video Learning
Paper
•
2103.16559
•
Published
UCB Momentum Q-learning: Correcting the bias without forgetting
Paper
•
2103.01312
•
Published
Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret
Paper
•
2104.11186
•
Published
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity
Paper
•
2111.02338
•
Published
Marginalized Operators for Off-policy Reinforcement Learning
Paper
•
2203.16177
•
Published