Cover Image

Q-learning with Posterior Sampling

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Agrawal, Priyank, Agrawal, Shipra, Azati, Azmat
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Optimistic Q-learning for average reward and episodic reinforcement learning
by: Agrawal, Priyank, et al.
Published: (2024)

Dynamic Pricing and Learning with Long-term Reference Effects
by: Agrawal, Shipra, et al.
Published: (2024)

A Tractable Online Learning Algorithm for the Multinomial Logit Contextual Bandit
by: Agrawal, Priyank, et al.
Published: (2020)

Dynamic Pricing and Advertising with Demand Learning
by: Agrawal, Shipra, et al.
Published: (2023)

Spectral Thompson sampling
by: Kocak, Tomas, et al.
Published: (2026)

Spectral bandits for smooth graph functions with applications in recommender systems
by: Kocák, Tomáš, et al.
Published: (2026)

Spectral bandits
by: Kocák, Tomáš, et al.
Published: (2026)

On the Convergence of Single-Timescale Actor-Critic
by: Kumar, Navdeep, et al.
Published: (2024)

Adaptive Few-Shot Learning (AFSL): Tackling Data Scarcity with Stability, Robustness, and Versatility
by: Agrawal, Rishabh
Published: (2025)

Amortized In-Context Bayesian Posterior Estimation
by: Mittal, Sarthak, et al.
Published: (2025)

Phase-Aware Deep Learning with Complex-Valued CNNs for Audio Signal Applications
by: Agrawal, Naman
Published: (2025)

Beyond Next Word Prediction: Developing Comprehensive Evaluation Frameworks for measuring LLM performance on real world applications
by: Agrawal, Vishakha, et al.
Published: (2025)

Illuminate: A novel approach for depression detection with explainable analysis and proactive therapy using prompt engineering
by: Agrawal, Aryan
Published: (2024)

A New Rejection Sampling Approach to $k$-$\mathtt{means}$++ With Improved Trade-Offs
by: Shah, Poojan, et al.
Published: (2025)

Reinforcement Learning in MDPs with Information-Ordered Policies
by: Zhang, Zhongjun, et al.
Published: (2025)

Disentangling impact of capacity, objective, batchsize, estimators, and step-size on flow VI
by: Agrawal, Abhinav, et al.
Published: (2024)

Understanding and mitigating difficulties in posterior predictive evaluation
by: Agrawal, Abhinav, et al.
Published: (2024)

FAST-Q: Fast-track Exploration with Adversarially Balanced State Representations for Counterfactual Action Estimation in Offline Reinforcement Learning
by: Agrawal, Pulkit, et al.
Published: (2025)

FGM optimization in complex domains using Gaussian process regression based profile generation algorithm
by: Konda, Chaitanya Kumar, et al.
Published: (2025)

Posterior Sampling for Continuing Environments
by: Xu, Wanqiao, et al.
Published: (2022)

Eventually LIL Regret: Almost Sure $\ln\ln T$ Regret for a sub-Gaussian Mixture on Unbounded Data
by: Agrawal, Shubhada, et al.
Published: (2025)

On Stopping Times of Power-one Sequential Tests: Tight Lower and Upper Bounds
by: Agrawal, Shubhada, et al.
Published: (2025)

Improving Few-Shot Cross-Domain Named Entity Recognition by Instruction Tuning a Word-Embedding based Retrieval Augmented Large Language Model
by: Nandi, Subhadip, et al.
Published: (2024)

Cover meets Robbins while Betting on Bounded Data: $\ln n$ Regret and Almost Sure $\ln\ln n$ Regret
by: Agrawal, Shubhada, et al.
Published: (2026)

Regret Tail Characterization of Optimal Bandit Algorithms with Generic Rewards
by: Panda, Subhodip, et al.
Published: (2026)

Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent
by: Li, Yingru, et al.
Published: (2024)

Investigating Fouling Efficiency in Football Using Expected Booking (xB) Model
by: Azmat, Adnan, et al.
Published: (2024)

Asymptotic Analysis of Sample-averaged Q-learning
by: Panda, Saunak Kumar, et al.
Published: (2024)

Pareto Set Identification With Posterior Sampling
by: Kone, Cyrille, et al.
Published: (2024)

Gibbs Sampling the Posterior of Neural Networks
by: Piccioli, Giovanni, et al.
Published: (2023)

Bayesian Optimization for Dynamic Pricing and Learning
by: Anand, Anush, et al.
Published: (2025)

RL's Razor: Why Online Reinforcement Learning Forgets Less
by: Shenfeld, Idan, et al.
Published: (2025)

Position: Federated Foundation Language Model Post-Training Should Focus on Open-Source Models
by: Agrawal, Nikita, et al.
Published: (2025)

Two-level Solar Irradiance Clustering with Season Identification: A Comparative Analysis
by: Agrawal, Roshni, et al.
Published: (2025)

Collective Model Intelligence Requires Compatible Specialization
by: Pari, Jyothish, et al.
Published: (2024)

VeriGate: Verifier-Gated Step-Level Supervision for GRPO
by: Agrawal, Aakriti, et al.
Published: (2026)

AGGRNet: Selective Feature Extraction and Aggregation for Enhanced Medical Image Classification
by: Makwe, Ansh, et al.
Published: (2025)

Adaptive Multi-Fidelity Reinforcement Learning for Variance Reduction in Engineering Design Optimization
by: Agrawal, Akash, et al.
Published: (2025)

Adaptive Learning of Design Strategies over Non-Hierarchical Multi-Fidelity Models via Policy Alignment
by: Agrawal, Akash, et al.
Published: (2024)

Addressing LLM Diversity by Infusing Random Concepts
by: Agrawal, Pulin, et al.
Published: (2026)