Sparse Optimistic Information Directed Sampling
Fuente:
arXiv
Guardado en:
| Autores principales: | Schwartz, Ludovic, Flynn, Hamish, Neu, Gergely |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Optimistic Information Directed Sampling
por: Neu, Gergely, et al.
Publicado: (2024)
por: Neu, Gergely, et al.
Publicado: (2024)
Linear Bandits with Non-i.i.d. Noise
por: Abélès, Baptiste, et al.
Publicado: (2025)
por: Abélès, Baptiste, et al.
Publicado: (2025)
Optimistically Optimistic Exploration for Provably Efficient Infinite-Horizon Reinforcement and Imitation Learning
por: Moulin, Antoine, et al.
Publicado: (2025)
por: Moulin, Antoine, et al.
Publicado: (2025)
Confidence Sequences for Generalized Linear Models via Regret Analysis
por: Clerico, Eugenio, et al.
Publicado: (2025)
por: Clerico, Eugenio, et al.
Publicado: (2025)
Relative Information Gain and Gaussian Process Regression
por: Flynn, Hamish
Publicado: (2025)
por: Flynn, Hamish
Publicado: (2025)
Distances for Markov chains from sample streams
por: Calo, Sergio, et al.
Publicado: (2025)
por: Calo, Sergio, et al.
Publicado: (2025)
Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently
por: Calo, Sergio, et al.
Publicado: (2024)
por: Calo, Sergio, et al.
Publicado: (2024)
Sparse Nonparametric Contextual Bandits
por: Flynn, Hamish, et al.
Publicado: (2025)
por: Flynn, Hamish, et al.
Publicado: (2025)
Tighter Confidence Bounds for Sequential Kernel Regression
por: Flynn, Hamish, et al.
Publicado: (2024)
por: Flynn, Hamish, et al.
Publicado: (2024)
Online combinatorial optimization with stochastic decision sets and adversarial losses
por: Neu, Gergely, et al.
Publicado: (2026)
por: Neu, Gergely, et al.
Publicado: (2026)
Offline RL via Feature-Occupancy Gradient Ascent
por: Neu, Gergely, et al.
Publicado: (2024)
por: Neu, Gergely, et al.
Publicado: (2024)
Online-to-PAC Conversions: Generalization Bounds via Regret Analysis
por: Lugosi, Gábor, et al.
Publicado: (2023)
por: Lugosi, Gábor, et al.
Publicado: (2023)
Posterior Sampling Reinforcement Learning with Gaussian Processes for Continuous Control: Sublinear Regret Bounds for Unbounded State Spaces
por: Flynn, Hamish, et al.
Publicado: (2026)
por: Flynn, Hamish, et al.
Publicado: (2026)
Dealing with unbounded gradients in stochastic saddle-point optimization
por: Neu, Gergely, et al.
Publicado: (2024)
por: Neu, Gergely, et al.
Publicado: (2024)
Inverse Q-Learning Done Right: Offline Imitation Learning in $Q^π$-Realizable MDPs
por: Moulin, Antoine, et al.
Publicado: (2025)
por: Moulin, Antoine, et al.
Publicado: (2025)
Online learning with Erdős-Rényi side-observation graphs
por: Kocák, Tomáš, et al.
Publicado: (2026)
por: Kocák, Tomáš, et al.
Publicado: (2026)
Online-to-PAC generalization bounds under graph-mixing dependencies
por: Abélès, Baptiste, et al.
Publicado: (2024)
por: Abélès, Baptiste, et al.
Publicado: (2024)
Online learning with noisy side observations
por: Kocák, Tomáš, et al.
Publicado: (2026)
por: Kocák, Tomáš, et al.
Publicado: (2026)
Generalization bounds for mixing processes via delayed online-to-PAC conversions
por: Abeles, Baptiste, et al.
Publicado: (2024)
por: Abeles, Baptiste, et al.
Publicado: (2024)
Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures
por: Flynn, Hamish, et al.
Publicado: (2023)
por: Flynn, Hamish, et al.
Publicado: (2023)
Efficient learning by implicit exploration in bandit problems with side observations
por: Kocak, Tomas, et al.
Publicado: (2026)
por: Kocak, Tomas, et al.
Publicado: (2026)
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
por: Bayrooti, Jasmine, et al.
Publicado: (2024)
por: Bayrooti, Jasmine, et al.
Publicado: (2024)
COMPASS: COntinual Multilingual PEFT with Adaptive Semantic Sampling
por: Flynn, Noah
Publicado: (2026)
por: Flynn, Noah
Publicado: (2026)
Optimistic Thompson Sampling for No-Regret Learning in Unknown Games
por: Li, Yingru, et al.
Publicado: (2024)
por: Li, Yingru, et al.
Publicado: (2024)
Optimistic Policy Regularization
por: Pham, Mai, et al.
Publicado: (2026)
por: Pham, Mai, et al.
Publicado: (2026)
Sparse random hypergraphs: Non-backtracking spectra and community detection
por: Stephan, Ludovic, et al.
Publicado: (2022)
por: Stephan, Ludovic, et al.
Publicado: (2022)
Omega: Optimistic EMA Gradients
por: Ramirez, Juan, et al.
Publicado: (2023)
por: Ramirez, Juan, et al.
Publicado: (2023)
Optimistic critics can empower small actors
por: Mastikhina, Olya, et al.
Publicado: (2025)
por: Mastikhina, Olya, et al.
Publicado: (2025)
SOMBRL: Scalable and Optimistic Model-Based RL
por: Sukhija, Bhavya, et al.
Publicado: (2025)
por: Sukhija, Bhavya, et al.
Publicado: (2025)
Optimistic Task Inference for Behavior Foundation Models
por: Rupf, Thomas, et al.
Publicado: (2025)
por: Rupf, Thomas, et al.
Publicado: (2025)
Bayesian Optimistic Optimisation with Exponentially Decaying Regret
por: Tran-The, Hung, et al.
Publicado: (2021)
por: Tran-The, Hung, et al.
Publicado: (2021)
Optimistic Dual Averaging Unifies Modern Optimizers
por: Pethick, Thomas, et al.
Publicado: (2026)
por: Pethick, Thomas, et al.
Publicado: (2026)
Optimistic Learning for Communication Networks
por: Iosifidis, George, et al.
Publicado: (2025)
por: Iosifidis, George, et al.
Publicado: (2025)
Optimistic Model Rollouts for Pessimistic Offline Policy Optimization
por: Zhai, Yuanzhao, et al.
Publicado: (2024)
por: Zhai, Yuanzhao, et al.
Publicado: (2024)
Optimistic Reinforcement Learning with Quantile Objectives
por: Alipour-Vaezi, Mohammad, et al.
Publicado: (2025)
por: Alipour-Vaezi, Mohammad, et al.
Publicado: (2025)
Optimistic Multi-Agent Policy Gradient
por: Zhao, Wenshuai, et al.
Publicado: (2023)
por: Zhao, Wenshuai, et al.
Publicado: (2023)
On Stability in Optimistic Bilevel Optimization
por: Royset, Johannes O.
Publicado: (2024)
por: Royset, Johannes O.
Publicado: (2024)
Optimistic Interior Point Methods for Sequential Hypothesis Testing by Betting
por: Chen, Can, et al.
Publicado: (2025)
por: Chen, Can, et al.
Publicado: (2025)
Optimistic Q-learning for average reward and episodic reinforcement learning
por: Agrawal, Priyank, et al.
Publicado: (2024)
por: Agrawal, Priyank, et al.
Publicado: (2024)
Optimistic Policy Optimization is Provably Efficient in Non-stationary MDPs
por: Zhong, Han, et al.
Publicado: (2021)
por: Zhong, Han, et al.
Publicado: (2021)
Ejemplares similares
-
Optimistic Information Directed Sampling
por: Neu, Gergely, et al.
Publicado: (2024) -
Linear Bandits with Non-i.i.d. Noise
por: Abélès, Baptiste, et al.
Publicado: (2025) -
Optimistically Optimistic Exploration for Provably Efficient Infinite-Horizon Reinforcement and Imitation Learning
por: Moulin, Antoine, et al.
Publicado: (2025) -
Confidence Sequences for Generalized Linear Models via Regret Analysis
por: Clerico, Eugenio, et al.
Publicado: (2025) -
Relative Information Gain and Gaussian Process Regression
por: Flynn, Hamish
Publicado: (2025)