conftrace_

posterior sampling

152 papers

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PS

Co-occurring keywords

bayesian inference (1907) markov chain monte carlo (725) regret bound (1926) diffusion model (3751) langevin dynamics (128) inverse problem (240) generative model (2892) reinforcement learning (4352) thompson sampling (237) uncertainty quantification (1393)

Papers

Posterior sampling strategies based on discretized stochastic differential equations for machine learning applications JMLR 2020
Aggregated Gradient Langevin Dynamics AAAI 2020
Distributionally Robust Bayesian Quadrature Optimization AISTATS 2020
Bayesian model predictive control: Efficient model exploration and regret bounds using posterior sampling L4DC 2020
Bandit Algorithms Based on Thompson Sampling for Bounded Reward Distributions ALT 2020
Randomized Exploration in Generalized Linear Bandits AISTATS 2020
Dueling Posterior Sampling for Preference-Based Reinforcement Learning UAI 2020
Sequential Bayesian Experimental Design with Variable Cost Structure NIPS 2020
On Connecting Stochastic Gradient MCMC and Differential Privacy AISTATS 2019
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning NIPS 2019
Communication-Efficient Stochastic Gradient MCMC for Neural Networks AAAI 2019
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments ICML 2019
Computational Separations between Sampling and Optimization NIPS 2019
The Relative Complexity of Maximum Likelihood Estimation, MAP Estimation, and Sampling COLT 2019
Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables ICML 2019
The promises and pitfalls of Stochastic Gradient Langevin Dynamics NIPS 2018
Scalar Posterior Sampling with Applications NIPS 2018
Multiphase MCMC Sampling for Parameter Inference in Nonlinear Ordinary Differential Equations AISTATS 2018
Coordinated Exploration in Concurrent Reinforcement Learning ICML 2018
Post-Inference Prior Swapping ICML 2017
Thompson Sampling for Linear-Quadratic Control Problems AISTATS 2017
Differential Privacy for Bayesian Inference through Posterior Sampling JMLR 2017
Adaptive Information Gathering via Imitation Learning RSS 2017
Optimistic posterior sampling for reinforcement learning: worst-case regret bounds NIPS 2017
Why is Posterior Sampling Better than Optimism for Reinforcement Learning? ICML 2017