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Stochastic Processes

2,667 papers

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Papers

From Importance Sampling to Doubly Robust Policy Gradient ICML 2020
Variational Inference for Sequential Data with Future Likelihood Estimates ICML 2020
Online Learning for Active Cache Synchronization ICML 2020
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates ICML 2020
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent ICML 2020
Almost Tune-Free Variance Reduction ICML 2020
AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation ICML 2020
Stochastically Dominant Distributional Reinforcement Learning ICML 2020
Involutive MCMC: a Unifying Framework ICML 2020
Low Bias Low Variance Gradient Estimates for Boolean Stochastic Networks ICML 2020
FormulaZero: Distributionally Robust Online Adaptation via Offline Population Synthesis ICML 2020
On the Generalization Benefit of Noise in Stochastic Gradient Descent ICML 2020
Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies ICML 2020
Non-Stationary Delayed Bandits with Intermediate Observations ICML 2020
Bandits for BMO Functions ICML 2020
Sequential Cooperative Bayesian Inference ICML 2020
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes ICML 2020
The Implicit and Explicit Regularization Effects of Dropout ICML 2020
Batch Stationary Distribution Estimation ICML 2020
On the Noisy Gradient Descent that Generalizes as SGD ICML 2020
Feature Selection using Stochastic Gates ICML 2020
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound ICML 2020
Simultaneous Inference for Massive Data: Distributed Bootstrap ICML 2020
Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support ICML 2020
Variance Reduction and Quasi-Newton for Particle-Based Variational Inference ICML 2020