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Stochastic Processes

2,667 papers

Papers per year

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Papers

Generative Modeling by Estimating Gradients of the Data Distribution NIPS 2019
Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees NIPS 2019
Exponentially convergent stochastic k-PCA without variance reduction NIPS 2019
Private Stochastic Convex Optimization with Optimal Rates NIPS 2019
A Generic Acceleration Framework for Stochastic Composite Optimization NIPS 2019
Parameter elimination in particle Gibbs sampling NIPS 2019
Mutually Regressive Point Processes NIPS 2019
Neural Jump Stochastic Differential Equations NIPS 2019
Large Scale Markov Decision Processes with Changing Rewards NIPS 2019
Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate NIPS 2019
Gradient-based Adaptive Markov Chain Monte Carlo NIPS 2019
Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices NIPS 2019
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates NIPS 2019
A Solvable High-Dimensional Model of GAN NIPS 2019
Optimal Best Markovian Arm Identification with Fixed Confidence NIPS 2019
Uncertainty on Asynchronous Time Event Prediction NIPS 2019
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation NIPS 2019
Maximum Mean Discrepancy Gradient Flow NIPS 2019
Recovering Bandits NIPS 2019
Nonparametric Regressive Point Processes Based on Conditional Gaussian Processes NIPS 2019
Continuous-time Models for Stochastic Optimization Algorithms NIPS 2019
Integer Discrete Flows and Lossless Compression NIPS 2019
Accurate Layerwise Interpretable Competence Estimation NIPS 2019
Fast and Accurate Stochastic Gradient Estimation NIPS 2019
A Family of Robust Stochastic Operators for Reinforcement Learning NIPS 2019