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Stochastic Processes

2667 directly classified papers

Papers per year

Papers

Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations ICML 2019
Understanding MCMC Dynamics as Flows on the Wasserstein Space ICML 2019
Theoretical guarantees for sampling and inference in generative models with latent diffusions COLT 2019
Learning deep kernels for exponential family densities ICML 2019
Online-Within-Online Meta-Learning NIPS 2019
On Exact Computation with an Infinitely Wide Neural Net NIPS 2019
Privacy Amplification by Mixing and Diffusion Mechanisms NIPS 2019
Cross-sectional Learning of Extremal Dependence among Financial Assets NIPS 2019
Continuous-time Models for Stochastic Optimization Algorithms NIPS 2019
Recovering Bandits NIPS 2019
Optimal Best Markovian Arm Identification with Fixed Confidence NIPS 2019
A Solvable High-Dimensional Model of GAN NIPS 2019
Transfer of Samples in Policy Search via Multiple Importance Sampling ICML 2019
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates NIPS 2019
Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices NIPS 2019
Gradient-based Adaptive Markov Chain Monte Carlo NIPS 2019
Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate NIPS 2019
Parameter elimination in particle Gibbs sampling NIPS 2019
A Generic Acceleration Framework for Stochastic Composite Optimization NIPS 2019
Modelling Stopping Criteria for Search Results using Poisson Processes EMNLP 2019
Private Stochastic Convex Optimization with Optimal Rates NIPS 2019
Online sampling from log-concave distributions NIPS 2019
Integrating Markov processes with structural causal modeling enables counterfactual inference in complex systems NIPS 2019
Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model NIPS 2019
Locality-Sensitive Hashing for f-Divergences: Mutual Information Loss and Beyond NIPS 2019