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Stochastic Processes

2,667 papers

Papers per year

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Papers

Efficient Estimation of Influence of a Training Instance EMNLP 2020
Why bigger is not always better: on finite and infinite neural networks ICML 2020
Restarted Bayesian Online Change-point Detector achieves Optimal Detection Delay ICML 2020
The Implicit Regularization of Stochastic Gradient Flow for Least Squares ICML 2020
Forecasting Sequential Data Using Consistent Koopman Autoencoders ICML 2020
Stochastic Optimization for Regularized Wasserstein Estimators ICML 2020
Option Discovery in the Absence of Rewards with Manifold Analysis ICML 2020
Interference and Generalization in Temporal Difference Learning ICML 2020
The Boomerang Sampler ICML 2020
Calibration, Entropy Rates, and Memory in Language Models ICML 2020
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference ICML 2020
Stochastic Gradient and Langevin Processes ICML 2020
Stochastic Flows and Geometric Optimization on the Orthogonal Group ICML 2020
Online Learning with Dependent Stochastic Feedback Graphs ICML 2020
Momentum Improves Normalized SGD ICML 2020
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC ICML 2020
Cooperative Multi-Agent Bandits with Heavy Tails ICML 2020
Stochastic Regret Minimization in Extensive-Form Games ICML 2020
The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation ICML 2020
Accelerating the diffusion-based ensemble sampling by non-reversible dynamics ICML 2020
Online Multi-Kernel Learning with Graph-Structured Feedback ICML 2020
Gradient Temporal-Difference Learning with Regularized Corrections ICML 2020
Likelihood-free MCMC with Amortized Approximate Ratio Estimators ICML 2020
Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics ICML 2020
Momentum-Based Policy Gradient Methods ICML 2020