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Stochastic Processes

2,667 papers

Papers per year

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244
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Papers

On Markov Chain Gradient Descent NIPS 2018
Modelling sparsity, heterogeneity, reciprocity and community structure in temporal interaction data NIPS 2018
Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs NIPS 2018
First-order Stochastic Algorithms for Escaping From Saddle Points in Almost Linear Time NIPS 2018
The Convergence of Sparsified Gradient Methods NIPS 2018
The promises and pitfalls of Stochastic Gradient Langevin Dynamics NIPS 2018
Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates NIPS 2018
Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo NIPS 2018
Bandit Learning in Concave N-Person Games NIPS 2018
Approximate Knowledge Compilation by Online Collapsed Importance Sampling NIPS 2018
A probabilistic population code based on neural samples NIPS 2018
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data NIPS 2018
New Insight into Hybrid Stochastic Gradient Descent: Beyond With-Replacement Sampling and Convexity NIPS 2018
PCA of high dimensional random walks with comparison to neural network training NIPS 2018
Multi-armed Bandits with Compensation NIPS 2018
Adaptive Methods for Nonconvex Optimization NIPS 2018
Implicit Reparameterization Gradients NIPS 2018
Entropy Rate Estimation for Markov Chains with Large State Space NIPS 2018
Breaking the Span Assumption Yields Fast Finite-Sum Minimization NIPS 2018
Fast Estimation of Causal Interactions using Wold Processes NIPS 2018
Online Adaptive Methods, Universality and Acceleration NIPS 2018
Reparameterization Gradient for Non-differentiable Models NIPS 2018
Geometrically Coupled Monte Carlo Sampling NIPS 2018
Nonparametric learning from Bayesian models with randomized objective functions NIPS 2018
Infinite-Horizon Gaussian Processes NIPS 2018