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Stochastic Processes

2667 directly classified papers

Papers per year

Papers

Predicting Smoking Events with a Time-Varying Semi-Parametric Hawkes Process Model MLHC 2018
Modeling "Presentness" of Electronic Health Record Data to Improve Patient State Estimation MLHC 2018
Acoustic-Prosodic Features of Tabla Bol Recitation and Correspondence with the Tabla Imitation INTERSPEECH 2018
Structured Gaussian Processes with Twin Multiple Kernel Learning ACML 2018
Infinite-Horizon Gaussian Processes NIPS 2018
Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling ICML 2018
Stochastic Variational Inference With Gradient Linearization CVPR 2018
Fast Monte-Carlo Localization on Aerial Vehicles Using Approximate Continuous Belief Representations CVPR 2018
Modelling sparsity, heterogeneity, reciprocity and community structure in temporal interaction data NIPS 2018
Gradient Diversity: a Key Ingredient for Scalable Distributed Learning AISTATS 2018
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data NIPS 2018
Entropy Rate Estimation for Markov Chains with Large State Space NIPS 2018
Tracking the gradients using the Hessian: A new look at variance reducing stochastic methods AISTATS 2018
Empirical bounds for functions with weak interactions COLT 2018
Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo NIPS 2018
PCA of high dimensional random walks with comparison to neural network training NIPS 2018
Corrupt Bandits for Preserving Local Privacy ALT 2018
The K-Nearest Neighbour UCB Algorithm for Multi-Armed Bandits with Covariates ALT 2018
A Reduction for Efficient LDA Topic Reconstruction NIPS 2018
Convergence of Langevin MCMC in KL-divergence ALT 2018
Implicit Reparameterization Gradients NIPS 2018
Reparameterization Gradient for Non-differentiable Models NIPS 2018
Log-concave sampling: Metropolis-Hastings algorithms are fast! COLT 2018
The Vertex Sample Complexity of Free Energy is Polynomial COLT 2018
Nonparametric learning from Bayesian models with randomized objective functions NIPS 2018