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Stochastic Processes

2667 directly classified papers

Papers per year

Papers

Robust Monte Carlo Sampling using Riemannian Nosé-Poincaré Hamiltonian Dynamics ICML 2016
Weak Convergence Properties of Constrained Emphatic Temporal-difference Learning with Constant and Slowly Diminishing Stepsize JMLR 2016
Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling ICML 2016
On collapsed representation of hierarchical Completely Random Measures ICML 2016
A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order NIPS 2016
Softened Approximate Policy Iteration for Markov Games ICML 2016
No-Regret Algorithms for Heavy-Tailed Linear Bandits ICML 2016
SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization ICML 2016
On Graduated Optimization for Stochastic Non-Convex Problems ICML 2016
RNN-BLSTM Based Multi-Pitch Estimation INTERSPEECH 2016
Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues ICML 2016
Isotonic Hawkes Processes ICML 2016
Scalable Discrete Sampling as a Multi-Armed Bandit Problem ICML 2016
Stance Classification in Rumours as a Sequential Task Exploiting the Tree Structure of Social Media Conversations COLING 2016
A Variational Analysis of Stochastic Gradient Algorithms ICML 2016
Partition Functions from Rao-Blackwellized Tempered Sampling ICML 2016
Markov-modulated Marked Poisson Processes for Check-in Data ICML 2016
Deep Gaussian Processes for Regression using Approximate Expectation Propagation ICML 2016
Mixing Rates for the Alternating Gibbs Sampler over Restricted Boltzmann Machines and Friends ICML 2016
Linear dynamical neural population models through nonlinear embeddings NIPS 2016
Universal Models of Multivariate Temporal Point Processes AISTATS 2016
A Template-Based Approach for Speech Synthesis Intonation Generation Using LSTMs INTERSPEECH 2016
Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series MLHC 2016
Consistently Estimating Markov Chains with Noisy Aggregate Data AISTATS 2016
Time series prediction and online learning COLT 2016