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Stochastic Processes

2,667 papers

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Papers

Tight Bounds for Bandit Combinatorial Optimization COLT 2017
Further and stronger analogy between sampling and optimization: Langevin Monte Carlo and gradient descent COLT 2017
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis COLT 2017
On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities COLT 2017
Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization COLT 2017
The Simulator: Understanding Adaptive Sampling in the Moderate-Confidence Regime COLT 2017
Exploiting 2D Floorplan for Building-Scale Panorama RGBD Alignment CVPR 2017
Multi-Modal Mean-Fields via Cardinality-Based Clamping CVPR 2017
Why ADAGRAD Fails for Online Topic Modeling EMNLP 2017
Uncovering Causality from Multivariate Hawkes Integrated Cumulants ICML 2017
Averaged-DQN: Variance Reduction and Stabilization for Deep Reinforcement Learning ICML 2017
An Alternative Softmax Operator for Reinforcement Learning ICML 2017
Dynamic Word Embeddings ICML 2017
A Distributional Perspective on Reinforcement Learning ICML 2017
Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC ICML 2017
Probabilistic Path Hamiltonian Monte Carlo ICML 2017
Stochastic Variance Reduction Methods for Policy Evaluation ICML 2017
Zonotope Hit-and-run for Efficient Sampling from Projection DPPs ICML 2017
Measuring Sample Quality with Kernels ICML 2017
Consistent On-Line Off-Policy Evaluation ICML 2017
Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo ICML 2017
Variational Inference for Sparse and Undirected Models ICML 2017
Conditional Accelerated Lazy Stochastic Gradient Descent ICML 2017
Algorithmic Stability and Hypothesis Complexity ICML 2017
Stochastic Gradient MCMC Methods for Hidden Markov Models ICML 2017