← Optimization & Theory
Machine Learning › Optimization & Theory ›

Stochastic Processes

2667 directly classified papers

Papers per year

Papers

Tight Bounds for Bandit Combinatorial Optimization 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
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
Probabilistic Completeness of Randomized Possibility Graphs Applied to Bipedal Walking in Semi-unstructured Environments RSS 2017
Collisions as Information Sources in Densely Packed Multi-Robot Systems Under Mean-Field Approximations RSS 2017
Experience-driven Predictive Control with Robust Constraint Satisfaction under Time-Varying State Uncertainty RSS 2017
Evaluating Trajectory Collision Probability through Adaptive Importance Sampling for Safe Motion Planning RSS 2017
The NTNU System at SemEval-2017 Task 10: Extracting Keyphrases and Relations from Scientific Publications Using Multiple Conditional Random Fields SEMEVAL 2017
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks NIPS 2017
A Distributional Perspective on Reinforcement Learning ICML 2017
An Alternative Softmax Operator for Reinforcement Learning ICML 2017
A-NICE-MC: Adversarial Training for MCMC NIPS 2017
Reducing Reparameterization Gradient Variance NIPS 2017
Averaged-DQN: Variance Reduction and Stabilization for Deep Reinforcement Learning ICML 2017
Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models NIPS 2017
Tomography of the London Underground: a Scalable Model for Origin-Destination Data NIPS 2017
Annular Augmentation Sampling AISTATS 2017
Quantifying the accuracy of approximate diffusions and Markov chains AISTATS 2017
Markov Chain Truncation for Doubly-Intractable Inference AISTATS 2017
Unsupervised Sequential Sensor Acquisition AISTATS 2017
Black-box Importance Sampling AISTATS 2017
Linking Micro Event History to Macro Prediction in Point Process Models AISTATS 2017