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Stochastic Methods

2,788 papers

Papers per year

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Papers

Online-to-Confidence-Set Conversions and Application to Sparse Stochastic Bandits AISTATS 2012
A Family of MCMC Methods on Implicitly Defined Manifolds AISTATS 2012
Bandit Theory meets Compressed Sensing for high dimensional Stochastic Linear Bandit AISTATS 2012
Error bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert space AISTATS 2012
Lightning-speed Structure Learning of Nonlinear Continuous Networks AISTATS 2012
Scalable Inference on Kingman’s Coalescent using Pair Similarity AISTATS 2012
On Bayesian Upper Confidence Bounds for Bandit Problems AISTATS 2012
Efficient Sampling from Combinatorial Space via Bridging AISTATS 2012
Adaptive MCMC with Bayesian Optimization AISTATS 2012
Bayesian Quadrature for Ratios AISTATS 2012
Complexity of Bethe Approximation AISTATS 2012
Quilting Stochastic Kronecker Product Graphs to Generate Multiplicative Attribute Graphs AISTATS 2012
Toward a Noncommutative Arithmetic-geometric Mean Inequality: Conjectures, Case-studies, and Consequences COLT 2012
Multi Kernel Learning with Online-Batch Optimization JMLR 2012
DEAP: Evolutionary Algorithms Made Easy JMLR 2012
Distributed Approximation of Joint Measurement Distributions Using Mixtures of Gaussians RSS 2012
Optimization-Based Estimator Design for Vision-Aided Inertial Navigation RSS 2012
Hashing Algorithms for Large-Scale Learning NIPS 2011
Sparse Recovery with Brownian Sensing NIPS 2011
Budgeted Optimization with Concurrent Stochastic-Duration Experiments NIPS 2011
Efficient Online Learning via Randomized Rounding NIPS 2011
Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning NIPS 2011
An Application of Tree-Structured Expectation Propagation for Channel Decoding NIPS 2011
Stochastic convex optimization with bandit feedback NIPS 2011
Online Learning: Stochastic, Constrained, and Smoothed Adversaries NIPS 2011