Stochastic Methods

Variance Reduction for Stochastic Gradient Optimization NeurIPS 2013 Adaptive MCMC with Bayesian Optimization AISTATS 2012 Adaptive Stratified Sampling for Monte-Carlo integration of Differentiable functions NeurIPS 2012 A Family of MCMC Methods on Implicitly Defined Manifolds AISTATS 2012 A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function NeurIPS 2012 A Stochastic Gradient Method with an Exponential Convergence _Rate for Finite Training Sets NeurIPS 2012 Bandit Theory meets Compressed Sensing for high dimensional Stochastic Linear Bandit AISTATS 2012 Bayesian Quadrature for Ratios AISTATS 2012 Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence NeurIPS 2012 Communication-Efficient Algorithms for Statistical Optimization NeurIPS 2012 Complexity of Bethe Approximation AISTATS 2012 Continuous Relaxations for Discrete Hamiltonian Monte Carlo NeurIPS 2012 DEAP: Evolutionary Algorithms Made Easy JMLR 2012 Distributed Approximation of Joint Measurement Distributions Using Mixtures of Gaussians RSS 2012 Efficient Sampling for Bipartite Matching Problems NeurIPS 2012 Efficient Sampling from Combinatorial Space via Bridging AISTATS 2012 Entropy Estimations Using Correlated Symmetric Stable Random Projections NeurIPS 2012 Error bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert space AISTATS 2012 Fast Resampling Weighted v-Statistics NeurIPS 2012 Feature Clustering for Accelerating Parallel Coordinate Descent NeurIPS 2012 Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods NeurIPS 2012 Interpreting prediction markets: a stochastic approach NeurIPS 2012 Iterative ranking from pair-wise comparisons NeurIPS 2012 Lightning-speed Structure Learning of Nonlinear Continuous Networks AISTATS 2012 MCMC for continuous-time discrete-state systems NeurIPS 2012