Stochastic Methods

Stable Coactive Learning via Perturbation ICML 2013 Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization NeurIPS 2013 Stochastic Optimization of PCA with Capped MSG NeurIPS 2013 The Fast Convergence of Incremental PCA NeurIPS 2013 Thompson Sampling for 1-Dimensional Exponential Family Bandits NeurIPS 2013 Trading Computation for Communication: Distributed Stochastic Dual Coordinate Ascent NeurIPS 2013 Variance Reduction for Stochastic Gradient Optimization NeurIPS 2013 Adaptive MCMC with Bayesian Optimization AISTATS 2012 Adaptive Metropolis with Online Relabeling AISTATS 2012 Adaptive Stratified Sampling for Monte-Carlo integration of Differentiable functions NeurIPS 2012 Ancestor Sampling for Particle Gibbs NeurIPS 2012 A Stochastic Bandit Algorithm for Scratch Games ACML 2012 A Stochastic Gradient Method with an Exponential Convergence _Rate for Finite Training Sets NeurIPS 2012 Breaking the Curse of Kernelization: Budgeted Stochastic Gradient Descent for Large-Scale SVM Training JMLR 2012 Confidence-Weighted Linear Classification for Text Categorization JMLR 2012 Confusion-Based Online Learning and a Passive-Aggressive Scheme NeurIPS 2012 Continuous Relaxations for Discrete Hamiltonian Monte Carlo NeurIPS 2012 Efficient Sampling for Bipartite Matching Problems NeurIPS 2012 Entangled Monte Carlo NeurIPS 2012 Entropy Estimations Using Correlated Symmetric Stable Random Projections NeurIPS 2012 Evaluation of marginal likelihoods via the density of states 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 Fully Bayesian inference for neural models with negative-binomial spiking NeurIPS 2012