stochastic gradient descent

Barzilai-Borwein Step Size for Stochastic Gradient Descent NeurIPS 2016 Black-Box Alpha Divergence Minimization ICML 2016 Conditional Generative Moment-Matching Networks NeurIPS 2016 Convergence of Stochastic Gradient Descent for PCA ICML 2016 DSA: Decentralized Double Stochastic Averaging Gradient Algorithm JMLR 2016 Early Stopping as Nonparametric Variational Inference AISTATS 2016 Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling ICML 2016 Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters NeurIPS 2016 Exponential Family Embeddings NeurIPS 2016 Generalization Properties and Implicit Regularization for Multiple Passes SGM ICML 2016 Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods NeurIPS 2016 Global Optimality of Local Search for Low Rank Matrix Recovery NeurIPS 2016 Hybrid Accelerated Optimization for Speech Recognition Interspeech 2016 Learning a Metric Embedding for Face Recognition using the Multibatch Method NeurIPS 2016 Low-rank tensor completion: a Riemannian manifold preconditioning approach ICML 2016 Multiple Kernel Learning with Data Augmentation ACML 2016 Nonparametric Budgeted Stochastic Gradient Descent AISTATS 2016 Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes NeurIPS 2016 On the Influence of Momentum Acceleration on Online Learning JMLR 2016 Optimal Learning for Multi-pass Stochastic Gradient Methods NeurIPS 2016 Provable Efficient Online Matrix Completion via Non-convex Stochastic Gradient Descent NeurIPS 2016 Rich Component Analysis ICML 2016 Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA AISTATS 2016 Scalable Adaptive Stochastic Optimization Using Random Projections NeurIPS 2016 Scaling-up Empirical Risk Minimization: Optimization of Incomplete U-statistics JMLR 2016