Optimization

The Solution Path Algorithm for Identity-Aware Multi-Object Tracking CVPR 2016 The Sound of APALM Clapping: Faster Nonsmooth Nonconvex Optimization with Stochastic Asynchronous PALM NeurIPS 2016 The Sum-Product Theorem: A Foundation for Learning Tractable Models ICML 2016 Tight Complexity Bounds for Optimizing Composite Objectives NeurIPS 2016 Time series prediction and online learning COLT 2016 Towards Faster Rates and Oracle Property for Low-Rank Matrix Estimation ICML 2016 TPOT: A Tree-based Pipeline Optimization Tool for Automating Machine Learning AutoML 2016 Trace Quotient Meets Sparsity: A Method for Learning Low Dimensional Image Representations CVPR 2016 Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient ICML 2016 Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization AISTATS 2016 Train and Test Tightness of LP Relaxations in Structured Prediction ICML 2016 Train faster, generalize better: Stability of stochastic gradient descent ICML 2016 Training Deep Neural Networks via Direct Loss Minimization ICML 2016 Training Region-Based Object Detectors With Online Hard Example Mining CVPR 2016 Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation NeurIPS 2016 Two-Stage Temporal Processing for Single-Channel Speech Enhancement Interspeech 2016 Unbounded Bayesian Optimization via Regularization AISTATS 2016 Unconstrained Salient Object Detection via Proposal Subset Optimization CVPR 2016 Unitary Evolution Recurrent Neural Networks ICML 2016 Unsupervised Learning from Noisy Networks with Applications to Hi-C Data NeurIPS 2016 Using Kernel Methods and Model Selection for Prediction of Preterm Birth MLHC 2016 Variance-Reduced and Projection-Free Stochastic Optimization ICML 2016 Variance Reduction for Faster Non-Convex Optimization ICML 2016 Variational Tempering AISTATS 2016 Verification Based Solution for Structured MAB Problems NeurIPS 2016