Optimization

A Convex Surrogate Operator for General Non-Modular Loss Functions AISTATS 2016 Adapting Multicomponent Predictive Systems using Hybrid Adaptation Strategies with Auto-WEKA in Process Industry AutoML 2016 Adaptive Algorithms for Online Convex Optimization with Long-term Constraints ICML 2016 Adaptive Averaging in Accelerated Descent Dynamics NeurIPS 2016 Adaptive Group Sparsity for Non-Negative Matrix Factorization with Application to Unsupervised Source Separation Interspeech 2016 Adaptive Neural Compilation NeurIPS 2016 Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy NeurIPS 2016 Adaptive Sampling for SGD by Exploiting Side Information ICML 2016 Adaptive Smoothed Online Multi-Task Learning NeurIPS 2016 Additive Approximations in High Dimensional Nonparametric Regression via the SALSA ICML 2016 A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights JMLR 2016 A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016 A General Framework for Constrained Bayesian Optimization using Information-based Search JMLR 2016 A General Optimization Framework for Multi-Document Summarization Using Genetic Algorithms and Swarm Intelligence COLING 2016 Agnostic Estimation for Misspecified Phase Retrieval Models NeurIPS 2016 A Hybrid Causal Search Algorithm for Latent Variable Models PGM 2016 A Hybrid Deep Learning Architecture for Sentiment Analysis COLING 2016 A Kronecker-factored approximate Fisher matrix for convolution layers ICML 2016 Algorithms and matching lower bounds for approximately-convex optimization NeurIPS 2016 Algorithms for Optimizing the Ratio of Submodular Functions ICML 2016 A Light Touch for Heavily Constrained SGD COLT 2016 A Linearly-Convergent Stochastic L-BFGS Algorithm AISTATS 2016 Altruistic Scheduling in Multi-Resource Clusters OSDI 2016 A Minimax Approach to Supervised Learning NeurIPS 2016 A Multi-Batch L-BFGS Method for Machine Learning NeurIPS 2016