Optimization

Learning to See in the Dark CVPR 2018 LEARNING TO SHARE: SIMULTANEOUS PARAMETER TYING AND SPARSIFICATION IN DEEP LEARNING ICLR 2018 Learning to Speed Up Structured Output Prediction ICML 2018 Learning to Teach with Dynamic Loss Functions NeurIPS 2018 Learning Transferable Architectures for Scalable Image Recognition CVPR 2018 Learning with SGD and Random Features NeurIPS 2018 Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games ICML 2018 Leveraged volume sampling for linear regression NeurIPS 2018 Leveraging Well-Conditioned Bases: Streaming and Distributed Summaries in Minkowski p-Norms ICML 2018 LHD: Improving Cache Hit Rate by Maximizing Hit Density NSDI 2018 Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data ICML 2018 Linear Stochastic Approximation: How Far Does Constant Step-Size and Iterate Averaging Go? AISTATS 2018 Lipschitz regularity of deep neural networks: analysis and efficient estimation NeurIPS 2018 Local and Global Optimization Techniques in Graph-Based Clustering CVPR 2018 Local Convergence Properties of SAGA/Prox-SVRG and Acceleration ICML 2018 Local Identifiability of ℓ_1-minimization Dictionary Learning: a Sufficient and Almost Necessary Condition JMLR 2018 Localized Incomplete Multiple Kernel k-means IJCAI 2018 Local Minima, Heavy Tails, and Search Effort for GBFS IJCAI 2018 Logistic Regression: The Importance of Being Improper COLT 2018 Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs NeurIPS 2018 Lower Bounds for Higher-Order Convex Optimization COLT 2018 Machine Learning and Constraint Programming for Relational-To-Ontology Schema Mapping IJCAI 2018 Manifold Structured Prediction NeurIPS 2018 Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step ICLR 2018 Marian: Fast Neural Machine Translation in C++ ACL 2018