Optimization

KCNN: Kernel-wise Quantization to Remarkably Decrease Multiplications in Convolutional Neural Network IJCAI 2019 Kernel Change-point Detection with Auxiliary Deep Generative Models ICLR 2019 L2-Nonexpansive Neural Networks ICLR 2019 Large Margin Training for Attention Based End-to-End Speech Recognition Interspeech 2019 Large-Scale Distributed Second-Order Optimization Using Kronecker-Factored Approximate Curvature for Deep Convolutional Neural Networks CVPR 2019 Large Scale Graph Learning From Smooth Signals ICLR 2019 Large-Scale Home Energy Management Using Entropy-Based Collective Multiagent Deep Reinforcement Learning Framework IJCAI 2019 Large Scale Structure of Neural Network Loss Landscapes NeurIPS 2019 Lazifying Conditional Gradient Algorithms JMLR 2019 Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models NeurIPS 2019 Learning Adaptive Random Features AAAI 2019 Learning Anytime Predictions in Neural Networks via Adaptive Loss Balancing AAAI 2019 Learning a SAT Solver from Single-Bit Supervision ICLR 2019 Learning beamforming in ultrasound imaging MIDL 2019 Learning Deep Priors for Image Dehazing ICCV 2019 Learning Diverse Bayesian Networks AAAI 2019 Learning dynamic polynomial proofs NeurIPS 2019 Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations ICML 2019 Learning (from) Deep Hierarchical Structure among Features AAAI 2019 Learning From Noisy Labels by Regularized Estimation of Annotator Confusion CVPR 2019 Learning Generative Models across Incomparable Spaces ICML 2019 Learning in Non-convex Games with an Optimization Oracle COLT 2019 Learning in the Machine: Random Backpropagation and the Deep Learning Channel (Extended Abstract) IJCAI 2019 Learning Local Descriptors With a CDF-Based Dynamic Soft Margin ICCV 2019 Learning Local Search Heuristics for Boolean Satisfiability NeurIPS 2019