Optimization & Theory

KungFu: Making Training in Distributed Machine Learning Adaptive OSDI 2020 L2-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks CVPR 2020 Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks ICML 2020 Language Through a Prism: A Spectral Approach for Multiscale Language Representations NeurIPS 2020 Layerwise Sparse Coding for Pruned Deep Neural Networks with Extreme Compression Ratio AAAI 2020 Learned Image Compression With Discretized Gaussian Mixture Likelihoods and Attention Modules CVPR 2020 Learning a Single Neuron with Gradient Methods COLT 2020 Learning Augmentation Network via Influence Functions CVPR 2020 Learning Better Lossless Compression Using Lossy Compression CVPR 2020 Learning Dynamic Routing for Semantic Segmentation CVPR 2020 Learning Filter Pruning Criteria for Deep Convolutional Neural Networks Acceleration CVPR 2020 Learning from Label Proportions with Consistency Regularization ACML 2020 Learning From Noisy Anchors for One-Stage Object Detection CVPR 2020 Learning in Gated Neural Networks AISTATS 2020 Learning Interpretable Models using Soft Integrity Constraints ACML 2020 Learning Model with Error -- Exposing the Hidden Model of BAYHENN IJCAI 2020 Learning Over-Parametrized Two-Layer Neural Networks beyond NTK COLT 2020 Learning Physics-Guided Face Relighting Under Directional Light CVPR 2020 Learning Rank-1 Diffractive Optics for Single-Shot High Dynamic Range Imaging CVPR 2020 Learning Relationships between Text, Audio, and Video via Deep Canonical Correlation for Multimodal Language Analysis AAAI 2020 Learning Sparse Neural Networks for Better Generalization IJCAI 2020 Learning Student Networks with Few Data AAAI 2020 Learning to Auto Weight: Entirely Data-Driven and Highly Efficient Weighting Framework AAAI 2020 Learning to Evaluate Perception Models Using Planner-Centric Metrics CVPR 2020 Learning to Optimize Non-Rigid Tracking CVPR 2020