Optimization & Theory

Optimizing Millions of Hyperparameters by Implicit Differentiation AISTATS 2020 Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains AAAI 2020 Orthogonal Convolutional Neural Networks CVPR 2020 Orthogonal Gradient Descent for Continual Learning AISTATS 2020 Orthogonalized SGD and Nested Architectures for Anytime Neural Networks ICML 2020 Overcoming Multi-Model Forgetting in One-Shot NAS With Diversity Maximization CVPR 2020 Overfitting Can Be Harmless for Basis Pursuit, But Only to a Degree NeurIPS 2020 Overlearning Reveals Sensitive Attributes ICLR 2020 Overview of the SustaiNLP 2020 Shared Task EMNLP 2020 Partial Weight Adaptation for Robust DNN Inference CVPR 2020 Patch Proposal Network for Fast Semantic Segmentation of High-Resolution Images AAAI 2020 PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-Time Execution on Mobile Devices AAAI 2020 Perceptual Quality Assessment of Smartphone Photography CVPR 2020 Plug-and-Play Algorithms for Large-Scale Snapshot Compressive Imaging CVPR 2020 Plug-in, Trainable Gate for Streamlining Arbitrary Neural Networks AAAI 2020 Polylogarithmic width suffices for gradient descent to achieve arbitrarily small test error with shallow ReLU networks ICLR 2020 Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods AAAI 2020 Privacy Amplification via Random Check-Ins NeurIPS 2020 Probing Linguistic Features of Sentence-Level Representations in Neural Relation Extraction ACL 2020 Pruning Filter in Filter NeurIPS 2020 Pruning from Scratch AAAI 2020 Pruning neural networks without any data by iteratively conserving synaptic flow NeurIPS 2020 Pruning Redundant Mappings in Transformer Models via Spectral-Normalized Identity Prior EMNLP 2020 Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT AAAI 2020 Quadtree Generating Networks: Efficient Hierarchical Scene Parsing with Sparse Convolutions WACV 2020