Optimization & Theory

Accuracy Booster: Performance Boosting using Feature Map Re-calibration WACV 2020 A Context-Aware Loss Function for Action Spotting in Soccer Videos CVPR 2020 AdaBits: Neural Network Quantization With Adaptive Bit-Widths CVPR 2020 AdapterHub: A Framework for Adapting Transformers EMNLP 2020 Adaptive Compression of Word Embeddings ACL 2020 Adaptive Convolutional ReLUs AAAI 2020 Adaptive Loss-Aware Quantization for Multi-Bit Networks CVPR 2020 Adaptive Transformers for Learning Multimodal Representations ACL 2020 AdaTune: Adaptive Tensor Program Compilation Made Efficient NeurIPS 2020 AdderNet: Do We Really Need Multiplications in Deep Learning? CVPR 2020 Addressing Exposure Bias With Document Minimum Risk Training: Cambridge at the WMT20 Biomedical Translation Task EMNLP 2020 A Deep Neural Network Model of Particle Thermal Radiation in Packed Bed AAAI 2020 A Diagnostic Study of Explainability Techniques for Text Classification EMNLP 2020 Adversarial Learning of Privacy-Preserving and Task-Oriented Representations AAAI 2020 Adversarially Robust Distillation AAAI 2020 Adversarial NLI: A New Benchmark for Natural Language Understanding ACL 2020 Adversarial Self-Supervised Data-Free Distillation for Text Classification EMNLP 2020 Adversarial Training is a Form of Data-dependent Operator Norm Regularization NeurIPS 2020 A Formal Hierarchy of RNN Architectures ACL 2020 A Generalized Framework for Edge-Preserving and Structure-Preserving Image Smoothing AAAI 2020 A General System of Differential Equations to Model First-Order Adaptive Algorithms JMLR 2020 A Graduated Filter Method for Large Scale Robust Estimation CVPR 2020 A Greedy Bit-flip Training Algorithm for Binarized Knowledge Graph Embeddings EMNLP 2020 A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth ICML 2020 Amortized variance reduction for doubly stochastic objective UAI 2020