Optimization & Theory

Structured Convolutions for Efficient Neural Network Design NeurIPS 2020 Structured Multi-Hashing for Model Compression CVPR 2020 Successfully Applying the Stabilized Lottery Ticket Hypothesis to the Transformer Architecture ACL 2020 Taylor Expansion Policy Optimization ICML 2020 T-Basis: a Compact Representation for Neural Networks ICML 2020 TBT: Targeted Neural Network Attack With Bit Trojan CVPR 2020 TEINet: Towards an Efficient Architecture for Video Recognition AAAI 2020 Tensorized Embedding Layers EMNLP 2020 TernaryBERT: Distillation-aware Ultra-low Bit BERT EMNLP 2020 TESA: Tensor Element Self-Attention via Matricization CVPR 2020 The asymptotic spectrum of the Hessian of DNN throughout training ICLR 2020 The Cascade Transformer: an Application for Efficient Answer Sentence Selection ACL 2020 The EOS Decision and Length Extrapolation EMNLP 2020 The HSIC Bottleneck: Deep Learning without Back-Propagation AAAI 2020 The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent ICML 2020 The Implicit and Explicit Regularization Effects of Dropout ICML 2020 The Knowledge Within: Methods for Data-Free Model Compression CVPR 2020 The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks ICML 2020 The NiuTrans System for WNGT 2020 Efficiency Task ACL 2020 The phase diagram of approximation rates for deep neural networks NeurIPS 2020 There and Back Again: Revisiting Backpropagation Saliency Methods CVPR 2020 The Right Tool for the Job: Matching Model and Instance Complexities ACL 2020 The Statistical Complexity of Early-Stopped Mirror Descent NeurIPS 2020 The Surprising Simplicity of the Early-Time Learning Dynamics of Neural Networks NeurIPS 2020 The Tree Ensemble Layer: Differentiability meets Conditional Computation ICML 2020