Optimization & Theory

Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation EMNLP 2020 Extreme Tensoring for Low-Memory Preconditioning ICLR 2020 Facet-Aware Evaluation for Extractive Summarization ACL 2020 FastBERT: a Self-distilling BERT with Adaptive Inference Time ACL 2020 Fastened CROWN: Tightened Neural Network Robustness Certificates AAAI 2020 Faster Differentially Private Samplers via Rényi Divergence Analysis of Discretized Langevin MCMC NeurIPS 2020 FASTER Recurrent Networks for Efficient Video Classification AAAI 2020 FastFormers: Highly Efficient Transformer Models for Natural Language Understanding EMNLP 2020 Fast Sparse ConvNets CVPR 2020 Fast Texture Synthesis via Pseudo Optimizer CVPR 2020 FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions CVPR 2020 F-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation CVPR 2020 Feature Variance Regularization: A Simple Way to Improve the Generalizability of Neural Networks AAAI 2020 Fenchel Lifted Networks: A Lagrange Relaxation of Neural Network Training AISTATS 2020 FetchSGD: Communication-Efficient Federated Learning with Sketching ICML 2020 Few Sample Knowledge Distillation for Efficient Network Compression CVPR 2020 Few Shot Network Compression via Cross Distillation AAAI 2020 Fiedler Regularization: Learning Neural Networks with Graph Sparsity ICML 2020 Filter Grafting for Deep Neural Networks CVPR 2020 Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep Neural Networks CVPR 2020 Finding the Optimal Vocabulary Size for Neural Machine Translation EMNLP 2020 Finding trainable sparse networks through Neural Tangent Transfer ICML 2020 Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent ICML 2020 Finite Versus Infinite Neural Networks: an Empirical Study NeurIPS 2020 FIREPruning: Learning-based Filter Pruning for Convolutional Neural Network Compression ACML 2020