Optimization & Theory

Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification NeurIPS 2020 Dynamical System Inspired Adaptive Time Stepping Controller for Residual Network Families AAAI 2020 Dynamic Convolution: Attention Over Convolution Kernels CVPR 2020 Dynamic Convolutions: Exploiting Spatial Sparsity for Faster Inference CVPR 2020 Dynamic Data Selection for Curriculum Learning via Ability Estimation EMNLP 2020 Dynamic Hierarchical Mimicking Towards Consistent Optimization Objectives CVPR 2020 Dynamic Network Pruning with Interpretable Layerwise Channel Selection AAAI 2020 Dynamics of Deep Neural Networks and Neural Tangent Hierarchy ICML 2020 EAC-Net: Efficient and Accurate Convolutional Network for Video Recognition AAAI 2020 Early Exiting BERT for Efficient Document Ranking EMNLP 2020 ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks CVPR 2020 EcoNAS: Finding Proxies for Economical Neural Architecture Search CVPR 2020 Edinburgh’s Submissions to the 2020 Machine Translation Efficiency Task ACL 2020 Effective Estimation of Deep Generative Language Models ACL 2020 Effectively Unbiased FID and Inception Score and Where to Find Them CVPR 2020 Efficient Adversarial Training With Transferable Adversarial Examples CVPR 2020 Efficient Algorithms for Device Placement of DNN Graph Operators NeurIPS 2020 Efficient and High-Quality Neural Machine Translation with OpenNMT ACL 2020 Efficient and Modularized Training on FPGA for Real-time Applications IJCAI 2020 Efficient Constituency Parsing by Pointing ACL 2020 EfficientDet: Scalable and Efficient Object Detection CVPR 2020 Efficient EUD Parsing ACL 2020 Efficient Inference For Neural Machine Translation EMNLP 2020 Efficient Learning of Generative Models via Finite-Difference Score Matching NeurIPS 2020 Efficient Low Rank Gaussian Variational Inference for Neural Networks NeurIPS 2020