Optimization & Theory

Residual Distillation: Towards Portable Deep Neural Networks without Shortcuts NeurIPS 2020 Resolution Adaptive Networks for Efficient Inference CVPR 2020 Resource-Adaptive Deep Learning for Visual Speech Recognition Interspeech 2020 ReSprop: Reuse Sparsified Backpropagation CVPR 2020 Rethinking Bias-Variance Trade-off for Generalization of Neural Networks ICML 2020 Rethinking Depthwise Separable Convolutions: How Intra-Kernel Correlations Lead to Improved MobileNets CVPR 2020 Rethinking Differentiable Search for Mixed-Precision Neural Networks CVPR 2020 Rethinking Performance Estimation in Neural Architecture Search CVPR 2020 Reverse Engineering Configurations of Neural Text Generation Models ACL 2020 Revisiting Parameter Sharing for Automatic Neural Channel Number Search NeurIPS 2020 Revisiting Saliency Metrics: Farthest-Neighbor Area Under Curve CVPR 2020 RNNs can generate bounded hierarchical languages with optimal memory EMNLP 2020 Robust Deep Learning as Optimal Control: Insights and Convergence Guarantees L4DC 2020 Robust Design of Deep Neural Networks Against Adversarial Attacks Based on Lyapunov Theory CVPR 2020 Robust Low-Rank Discovery of Data-Driven Partial Differential Equations AAAI 2020 Robustness Analysis of Non-Convex Stochastic Gradient Descent using Biased Expectations NeurIPS 2020 Robust Quantization: One Model to Rule Them All NeurIPS 2020 Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization NeurIPS 2020 Rotated Binary Neural Network NeurIPS 2020 Rotation Consistent Margin Loss for Efficient Low-Bit Face Recognition CVPR 2020 RoutedFusion: Learning Real-Time Depth Map Fusion CVPR 2020 RTN: Reparameterized Ternary Network AAAI 2020 SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive Connection NeurIPS 2020 Sample Complexity Bounds for RNNs with Application to Combinatorial Graph Problems (Student Abstract) AAAI 2020 SampleNet: Differentiable Point Cloud Sampling CVPR 2020