Optimization & Theory

On the Acceleration of Deep Learning Model Parallelism With Staleness CVPR 2020 On the Convergence of SARAH and Beyond AISTATS 2020 On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning AAAI 2020 On The Evaluation of Machine Translation Systems Trained With Back-Translation ACL 2020 On the Generalization Benefit of Noise in Stochastic Gradient Descent ICML 2020 On the Global Convergence of Training Deep Linear ResNets ICLR 2020 On the Interplay Between Fine-tuning and Sentence-level Probing for Linguistic Knowledge in Pre-trained Transformers EMNLP 2020 On the Interplay Between Fine-tuning and Sentence-Level Probing for Linguistic Knowledge in Pre-Trained Transformers EMNLP 2020 On the Learning Property of Logistic and Softmax Losses for Deep Neural Networks AAAI 2020 On the linearity of large non-linear models: when and why the tangent kernel is constant NeurIPS 2020 On the Multiple Descent of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels COLT 2020 On the Optimal Weighted ℓ_2 Regularization in Overparameterized Linear Regression NeurIPS 2020 On the Regularization Properties of Structured Dropout CVPR 2020 On the Sparsity of Neural Machine Translation Models EMNLP 2020 On the training dynamics of deep networks with L_2 regularization NeurIPS 2020 On the Variance of the Adaptive Learning Rate and Beyond ICLR 2020 On the weak link between importance and prunability of attention heads EMNLP 2020 On Translation Invariance in CNNs: Convolutional Layers Can Exploit Absolute Spatial Location CVPR 2020 On Warm-Starting Neural Network Training NeurIPS 2020 Operation-Aware Soft Channel Pruning using Differentiable Masks ICML 2020 Optimal Policy for Deployment of Machine Learning Models on Energy-Bounded Systems IJCAI 2020 Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities NeurIPS 2020 Optimization and Evaluation of an Intelligibility-Improving Signal Processing Approach (IISPA) for the Hurricane Challenge 2.0 with FADE Interspeech 2020 Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks NeurIPS 2020 Optimization Learning: Perspective, Method, and Applications IJCAI 2020