Optimization & Theory

One-Shot Marginal MAP Inference in Markov Random Fields UAI 2019 One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers NeurIPS 2019 On Exact Computation with an Infinitely Wide Neural Net NeurIPS 2019 On Implicit Filter Level Sparsity in Convolutional Neural Networks CVPR 2019 Online Normalization for Training Neural Networks NeurIPS 2019 On NMT Search Errors and Model Errors: Cat Got Your Tongue? EMNLP 2019 On Stabilizing Generative Adversarial Training With Noise CVPR 2019 On the Connection Between Learning Two-Layer Neural Networks and Tensor Decomposition AISTATS 2019 On the Continuity of Rotation Representations in Neural Networks CVPR 2019 On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization ICLR 2019 On the Convergence Rate of Training Recurrent Neural Networks NeurIPS 2019 On the Downstream Performance of Compressed Word Embeddings NeurIPS 2019 On the Dynamics of Gradient Descent for Autoencoders AISTATS 2019 Optimization of Inf-Convolution Regularized Nonconvex Composite Problems AISTATS 2019 Optimizing a Speaker Embedding Extractor Through Backend-Driven Regularization Interspeech 2019 Ouroboros: On Accelerating Training of Transformer-Based Language Models NeurIPS 2019 Overcoming Multi-model Forgetting ICML 2019 P2SGrad: Refined Gradients for Optimizing Deep Face Models CVPR 2019 P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification CVPR 2019 Parallel Optimal Transport GAN CVPR 2019 Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning AAAI 2019 Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness Against Adversarial Attack CVPR 2019 Photometric Mesh Optimization for Video-Aligned 3D Object Reconstruction CVPR 2019 Pitfalls in the Evaluation of Sentence Embeddings ACL 2019 Positive-Unlabeled Compression on the Cloud NeurIPS 2019