gradient descent

Rank Aggregation via Heterogeneous Thurstone Preference Models AAAI 2020 Recursive Least-Squares Estimator-Aided Online Learning for Visual Tracking CVPR 2020 Regularized linear autoencoders recover the principal components, eventually NeurIPS 2020 Reparameterizing Mirror Descent as Gradient Descent NeurIPS 2020 Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization NeurIPS 2020 SIGUA: Forgetting May Make Learning with Noisy Labels More Robust ICML 2020 Simple and Effective Regularization Methods for Training on Noisily Labeled Data with Generalization Guarantee ICLR 2020 Smoothness and Stability in GANs ICLR 2020 Sparse and Low-rank Tensor Estimation via Cubic Sketchings AISTATS 2020 Spike-based causal inference for weight alignment ICLR 2020 Stochastic Loss Function AAAI 2020 Stochastic Optimization for Performative Prediction NeurIPS 2020 Streaming Batch Gradient Tracking for Neural Network Training (Student Abstract) AAAI 2020 Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent ICML 2020 The asymptotic spectrum of the Hessian of DNN throughout training ICLR 2020 The estimation error of general first order methods COLT 2020 The Implicit Bias of Depth: How Incremental Learning Drives Generalization ICLR 2020 The interplay between randomness and structure during learning in RNNs NeurIPS 2020 The Performance Analysis of Generalized Margin Maximizers on Separable Data ICML 2020 Tight First- and Second-Order Regret Bounds for Adversarial Linear Bandits NeurIPS 2020 Tree-projected gradient descent for estimating gradient-sparse parameters on graphs COLT 2020 Understanding Attention for Text Classification ACL 2020 Understanding the Disharmony between Weight Normalization Family and Weight Decay AAAI 2020 Unique Properties of Flat Minima in Deep Networks ICML 2020 Why Gradient Clipping Accelerates Training: A Theoretical Justification for Adaptivity ICLR 2020