gradient descent

Implicit Regularization in ReLU Networks with the Square Loss COLT 2021 Implicit Regularization in Tensor Factorization ICML 2021 Implicit Sparse Regularization: The Impact of Depth and Early Stopping NeurIPS 2021 Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions L4DC 2021 Influence Selection for Active Learning ICCV 2021 Large Batch Optimization for Deep Learning Using New Complete Layer-Wise Adaptive Rate Scaling AAAI 2021 Large-Scale Meta-Learning with Continual Trajectory Shifting ICML 2021 Learner-Private Convex Optimization ICML 2021 Learning about Word Vector Representations and Deep Learning through Implementing Word2vec NAACL 2021 Learning a Single Neuron with Bias Using Gradient Descent NeurIPS 2021 Learning a Universal Template for Few-shot Dataset Generalization ICML 2021 Learning Graph Neural Networks with Approximate Gradient Descent AAAI 2021 Learning the Dynamics of Time Delay Systems with Trainable Delays L4DC 2021 Learning with Gradient Descent and Weakly Convex Losses AISTATS 2021 Limiting fluctuation and trajectorial stability of multilayer neural networks with mean field training NeurIPS 2021 Linear Convergence of Gradient Methods for Estimating Structured Transition Matrices in High-dimensional Vector Autoregressive Models NeurIPS 2021 Lipschitz normalization for self-attention layers with application to graph neural networks ICML 2021 MARINA: Faster Non-Convex Distributed Learning with Compression ICML 2021 Meta-Learning Bidirectional Update Rules ICML 2021 Meta Learning in the Continuous Time Limit AISTATS 2021 Meta-learning with negative learning rates ICLR 2021 Mirror Descent View for Neural Network Quantization AISTATS 2021 Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks COLT 2021 Multi-Objective Meta Learning NeurIPS 2021 Multi-Receiver Online Bayesian Persuasion ICML 2021