gradient descent

Metamers of neural networks reveal divergence from human perceptual systems NeurIPS 2019 Multiclass Boosting: Margins, Codewords, Losses, and Algorithms JMLR 2019 Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation NeurIPS 2019 Multivariate Triangular Quantile Maps for Novelty Detection NeurIPS 2019 Negative Momentum for Improved Game Dynamics AISTATS 2019 Neural network gradient-based learning of black-box function interfaces ICLR 2019 Neuron birth-death dynamics accelerates gradient descent and converges asymptotically ICML 2019 Nonconvex Low-Rank Tensor Completion from Noisy Data NeurIPS 2019 Nonconvex Matrix Factorization from Rank-One Measurements AISTATS 2019 Non-Parametric Transformation Networks for Learning General Invariances from Data AAAI 2019 On Learning Over-parameterized Neural Networks: A Functional Approximation Perspective NeurIPS 2019 On the Connection Between Learning Two-Layer Neural Networks and Tensor Decomposition AISTATS 2019 On the Dynamics of Gradient Descent for Autoencoders AISTATS 2019 On the Power and Limitations of Random Features for Understanding Neural Networks NeurIPS 2019 Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path? ICML 2019 Predicting Hurricane Trajectories Using a Recurrent Neural Network AAAI 2019 Projections for Approximate Policy Iteration Algorithms ICML 2019 Provable Non-linear Inductive Matrix Completion NeurIPS 2019 Redundancy Techniques for Straggler Mitigation in Distributed Optimization and Learning JMLR 2019 Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel NeurIPS 2019 Revisit Batch Normalization: New Understanding and Refinement via Composition Optimization AISTATS 2019 Robust and Communication-Efficient Collaborative Learning NeurIPS 2019 Searching for a Robust Neural Architecture in Four GPU Hours CVPR 2019 Sever: A Robust Meta-Algorithm for Stochastic Optimization ICML 2019 Shadowing Properties of Optimization Algorithms NeurIPS 2019