conftrace_

gradient descent

1144 papers

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Also known as

GD

Co-occurring keywords

neural network (6616) neural network optimization (1293) convex optimization (1321) non-convex optimization (547) convergence rate (607) stochastic optimization (1060) convergence analysis (395) stochastic gradient descent (1091) nonconvex optimization (316) implicit bia (107)

Papers

Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent AISTATS 2019
Nonconvex Matrix Factorization from Rank-One Measurements AISTATS 2019
Learning One-hidden-layer ReLU Networks via Gradient Descent AISTATS 2019
Heavy-ball Algorithms Always Escape Saddle Points IJCAI 2019
Differentiable Game Mechanics JMLR 2019
Redundancy Techniques for Straggler Mitigation in Distributed Optimization and Learning JMLR 2019
Convergence Guarantees for a Class of Non-convex and Non-smooth Optimization Problems JMLR 2019
Comparing EM with GD in Mixture Models of Two Components UAI 2019
Projections for Approximate Policy Iteration Algorithms ICML 2019
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path? ICML 2019
Complex Unitary Recurrent Neural Networks Using Scaled Cayley Transform AAAI 2019
Non-Parametric Transformation Networks for Learning General Invariances from Data AAAI 2019
An Optimal Control Approach to Sequential Machine Teaching AISTATS 2019
On the Dynamics of Gradient Descent for Autoencoders AISTATS 2019
Revisit Batch Normalization: New Understanding and Refinement via Composition Optimization AISTATS 2019
Convergence of Gradient Descent on Separable Data AISTATS 2019
Spurious Valleys in One-hidden-layer Neural Network Optimization Landscapes JMLR 2019
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks ICML 2019
Width Provably Matters in Optimization for Deep Linear Neural Networks ICML 2019
Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models ICML 2019
Neuron birth-death dynamics accelerates gradient descent and converges asymptotically ICML 2019
Toward Understanding the Importance of Noise in Training Neural Networks ICML 2019
Searching for a Robust Neural Architecture in Four GPU Hours CVPR 2019
Beyond Gradient Descent for Regularized Segmentation Losses CVPR 2019
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel NIPS 2019