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Optimization

14,969 papers

Papers per year

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Papers

Weight Agnostic Neural Networks NIPS 2019
DeepWave: A Recurrent Neural-Network for Real-Time Acoustic Imaging NIPS 2019
Double Quantization for Communication-Efficient Distributed Optimization NIPS 2019
Learning to Optimize in Swarms NIPS 2019
Generalized Sliced Wasserstein Distances NIPS 2019
Theoretical Limits of Pipeline Parallel Optimization and Application to Distributed Deep Learning NIPS 2019
Global Sparse Momentum SGD for Pruning Very Deep Neural Networks NIPS 2019
Thompson Sampling and Approximate Inference NIPS 2019
Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks NIPS 2019
Adaptive Gradient-Based Meta-Learning Methods NIPS 2019
Massively scalable Sinkhorn distances via the Nyström method NIPS 2019
Efficient online learning with kernels for adversarial large scale problems NIPS 2019
Primal-Dual Block Generalized Frank-Wolfe NIPS 2019
Blended Matching Pursuit NIPS 2019
Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models NIPS 2019
Online Convex Matrix Factorization with Representative Regions NIPS 2019
Stagewise Training Accelerates Convergence of Testing Error Over SGD NIPS 2019
Multivariate Distributionally Robust Convex Regression under Absolute Error Loss NIPS 2019
Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models NIPS 2019
Efficient Rematerialization for Deep Networks NIPS 2019
Data Efficient Reinforcement Learning for Legged Robots CORL 2019
Bayesian Optimization Meets Riemannian Manifolds in Robot Learning CORL 2019
Provably Robust Blackbox Optimization for Reinforcement Learning CORL 2019
Stochastic Optimal Control as Approximate Input Inference CORL 2019
Quasi-Newton Trust Region Policy Optimization CORL 2019