Optimization
Efficient Convex Completion of Coupled Tensors using Coupled Nuclear Norms
Kishan Wimalawarne, Hiroshi Mamitsuka
Neural Information Processing Systems http://nips.cc/
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization
Xiangyi Chen, Sijia Liu, Kaidi Xu, Xingguo Li, Xue Lin, Mingyi Hong, David Cox
Neural Information Processing Systems http://nips.cc/
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries
Zhewei Yao, Amir Gholami, Qi Lei, Kurt Keutzer, Michael W. Mahoney
Neural Information Processing Systems http://nips.cc/
Optimal Scalarizations for Sublinear Hypervolume Regret
To address this, some works have proposed piecewise linear scalar-izations inspired by economics [Busa-Fekete et al., 2017], while for multi-armed bandits, scalarized
Computing Higher Order Derivatives of Matrix and Tensor Expressions
Soeren Laue, Matthias Mitterreiter, Joachim Giesen
Optimization is an integral part of most machine learning systems and most numerical optimization schemes relyonthecomputation ofderivatives.
Learning to Correlate in Multi-Player General-Sum Sequential Games
Andrea Celli, Alberto Marchesi, Tommaso Bianchi, Nicola Gatti
Neural Information Processing Systems http://nips.cc/