Learning with Average Top-k Loss

Learning with Average Top-k Loss

24 May 2017

Papers citing "Learning with Average Top-k Loss"

11 / 61 papers shown

Title
Ordered SGD: A New Stochastic Optimization Framework for Empirical Risk Minimization Kenji Kawaguchi Haihao Lu ODL 30 62 0 09 Jul 2019
$Stochastic Primal-Dual Algorithms with Faster Convergence than $O(1/\sqrt{T})$ for Problems without Bilinear Structure$ Stochastic Primal-Dual Algorithms with Faster Convergence than $O(1/\sqrt{T})$ for Problems without Bilinear Structure Yan Yan Yi Tian Xu Qihang Lin Lijun Zhang Tianbao Yang 22 35 0 23 Apr 2019
Fairness risk measures Robert C. Williamson A. Menon FaML 20 135 0 24 Jan 2019
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature Franz J. Király Bilal A. Mateen R. Sonabend 20 10 0 18 Dec 2018
Minimizing Close-k Aggregate Loss Improves Classification Bryan He James Zou 32 2 0 01 Nov 2018
Deep Learning from Shallow Dives: Sonar Image Generation and Training for Underwater Object Detection Sejin Lee Byungjae Park Ayoung Kim 11 52 0 18 Oct 2018
Weakly-Convex Concave Min-Max Optimization: Provable Algorithms and Applications in Machine Learning Hassan Rafique Mingrui Liu Qihang Lin Tianbao Yang 15 107 0 04 Oct 2018
Knowledge Integrated Classifier Design Based on Utility Optimization Shaohan Chen Chuanhou Gao 14 0 0 05 Sep 2018
Efficacy of regularized multi-task learning based on SVM models Shaohan Chen Zhou Fang Sijie Lu Chuanhou Gao 13 9 0 31 May 2018
A Univariate Bound of Area Under ROC Siwei Lyu Yiming Ying 17 11 0 16 Apr 2018
Smooth Loss Functions for Deep Top-k Classification Leonard Berrada Andrew Zisserman M. P. Kumar 19 117 0 21 Feb 2018