Top-k Multiclass SVM

20 November 2015

Maksim Lapin

Matthias Hein

Bernt Schiele

VLM

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Papers citing "Top-k Multiclass SVM"

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Title
Machine Learning Should Maximize Welfare, but Not by (Only) Maximizing Accuracy Nir Rosenfeld Haifeng Xu FaML HAI 114 2 0 17 Feb 2025
Multi-class Support Vector Machine with Maximizing Minimum Margin Feiping Nie Zhezheng Hao Rong Wang 168 16 0 11 Dec 2023
Optimizing Partial Area Under the Top-k Curve: Theory and Practice Zitai Wang Qianqian Xu Zhiyong Yang Yuan He Xiaochun Cao Qingming Huang 65 7 0 03 Sep 2022
Rank-based Decomposable Losses in Machine Learning: A Survey Shu Hu Xin Wang Siwei Lyu 100 32 0 18 Jul 2022
An Embedding Framework for the Design and Analysis of Consistent Polyhedral Surrogates Jessie Finocchiaro Rafael Frongillo Bo Waggoner 103 14 0 29 Jun 2022
Differentiable Top-k Classification Learning Felix Petersen Hilde Kuehne Christian Borgelt Oliver Deussen 119 32 0 15 Jun 2022
Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity Dixian Zhu Yiming Ying Tianbao Yang 122 11 0 30 Dec 2021
Tensor Normalization and Full Distribution Training Wolfgang Fuhl OOD 92 4 0 06 Sep 2021
sigmoidF1: A Smooth F1 Score Surrogate Loss for Multilabel Classification Gabriel Bénédict Vincent Koops Daan Odijk Maarten de Rijke 92 33 0 24 Aug 2021
T $_k$ ML-AP: Adversarial Attacks to Top- $k$ Multi-Label Learning Shu Hu Lipeng Ke Xin Wang Siwei Lyu VLM AAML 94 34 0 31 Jul 2021
Fine-grained Generalization Analysis of Vector-valued Learning Liang Wu Antoine Ledent Yunwen Lei Marius Kloft 74 10 0 29 Apr 2021
Set-valued classification -- overview via a unified framework Evgenii Chzhen Christophe Denis Mohamed Hebiri Titouan Lorieul 174 34 0 24 Feb 2021
General Framework for Binary Classification on Top Samples Lukáš Adam V. Mácha Václav Smídl Tomás Pevný 47 5 0 25 Feb 2020
An Embedding Framework for Consistent Polyhedral Surrogates Jessie Finocchiaro Rafael Frongillo Bo Waggoner 59 30 0 17 Jul 2019
The Limited Multi-Label Projection Layer Brandon Amos V. Koltun J. Zico Kolter 95 36 0 20 Jun 2019
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations Debraj Basu Deepesh Data C. Karakuş Suhas Diggavi MQ 74 408 0 06 Jun 2019
Learning with Fenchel-Young Losses Mathieu Blondel André F. T. Martins Vlad Niculae 172 137 0 08 Jan 2019
Smooth Loss Functions for Deep Top-k Classification Leonard Berrada Andrew Zisserman M. P. Kumar 74 118 0 21 Feb 2018
tau-FPL: Tolerance-Constrained Learning in Linear Time Ao Zhang Nan Li Jian Pu Jun Wang Junchi Yan H. Zha 32 2 0 15 Jan 2018
Learning with Average Top-k Loss Yanbo Fan Siwei Lyu Yiming Ying Bao-Gang Hu DML 128 105 0 24 May 2017
Analysis and Optimization of Loss Functions for Multiclass, Top-k, and Multilabel Classification Maksim Lapin Matthias Hein Bernt Schiele 87 103 0 12 Dec 2016
The Z-loss: a shift and scale invariant classification loss belonging to the Spherical Family A. D. Brébisson Pascal Vincent 90 10 0 29 Apr 2016
Loss Functions for Top-k Error: Analysis and Insights Maksim Lapin Matthias Hein Bernt Schiele 167 96 0 01 Dec 2015