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Consistent Polyhedral Surrogates for Top-$k$ Classification and Variants

Consistent Polyhedral Surrogates for Top-kkk Classification and Variants

18 July 2022
Jessie Finocchiaro
Rafael Frongillo
Emma R Goodwill
Anish Thilagar
ArXivPDFHTML

Papers citing "Consistent Polyhedral Surrogates for Top-$k$ Classification and Variants"

7 / 7 papers shown
Title
Establishing Linear Surrogate Regret Bounds for Convex Smooth Losses via Convolutional Fenchel-Young Losses
Establishing Linear Surrogate Regret Bounds for Convex Smooth Losses via Convolutional Fenchel-Young Losses
Yuzhou Cao
Han Bao
Lei Feng
Bo An
29
0
0
14 May 2025
Cardinality-Aware Set Prediction and Top-$k$ Classification
Cardinality-Aware Set Prediction and Top-kkk Classification
Corinna Cortes
Anqi Mao
Christopher Mohri
M. Mohri
Yutao Zhong
38
7
0
09 Jul 2024
Top-$k$ Classification and Cardinality-Aware Prediction
Top-kkk Classification and Cardinality-Aware Prediction
Anqi Mao
M. Mohri
Yutao Zhong
36
7
0
28 Mar 2024
Online Structured Prediction with Fenchel--Young Losses and Improved
  Surrogate Regret for Online Multiclass Classification with Logistic Loss
Online Structured Prediction with Fenchel--Young Losses and Improved Surrogate Regret for Online Multiclass Classification with Logistic Loss
Shinsaku Sakaue
Han Bao
Taira Tsuchiya
Taihei Oki
32
4
0
13 Feb 2024
Cross-Entropy Loss Functions: Theoretical Analysis and Applications
Cross-Entropy Loss Functions: Theoretical Analysis and Applications
Anqi Mao
M. Mohri
Yutao Zhong
AAML
29
279
0
14 Apr 2023
An Embedding Framework for the Design and Analysis of Consistent
  Polyhedral Surrogates
An Embedding Framework for the Design and Analysis of Consistent Polyhedral Surrogates
Jessie Finocchiaro
Rafael Frongillo
Bo Waggoner
22
14
0
29 Jun 2022
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
313
39,252
0
01 Sep 2014
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