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Confidence sets with expected sizes for Multiclass Classification
v1v2 (latest)

Confidence sets with expected sizes for Multiclass Classification

31 August 2016
Christophe Denis
Mohamed Hebiri
ArXiv (abs)PDFHTML

Papers citing "Confidence sets with expected sizes for Multiclass Classification"

17 / 17 papers shown
Title
Towards certifiable AI in aviation: landscape, challenges, and
  opportunities
Towards certifiable AI in aviation: landscape, challenges, and opportunities
Hymalai Bello
Daniel Geißler
L. Ray
Stefan Muller-Divéky
Peter Muller
Shannon Kittrell
Mengxi Liu
Bo Zhou
Paul Lukowicz
85
1
0
13 Sep 2024
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
64
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
61
7
0
28 Mar 2024
A two-head loss function for deep Average-K classification
A two-head loss function for deep Average-K classification
Camille Garcin
Maximilien Servajean
Alexis Joly
Joseph Salmon
52
0
0
31 Mar 2023
Learning Acceptance Regions for Many Classes with Anomaly Detection
Learning Acceptance Regions for Many Classes with Anomaly Detection
Zhou Wang
Xingye Qiao
51
1
0
20 Sep 2022
Prediction intervals with controlled length in the heteroscedastic
  Gaussian regression
Prediction intervals with controlled length in the heteroscedastic Gaussian regression
Christophe Denis
Mohamed Hebiri
A. Zaoui
39
0
0
08 Sep 2022
Set-valued prediction in hierarchical classification with constrained
  representation complexity
Set-valued prediction in hierarchical classification with constrained representation complexity
Thomas Mortier
Eyke Hüllermeier
Krzysztof Dembczyñski
Willem Waegeman
119
3
0
13 Mar 2022
Classification Under Ambiguity: When Is Average-K Better Than Top-K?
Classification Under Ambiguity: When Is Average-K Better Than Top-K?
Titouan Lorieul
Alexis Joly
Dennis Shasha
65
1
0
16 Dec 2021
Statistical Guarantees for Fairness Aware Plug-In Algorithms
Statistical Guarantees for Fairness Aware Plug-In Algorithms
Drona Khurana
S. Ravichandran
Sparsh Jain
N. Edakunni
FaML
107
0
0
27 Jul 2021
Posthoc Verification and the Fallibility of the Ground Truth
Posthoc Verification and the Fallibility of the Ground Truth
Yifan Ding
Nicholas Botzer
Tim Weninger
54
5
0
02 Jun 2021
Set-valued classification -- overview via a unified framework
Set-valued classification -- overview via a unified framework
Evgenii Chzhen
Christophe Denis
Mohamed Hebiri
Titouan Lorieul
174
34
0
24 Feb 2021
Selective Classification via One-Sided Prediction
Selective Classification via One-Sided Prediction
Aditya Gangrade
Anil Kag
Venkatesh Saligrama
UQCV
115
36
0
15 Oct 2020
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction
Sangdon Park
Osbert Bastani
Nikolai Matni
Insup Lee
UQCV
248
70
0
31 Dec 2019
Leveraging Labeled and Unlabeled Data for Consistent Fair Binary
  Classification
Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification
Evgenii Chzhen
Christophe Denis
Mohamed Hebiri
L. Oneto
Massimiliano Pontil
FaML
227
87
0
12 Jun 2019
Minimax semi-supervised confidence sets for multi-class classification
Minimax semi-supervised confidence sets for multi-class classification
Evgenii Chzhen
Christophe Denis
Mohamed Hebiri
44
8
0
29 Apr 2019
Stochastic Negative Mining for Learning with Large Output Spaces
Stochastic Negative Mining for Learning with Large Output Spaces
Sashank J. Reddi
Satyen Kale
Felix X. Yu
D. Holtmann-Rice
Jiecao Chen
Sanjiv Kumar
NoLa
89
62
0
16 Oct 2018
Learning Confidence Sets using Support Vector Machines
Learning Confidence Sets using Support Vector Machines
Wenbo Wang
Xingye Qiao
60
13
0
28 Sep 2018
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