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SelectiveNet: A Deep Neural Network with an Integrated Reject Option
v1v2v3v4 (latest)

SelectiveNet: A Deep Neural Network with an Integrated Reject Option

26 January 2019
Yonatan Geifman
Ran El-Yaniv
    CVBMOOD
ArXiv (abs)PDFHTML

Papers citing "SelectiveNet: A Deep Neural Network with an Integrated Reject Option"

50 / 180 papers shown
Title
Conformal Arbitrage: Risk-Controlled Balancing of Competing Objectives in Language Models
Conformal Arbitrage: Risk-Controlled Balancing of Competing Objectives in Language Models
William Overman
Mohsen Bayati
22
0
0
01 Jun 2025
Bounded-Abstention Pairwise Learning to Rank
Bounded-Abstention Pairwise Learning to Rank
Antonio Ferrara
Andrea Pugnana
Francesco Bonchi
Salvatore Ruggieri
22
0
0
29 May 2025
Suitability Filter: A Statistical Framework for Classifier Evaluation in Real-World Deployment Settings
Suitability Filter: A Statistical Framework for Classifier Evaluation in Real-World Deployment Settings
Angéline Pouget
Mohammad Yaghini
Stephan Rabanser
Nicolas Papernot
29
0
0
28 May 2025
Know When to Abstain: Optimal Selective Classification with Likelihood Ratios
Know When to Abstain: Optimal Selective Classification with Likelihood Ratios
Alvin Heng
Harold Soh
110
0
0
21 May 2025
Variational Visual Question Answering
Variational Visual Question Answering
Tobias Jan Wieczorek
Nathalie Daun
Mohammad Emtiyaz Khan
Marcus Rohrbach
OOD
92
0
0
14 May 2025
Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs
Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs
Shenzhi Yang
Bin Liang
An Liu
Lin Gui
Xingkai Yao
Xiaofang Zhang
OODD
198
4
0
18 Apr 2025
Interpretable and Fair Mechanisms for Abstaining Classifiers
Interpretable and Fair Mechanisms for Abstaining Classifiers
Daphne Lenders
Andrea Pugnana
Roberto Pellungrini
Toon Calders
D. Pedreschi
F. Giannotti
FaML
143
1
0
24 Mar 2025
You Only Look Once at Anytime (AnytimeYOLO): Analysis and Optimization of Early-Exits for Object-Detection
You Only Look Once at Anytime (AnytimeYOLO): Analysis and Optimization of Early-Exits for Object-Detection
Daniel Kuhse
Harun Teper
Sebastian Buschjäger
Chien-Yao Wang
Jian-Jia Chen
AAML
118
1
0
21 Mar 2025
Category-free Out-of-Distribution Node Detection with Feature Resonance
Shenzhi Yang
Junbo Zhao
Shouqing Yang
Yixuan Li
Dingyu Yang
Xiaofang Zhang
Haobo Wang
OODD
83
0
0
22 Feb 2025
Out-of-Distribution Detection using Synthetic Data Generation
Out-of-Distribution Detection using Synthetic Data Generation
Momin Abbas
Muneeza Azmat
R. Horesh
Mikhail Yurochkin
174
2
0
05 Feb 2025
Detection of adrenal anomalous findings in spinal CT images using multi model graph aggregation
Detection of adrenal anomalous findings in spinal CT images using multi model graph aggregation
Shabalin Carmel
Shenkman Israel
Shelef Ilan
Ben-Arie Gal
Alex Geftler
Shahar Yuval
MedIm
117
0
0
03 Jan 2025
Calibrating Bayesian Learning via Regularization, Confidence Minimization, and Selective Inference
Calibrating Bayesian Learning via Regularization, Confidence Minimization, and Selective Inference
Jiayi Huang
Sangwoo Park
Osvaldo Simeone
252
2
0
03 Jan 2025
Safety Monitoring of Machine Learning Perception Functions: a Survey
Safety Monitoring of Machine Learning Perception Functions: a Survey
Raul Sena Ferreira
Joris Guérin
Kevin Delmas
Jérémie Guiochet
H. Waeselynck
121
0
0
09 Dec 2024
Improving Predictor Reliability with Selective Recalibration
Improving Predictor Reliability with Selective Recalibration
Thomas P. Zollo
Zhun Deng
Jake C. Snell
T. Pitassi
Richard Zemel
OOD
72
0
0
07 Oct 2024
Look Around and Find Out: OOD Detection with Relative Angles
Look Around and Find Out: OOD Detection with Relative Angles
Berker Demirel
Marco Fumero
Francesco Locatello
111
0
0
06 Oct 2024
Bridging OOD Detection and Generalization: A Graph-Theoretic View
Bridging OOD Detection and Generalization: A Graph-Theoretic View
Han Wang
Yixuan Li
CML
91
2
0
26 Sep 2024
Learning To Help: Training Models to Assist Legacy Devices
Learning To Help: Training Models to Assist Legacy Devices
Yu Wu
Anand Sarwate
63
1
0
24 Sep 2024
Abstaining Machine Learning -- Philosophical Considerations
Abstaining Machine Learning -- Philosophical Considerations
Daniela Schuster
70
0
0
01 Sep 2024
Privacy-preserving Universal Adversarial Defense for Black-box Models
Privacy-preserving Universal Adversarial Defense for Black-box Models
Qiao Li
Yanwei Yue
Jing Chen
Zijun Zhang
Kun He
Ruiying Du
Xinxin Wang
Qingchuang Zhao
Yang Liu
AAML
112
6
0
20 Aug 2024
Your Classifier Can Be Secretly a Likelihood-Based OOD Detector
Your Classifier Can Be Secretly a Likelihood-Based OOD Detector
Jirayu Burapacheep
Yixuan Li
OODD
62
4
0
09 Aug 2024
A3Rank: Augmentation Alignment Analysis for Prioritizing Overconfident
  Failing Samples for Deep Learning Models
A3Rank: Augmentation Alignment Analysis for Prioritizing Overconfident Failing Samples for Deep Learning Models
Zhengyuan Wei
Haipeng Wang
Qili Zhou
William Chan
43
0
0
19 Jul 2024
Realizable $H$-Consistent and Bayes-Consistent Loss Functions for
  Learning to Defer
Realizable HHH-Consistent and Bayes-Consistent Loss Functions for Learning to Defer
Anqi Mao
M. Mohri
Yutao Zhong
67
10
0
18 Jul 2024
Overcoming Common Flaws in the Evaluation of Selective Classification
  Systems
Overcoming Common Flaws in the Evaluation of Selective Classification Systems
Jeremias Traub
Till J. Bungert
Carsten T. Lüth
Michael Baumgartner
Klaus H. Maier-Hein
Lena Maier-Hein
Paul F. Jaeger
74
4
0
01 Jul 2024
Effective Generation of Feasible Solutions for Integer Programming via
  Guided Diffusion
Effective Generation of Feasible Solutions for Integer Programming via Guided Diffusion
Hao Zeng
Jiaqi Wang
Avirup Das
Junying He
Kunpeng Han
Haoyuan Hu
Mingfei Sun
75
2
0
18 Jun 2024
Confidence-aware Contrastive Learning for Selective Classification
Confidence-aware Contrastive Learning for Selective Classification
Yu-Chang Wu
Shen-Huan Lyu
Haopu Shang
Xiangyu Wang
Chao Qian
75
3
0
07 Jun 2024
EMOE: Expansive Matching of Experts for Robust Uncertainty Based
  Rejection
EMOE: Expansive Matching of Experts for Robust Uncertainty Based Rejection
Yunni Qu
James Wellnitz
Alexander Tropsha
Junier Oliva
89
0
0
03 Jun 2024
Selective Explanations
Selective Explanations
Lucas Monteiro Paes
Dennis L. Wei
Flavio du Pin Calmon
FAtt
68
0
0
29 May 2024
A Causal Framework for Evaluating Deferring Systems
A Causal Framework for Evaluating Deferring Systems
Filippo Palomba
Andrea Pugnana
Jose M. Alvarez
Salvatore Ruggieri
CML
142
4
0
29 May 2024
When and How Does In-Distribution Label Help Out-of-Distribution
  Detection?
When and How Does In-Distribution Label Help Out-of-Distribution Detection?
Xuefeng Du
Yiyou Sun
Yixuan Li
75
9
0
28 May 2024
From Conformal Predictions to Confidence Regions
From Conformal Predictions to Confidence Regions
Charles Guille-Escuret
Eugene Ndiaye
109
2
0
28 May 2024
Hierarchical Selective Classification
Hierarchical Selective Classification
Shani Goren
Ido Galil
Ran El-Yaniv
BDL
93
2
0
19 May 2024
Selective Classification Under Distribution Shifts
Selective Classification Under Distribution Shifts
Hengyue Liang
Le Peng
Ju Sun
UQCV
101
2
0
08 May 2024
Taming False Positives in Out-of-Distribution Detection with Human
  Feedback
Taming False Positives in Out-of-Distribution Detection with Human Feedback
Harit Vishwakarma
Heguang Lin
Ramya Korlakai Vinayak
OODD
70
7
0
25 Apr 2024
Uncertainty-Based Abstention in LLMs Improves Safety and Reduces
  Hallucinations
Uncertainty-Based Abstention in LLMs Improves Safety and Reduces Hallucinations
Christian Tomani
Kamalika Chaudhuri
Ivan Evtimov
Daniel Cremers
Mark Ibrahim
107
15
0
16 Apr 2024
Consistency and Uncertainty: Identifying Unreliable Responses From
  Black-Box Vision-Language Models for Selective Visual Question Answering
Consistency and Uncertainty: Identifying Unreliable Responses From Black-Box Vision-Language Models for Selective Visual Question Answering
Zaid Khan
Yun Fu
AAML
83
10
0
16 Apr 2024
Online Safety Analysis for LLMs: a Benchmark, an Assessment, and a Path
  Forward
Online Safety Analysis for LLMs: a Benchmark, an Assessment, and a Path Forward
Xuan Xie
Jiayang Song
Zhehua Zhou
Yuheng Huang
Da Song
Lei Ma
OffRL
128
6
0
12 Apr 2024
Selective Temporal Knowledge Graph Reasoning
Selective Temporal Knowledge Graph Reasoning
Zhongni Hou
Xiaolong Jin
Zixuan Li
Long Bai
Jiafeng Guo
Xueqi Cheng
87
0
0
02 Apr 2024
Regression with Multi-Expert Deferral
Regression with Multi-Expert Deferral
Anqi Mao
M. Mohri
Yutao Zhong
79
14
0
28 Mar 2024
Hyperbolic Metric Learning for Visual Outlier Detection
Hyperbolic Metric Learning for Visual Outlier Detection
Alvaro Gonzalez-Jimenez
Simone Lionetti
Dena Bazazian
Philippe Gottfrois
Fabian Gröger
Marc Pouly
Alexander A. Navarini
81
2
0
22 Mar 2024
Out-of-Distribution Detection Should Use Conformal Prediction (and
  Vice-versa?)
Out-of-Distribution Detection Should Use Conformal Prediction (and Vice-versa?)
Paul Novello
Joseba Dalmau
Léo Andéol
OODD
87
2
0
18 Mar 2024
Advancing Out-of-Distribution Detection through Data Purification and
  Dynamic Activation Function Design
Advancing Out-of-Distribution Detection through Data Purification and Dynamic Activation Function Design
Yingrui Ji
Yao Zhu
Zhigang Li
Jiansheng Chen
Yun-long Kong
Jingbo Chen
OODD
83
0
0
06 Mar 2024
Conformalized Selective Regression
Conformalized Selective Regression
Anna Sokol
Nuno Moniz
Nitesh Chawla
190
1
0
26 Feb 2024
Towards Trustworthy Reranking: A Simple yet Effective Abstention
  Mechanism
Towards Trustworthy Reranking: A Simple yet Effective Abstention Mechanism
Hippolyte Gisserot-Boukhlef
Manuel Faysse
Emmanuel Malherbe
C´eline Hudelot
Pierre Colombo
175
4
0
20 Feb 2024
Soft Dice Confidence: A Near-Optimal Confidence Estimator for Selective Prediction in Semantic Segmentation
Soft Dice Confidence: A Near-Optimal Confidence Estimator for Selective Prediction in Semantic Segmentation
Bruno Laboissiere Camargos Borges
Bruno Machado Pacheco
Danilo Silva
41
0
0
16 Feb 2024
AI, Meet Human: Learning Paradigms for Hybrid Decision Making Systems
AI, Meet Human: Learning Paradigms for Hybrid Decision Making Systems
Clara Punzi
Roberto Pellungrini
Mattia Setzu
F. Giannotti
D. Pedreschi
76
6
0
09 Feb 2024
How Does Unlabeled Data Provably Help Out-of-Distribution Detection?
How Does Unlabeled Data Provably Help Out-of-Distribution Detection?
Xuefeng Du
Zhen Fang
Ilias Diakonikolas
Yixuan Li
OODD
87
29
0
05 Feb 2024
Uncertainty Quantification on Clinical Trial Outcome Prediction
Uncertainty Quantification on Clinical Trial Outcome Prediction
Tianyi Chen
Yingzhou Lu
Nan Hao
Capucine Van Rechem
Jintai Chen
Tianfan Fu
117
23
0
07 Jan 2024
How to Overcome Curse-of-Dimensionality for Out-of-Distribution
  Detection?
How to Overcome Curse-of-Dimensionality for Out-of-Distribution Detection?
Soumya Suvra Ghosal
Yiyou Sun
Yixuan Li
OODD
80
12
0
22 Dec 2023
RankFeat&RankWeight: Rank-1 Feature/Weight Removal for
  Out-of-distribution Detection
RankFeat&RankWeight: Rank-1 Feature/Weight Removal for Out-of-distribution Detection
Yue Song
N. Sebe
Wei Wang
OODD
81
2
0
23 Nov 2023
Model Agnostic Explainable Selective Regression via Uncertainty
  Estimation
Model Agnostic Explainable Selective Regression via Uncertainty Estimation
Andrea Pugnana
Carlos Mougan
Dan Saattrup Nielsen
78
0
0
15 Nov 2023
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