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  4. Cited By
Fast learning rates for plug-in classifiers

Fast learning rates for plug-in classifiers

17 August 2007
Jean-Yves Audibert
Alexandre B. Tsybakov
ArXiv (abs)PDFHTML

Papers citing "Fast learning rates for plug-in classifiers"

50 / 251 papers shown
The Adaptivity Barrier in Batched Nonparametric Bandits: Sharp Characterization of the Price of Unknown Margin
The Adaptivity Barrier in Batched Nonparametric Bandits: Sharp Characterization of the Price of Unknown Margin
Rong Jiang
Cong Ma
196
0
0
05 Nov 2025
Bridging the Gap between Empirical Welfare Maximization and Conditional Average Treatment Effect Estimation in Policy Learning
Bridging the Gap between Empirical Welfare Maximization and Conditional Average Treatment Effect Estimation in Policy Learning
Masahiro Kato
OffRLCML
328
0
0
30 Oct 2025
Concentration and excess risk bounds for imbalanced classification with synthetic oversampling
Concentration and excess risk bounds for imbalanced classification with synthetic oversampling
Touqeer Ahmad
Mohammadreza M. Kalan
François Portier
Gilles Stupfler
145
1
0
23 Oct 2025
Set to Be Fair: Demographic Parity Constraints for Set-Valued Classification
Set to Be Fair: Demographic Parity Constraints for Set-Valued Classification
Eyal Cohen
Christophe Denis
Mohamed Hebiri
FaML
239
0
0
06 Oct 2025
AdaDetectGPT: Adaptive Detection of LLM-Generated Text with Statistical Guarantees
AdaDetectGPT: Adaptive Detection of LLM-Generated Text with Statistical Guarantees
Hongyi Zhou
Jin Zhu
Pingfan Su
Kai Ye
Ying Yang
Shakeel A O B Gavioli-Akilagun
Chengchun Shi
DeLMO
516
5
0
29 Sep 2025
Unsupervised Domain Adaptation for Binary Classification with an Unobservable Source Subpopulation
Unsupervised Domain Adaptation for Binary Classification with an Unobservable Source Subpopulation
Chao Ying
Jun Jin
H. Zhang
Qinglong Tian
Yanyuan Ma
Yixuan Li
Jiwei Zhao
OOD
358
0
0
24 Sep 2025
Beyond ATE: Multi-Criteria Design for A/B Testing
Beyond ATE: Multi-Criteria Design for A/B Testing
Jiachun Li
Kaining Shi
David Simchi-Levi
148
0
0
06 Sep 2025
Vector preference-based contextual bandits under distributional shifts
Vector preference-based contextual bandits under distributional shifts
Apurv Shukla
P.R. Kumar
OffRL
128
0
0
21 Aug 2025
Bridging Unsupervised and Semi-Supervised Anomaly Detection: A Theoretically-Grounded and Practical Framework with Synthetic Anomalies
Bridging Unsupervised and Semi-Supervised Anomaly Detection: A Theoretically-Grounded and Practical Framework with Synthetic Anomalies
Matthew Lau
Tian-Yi Zhou
Xiangchi Yuan
Jizhou Chen
Wenke Lee
Xiaoming Huo
262
0
0
16 Jun 2025
Batched Nonparametric Bandits via k-Nearest Neighbor UCB
Batched Nonparametric Bandits via k-Nearest Neighbor UCB
Sakshi Arya
OffRL
363
1
0
15 May 2025
Super-fast rates of convergence for Neural Networks Classifiers under the Hard Margin Condition
Super-fast rates of convergence for Neural Networks Classifiers under the Hard Margin Condition
Nathanael Tepakbong
Ding-Xuan Zhou
Xiang Zhou
458
0
0
13 May 2025
Learning Guarantee of Reward Modeling Using Deep Neural Networks
Learning Guarantee of Reward Modeling Using Deep Neural Networks
Yuanhang Luo
Yeheng Ge
Ruijian Han
Guohao Shen
277
2
0
10 May 2025
Test-time Correlation Alignment
Test-time Correlation Alignment
Linjing You
Jiabao Lu
Xiayuan Huang
OOD
571
3
0
01 May 2025
Empirical risk minimization algorithm for multiclass classification of S.D.E. paths
Empirical risk minimization algorithm for multiclass classification of S.D.E. paths
Christophe Denis
Eddy Ella Mintsa
233
1
0
18 Mar 2025
Locally Private Nonparametric Contextual Multi-armed Bandits
Locally Private Nonparametric Contextual Multi-armed Bandits
Hanfang Yang
Feiyu Jiang
Zifeng Zhao
Yuheng Ma
Y. Yu
484
0
0
11 Mar 2025
Conformal Prediction Under Generalized Covariate Shift with Posterior Drift
Conformal Prediction Under Generalized Covariate Shift with Posterior DriftInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Baozhen Wang
Xingye Qiao
501
1
0
25 Feb 2025
Explaining the Success of Nearest Neighbor Methods in Prediction
Explaining the Success of Nearest Neighbor Methods in Prediction
George H. Chen
Devavrat Shah
OOD
979
155
0
21 Feb 2025
Multivariate root-n-consistent smoothing parameter free matching estimators and estimators of inverse density weighted expectations
Multivariate root-n-consistent smoothing parameter free matching estimators and estimators of inverse density weighted expectations
H. Holzmann
A. Meister
322
1
0
17 Feb 2025
Understanding Scaling Laws with Statistical and Approximation Theory for
  Transformer Neural Networks on Intrinsically Low-dimensional Data
Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional DataNeural Information Processing Systems (NeurIPS), 2024
Alex Havrilla
Wenjing Liao
327
22
0
11 Nov 2024
Accounting for Missing Covariates in Heterogeneous Treatment Estimation
Accounting for Missing Covariates in Heterogeneous Treatment Estimation
Khurram Yamin
Vibhhu Sharma
Ed Kennedy
Bryan Wilder
162
0
0
21 Oct 2024
Linear Contextual Bandits with Interference
Linear Contextual Bandits with Interference
Yang Xu
Wenbin Lu
Rui Song
357
4
0
24 Sep 2024
The Central Role of the Loss Function in Reinforcement Learning
The Central Role of the Loss Function in Reinforcement Learning
Kaiwen Wang
Nathan Kallus
Wen Sun
OffRL
738
14
0
19 Sep 2024
Optimal Classification-based Anomaly Detection with Neural Networks:
  Theory and Practice
Optimal Classification-based Anomaly Detection with Neural Networks: Theory and Practice
Tian-Yi Zhou
Matthew Lau
Jizhou Chen
Wenke Lee
Xiaoming Huo
296
2
0
13 Sep 2024
Contextual Bandits for Unbounded Context Distributions
Contextual Bandits for Unbounded Context Distributions
Puning Zhao
Yan Han
Zhe Liu
Huiwen Wu
Qin Zhang
Zong Ke
Tianhang Zheng
662
16
0
19 Aug 2024
A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer
  Problems
A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problems
Mohammad-Amin Charusaie
Samira Samadi
308
5
0
17 Jul 2024
Minimax And Adaptive Transfer Learning for Nonparametric Classification
  under Distributed Differential Privacy Constraints
Minimax And Adaptive Transfer Learning for Nonparametric Classification under Distributed Differential Privacy Constraints
Arnab Auddy
T. T. Cai
Abhinav Chakraborty
325
7
0
28 Jun 2024
Highest Probability Density Conformal Regions
Highest Probability Density Conformal Regions
Max Sampson
Kung-Sik Chan
219
0
0
12 Jun 2024
Learning with User-Level Local Differential Privacy
Learning with User-Level Local Differential Privacy
Puning Zhao
Li Shen
Rongfei Fan
Qingming Li
Huiwen Wu
Yan Han
Zhe Liu
245
5
0
27 May 2024
Harnessing the Power of Vicinity-Informed Analysis for Classification
  under Covariate Shift
Harnessing the Power of Vicinity-Informed Analysis for Classification under Covariate Shift
Mitsuhiro Fujikawa
Yohei Akimoto
Jun Sakuma
Kazuto Fukuchi
266
1
0
27 May 2024
Contextual Linear Optimization with Partial Feedback
Contextual Linear Optimization with Partial Feedback
Yichun Hu
Nathan Kallus
Xiaojie Mao
Yanchen Wu
458
0
0
26 May 2024
Discriminative Estimation of Total Variation Distance: A Fidelity
  Auditor for Generative Data
Discriminative Estimation of Total Variation Distance: A Fidelity Auditor for Generative Data
Lan Tao
Shi Xu
ChiHua Wang
Namjoon Suh
Guang Cheng
384
8
0
24 May 2024
Error Exponent in Agnostic PAC Learning
Error Exponent in Agnostic PAC Learning
Adi Hendel
Meir Feder
198
0
0
01 May 2024
Robust performance metrics for imbalanced classification problems
Robust performance metrics for imbalanced classification problems
H. Holzmann
Bernhard Klar
162
8
0
11 Apr 2024
Statistical Inference of Optimal Allocations I: Regularities and their Implications
Statistical Inference of Optimal Allocations I: Regularities and their Implications
Kai Feng
Han Hong
Denis Nekipelov
251
1
0
27 Mar 2024
On the rates of convergence for learning with convolutional neural networks
On the rates of convergence for learning with convolutional neural networks
Yunfei Yang
Han Feng
Ding-Xuan Zhou
455
4
0
25 Mar 2024
Auditing Fairness under Unobserved Confounding
Auditing Fairness under Unobserved ConfoundingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Yewon Byun
Dylan Sam
Michael Oberst
Zachary Chase Lipton
Bryan Wilder
307
9
0
18 Mar 2024
Batched Nonparametric Contextual Bandits
Batched Nonparametric Contextual Bandits
Rong Jiang
Cong Ma
OffRL
525
4
0
27 Feb 2024
A hierarchical decomposition for explaining ML performance discrepancies
A hierarchical decomposition for explaining ML performance discrepancies
Jean Feng
Harvineet Singh
Fan Xia
Adarsh Subbaswamy
Alexej Gossmann
CML
279
4
0
22 Feb 2024
Differentially Private High Dimensional Bandits
Differentially Private High Dimensional Bandits
Apurv Shukla
227
0
0
06 Feb 2024
The Optimality of Kernel Classifiers in Sobolev Space
The Optimality of Kernel Classifiers in Sobolev Space
Jianfa Lai
Zhifan Li
Dongming Huang
Qian Lin
284
1
0
02 Feb 2024
A Survey on Statistical Theory of Deep Learning: Approximation, Training
  Dynamics, and Generative Models
A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative ModelsAnnual Review of Statistics and Its Application (ARSIA), 2024
Namjoon Suh
Guang Cheng
MedIm
464
22
0
14 Jan 2024
Universal Consistency of Wide and Deep ReLU Neural Networks and Minimax
  Optimal Convergence Rates for Kolmogorov-Donoho Optimal Function Classes
Universal Consistency of Wide and Deep ReLU Neural Networks and Minimax Optimal Convergence Rates for Kolmogorov-Donoho Optimal Function ClassesInternational Conference on Machine Learning (ICML), 2024
Hyunouk Ko
Xiaoming Huo
296
1
0
08 Jan 2024
Estimation of subsidiary performance metrics under optimal policies
Estimation of subsidiary performance metrics under optimal policiesStatistica sinica (SS), 2024
Zhaoqi Li
Houssam Nassif
Alex Luedtke
217
5
0
08 Jan 2024
On Rate-Optimal Partitioning Classification from Observable and from Privatised Data
On Rate-Optimal Partitioning Classification from Observable and from Privatised Data
Balázs Csanád Csáji
László Gyorfi
Ambrus Tamás
Harro Walk
335
0
0
22 Dec 2023
Statistical learning by sparse deep neural networks
Statistical learning by sparse deep neural networks
Felix Abramovich
BDL
244
1
0
15 Nov 2023
Nonparametric active learning for cost-sensitive classification
Nonparametric active learning for cost-sensitive classification
Boris Ndjia Njike
Xavier Siebert
251
0
0
30 Sep 2023
Nonparametric estimation of a covariate-adjusted counterfactual
  treatment regimen response curve
Nonparametric estimation of a covariate-adjusted counterfactual treatment regimen response curve
Ashkan Ertefaie
Luke Duttweiler
Brent A. Johnson
Mark van der Laan
222
0
0
28 Sep 2023
On Excess Risk Convergence Rates of Neural Network Classifiers
On Excess Risk Convergence Rates of Neural Network Classifiers
Hyunouk Ko
Namjoon Suh
X. Huo
215
3
0
26 Sep 2023
Fast and Multiphase Rates for Nearest Neighbor Classifiers
Fast and Multiphase Rates for Nearest Neighbor ClassifiersAnnual Conference Computational Learning Theory (COLT), 2023
Pengkun Yang
J.N. Zhang
607
0
0
16 Aug 2023
Classification of Data Generated by Gaussian Mixture Models Using Deep
  ReLU Networks
Classification of Data Generated by Gaussian Mixture Models Using Deep ReLU NetworksJournal of machine learning research (JMLR), 2023
Tiancong Zhou
X. Huo
229
5
0
15 Aug 2023
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