Articles citing this article

The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).

Cited article:

For interpolating kernel machines, minimizing the norm of the ERM solution maximizes stability

Akshay Rangamani, Lorenzo Rosasco and Tomaso Poggio
Analysis and Applications 21 (01) 193 (2023)
https://doi.org/10.1142/S0219530522400115

Positive-Unlabeled Learning With Label Distribution Alignment

Yangbangyan Jiang, Qianqian Xu, Yunrui Zhao, Zhiyong Yang, Peisong Wen, Xiaochun Cao and Qingming Huang
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (12) 15345 (2023)
https://doi.org/10.1109/TPAMI.2023.3319431

Learning From Heterogeneous Data Based on Social Interactions Over Graphs

Virginia Bordignon, Stefan Vlaski, Vincenzo Matta and Ali H. Sayed
IEEE Transactions on Information Theory 69 (5) 3347 (2023)
https://doi.org/10.1109/TIT.2022.3232368

Error scaling laws for kernel classification under source and capacity conditions

Hugo Cui, Bruno Loureiro, Florent Krzakala and Lenka Zdeborová
Machine Learning: Science and Technology 4 (3) 035033 (2023)
https://doi.org/10.1088/2632-2153/acf041

Exponential Savings in Agnostic Active Learning Through Abstention

Nikita Puchkin and Nikita Zhivotovskiy
IEEE Transactions on Information Theory 68 (7) 4651 (2022)
https://doi.org/10.1109/TIT.2022.3156592

SVRG meets AdaGrad: painless variance reduction

Benjamin Dubois-Taine, Sharan Vaswani, Reza Babanezhad, Mark Schmidt and Simon Lacoste-Julien
Machine Learning 111 (12) 4359 (2022)
https://doi.org/10.1007/s10994-022-06265-x

Stochastic Difference-of-Convex-Functions Algorithms for Nonconvex Programming

Hoai An Le Thi, Van Ngai Huynh, Tao Pham Dinh and Hoang Phuc Hau Luu
SIAM Journal on Optimization 32 (3) 2263 (2022)
https://doi.org/10.1137/20M1385706

Statistical learning from biased training samples

Stephan Clémençon and Pierre Laforgue
Electronic Journal of Statistics 16 (2) (2022)
https://doi.org/10.1214/22-EJS2084

How Can We Identify the Sparsity Structure Pattern of High-Dimensional Data: an Elementary Statistical Analysis to Interpretable Machine Learning

K. L. Lu
Mathematical Notes 112 (1-2) 223 (2022)
https://doi.org/10.1134/S0001434622070264

Using Locality-Sensitive Hashing for SVM Classification of Large Data Sets

Maria D. Gonzalez-Lima and Carenne C. Ludeña
Mathematics 10 (11) 1812 (2022)
https://doi.org/10.3390/math10111812

Statistical analysis of Mapper for stochastic and multivariate filters

Mathieu Carrière and Bertrand Michel
Journal of Applied and Computational Topology 6 (3) 331 (2022)
https://doi.org/10.1007/s41468-022-00090-w

Machine Learning–Based Feasibility Checks for Dynamic Time Slot Management

Liana van der Hagen, Niels Agatz, Remy Spliet, Thomas R. Visser and Leendert Kok
Transportation Science (2022)
https://doi.org/10.1287/trsc.2022.1183

Machine Learning-Based Feasability Checks for Dynamic Time Slot Management

Liana van der Hagen, Niels A.H. Agatz, Remy Spliet, Thomas Visser and Adrianus Kok
SSRN Electronic Journal (2022)
https://doi.org/10.2139/ssrn.4011237

How isotropic kernels perform on simple invariants

Jonas Paccolat, Stefano Spigler and Matthieu Wyart
Machine Learning: Science and Technology 2 (2) 025020 (2021)
https://doi.org/10.1088/2632-2153/abd485

Model Selection for Treatment Choice: Penalized Welfare Maximization

Eric Mbakop and Max Tabord-Meehan
Econometrica 89 (2) 825 (2021)
https://doi.org/10.3982/ECTA16437

Binary classification with covariate selection through ℓ0-penalised empirical risk minimisation

Le-Yu Chen and Sokbae Lee
The Econometrics Journal 24 (1) 103 (2021)
https://doi.org/10.1093/ectj/utaa017

Random projections: Data perturbation for classification problems

Timothy I. Cannings
WIREs Computational Statistics 13 (1) (2021)
https://doi.org/10.1002/wics.1499

A novel multi-objective forest optimization algorithm for wrapper feature selection

Babak Nouri-Moghaddam, Mehdi Ghazanfari and Mohammad Fathian
Expert Systems with Applications 175 114737 (2021)
https://doi.org/10.1016/j.eswa.2021.114737

Robust k-means clustering for distributions with two moments

Yegor Klochkov, Alexey Kroshnin and Nikita Zhivotovskiy
The Annals of Statistics 49 (4) (2021)
https://doi.org/10.1214/20-AOS2033

Concentration inequalities for two-sample rank processes with application to bipartite ranking

Stephan Clémençon, Myrto Limnios and Nicolas Vayatis
Electronic Journal of Statistics 15 (2) (2021)
https://doi.org/10.1214/21-EJS1907

Belief polarization in a complex world: A learning theory perspective

Nika Haghtalab, Matthew O. Jackson and Ariel D. Procaccia
Proceedings of the National Academy of Sciences 118 (19) (2021)
https://doi.org/10.1073/pnas.2010144118

Sharpness Estimation of Combinatorial Generalization Ability Bounds for Threshold Decision Rules

Sh. Kh. Ishkina and K. V. Vorontsov
Automation and Remote Control 82 (5) 863 (2021)
https://doi.org/10.1134/S0005117921050106

Multiclass Classification by Sparse Multinomial Logistic Regression

Felix Abramovich, Vadim Grinshtein and Tomer Levy
IEEE Transactions on Information Theory 67 (7) 4637 (2021)
https://doi.org/10.1109/TIT.2021.3075137

Fast classification rates without standard margin assumptions

Olivier Bousquet and Nikita Zhivotovskiy
Information and Inference: A Journal of the IMA 10 (4) 1389 (2021)
https://doi.org/10.1093/imaiai/iaab010

An empirical classification procedure for nonparametric mixture models

Qiang Zhao, Rohana J. Karunamuni and Jingjing Wu
Journal of the Korean Statistical Society 49 (3) 924 (2020)
https://doi.org/10.1007/s42952-019-00043-7

Tightening Mutual Information-Based Bounds on Generalization Error

Yuheng Bu, Shaofeng Zou and Venugopal V. Veeravalli
IEEE Journal on Selected Areas in Information Theory 1 (1) 121 (2020)
https://doi.org/10.1109/JSAIT.2020.2991139

Robust statistical learning with Lipschitz and convex loss functions

Geoffrey Chinot, Guillaume Lecué and Matthieu Lerasle
Probability Theory and Related Fields 176 (3-4) 897 (2020)
https://doi.org/10.1007/s00440-019-00931-3

Mining Sequential Patterns with VC-Dimension and Rademacher Complexity

Diego Santoro, Andrea Tonon and Fabio Vandin
Algorithms 13 (5) 123 (2020)
https://doi.org/10.3390/a13050123

Local nearest neighbour classification with applications to semi-supervised learning

Timothy I. Cannings, Thomas B. Berrett and Richard J. Samworth
The Annals of Statistics 48 (3) (2020)
https://doi.org/10.1214/19-AOS1868

Optimal functional supervised classification with separation condition

Sébastien Gadat, Sébastien Gerchinovitz and Clément Marteau
Bernoulli 26 (3) (2020)
https://doi.org/10.3150/19-BEJ1170

Accurate automatic detection of acute lymphatic leukemia using a refined simple classification

F. E. Al‐Tahhan, M. E. Fares, Ali A. Sakr and Doaa A. Aladle
Microscopy Research and Technique 83 (10) 1178 (2020)
https://doi.org/10.1002/jemt.23509

Prediction and Variable Selection in High-Dimensional Misspecified Binary Classification

Konrad Furmańczyk and Wojciech Rejchel
Entropy 22 (5) 543 (2020)
https://doi.org/10.3390/e22050543

Advances in Intelligent Data Analysis XVIII

Alexander Mey, Tom Julian Viering and Marco Loog
Lecture Notes in Computer Science, Advances in Intelligent Data Analysis XVIII 12080 326 (2020)
https://doi.org/10.1007/978-3-030-44584-3_26

Optimal survey schemes for stochastic gradient descent with applications to M-estimation

Stephan Clémençon, Patrice Bertail, Emilie Chautru and Guillaume Papa
ESAIM: Probability and Statistics 23 310 (2019)
https://doi.org/10.1051/ps/2018021

Cause Effect Pairs in Machine Learning

Diviyan Kalainathan, Olivier Goudet, Michèle Sebag and Isabelle Guyon
The Springer Series on Challenges in Machine Learning, Cause Effect Pairs in Machine Learning 155 (2019)
https://doi.org/10.1007/978-3-030-21810-2_4

Multi-scale characterizations of colon polyps via computed tomographic colonography

Weiguo Cao, Marc J. Pomeroy, Yongfeng Gao, et al.
Visual Computing for Industry, Biomedicine, and Art 2 (1) (2019)
https://doi.org/10.1186/s42492-019-0032-7

Relative deviation learning bounds and generalization with unbounded loss functions

Corinna Cortes, Spencer Greenberg and Mehryar Mohri
Annals of Mathematics and Artificial Intelligence 85 (1) 45 (2019)
https://doi.org/10.1007/s10472-018-9613-y

High-Dimensional Classification by Sparse Logistic Regression

Felix Abramovich and Vadim Grinshtein
IEEE Transactions on Information Theory 65 (5) 3068 (2019)
https://doi.org/10.1109/TIT.2018.2884963

Chemical machine learning with kernels: The impact of loss functions

Quang Van Nguyen, Sandip De, Junhong Lin and Volkan Cevher
International Journal of Quantum Chemistry 119 (9) (2019)
https://doi.org/10.1002/qua.25872

Condition-Based Maintenance of Naval Propulsion Systems with supervised Data Analysis

Francesca Cipollini, Luca Oneto, Andrea Coraddu, Alan John Murphy and Davide Anguita
Ocean Engineering 149 268 (2018)
https://doi.org/10.1016/j.oceaneng.2017.12.002

Stability and Minimax Optimality of Tangential Delaunay Complexes for Manifold Reconstruction

Eddie Aamari and Clément Levrard
Discrete & Computational Geometry 59 (4) 923 (2018)
https://doi.org/10.1007/s00454-017-9962-z

The Power of Localization for Efficiently Learning Linear Separators with Noise

Pranjal Awasthi, Maria Florina Balcan and Philip M. Long
Journal of the ACM 63 (6) 1 (2017)
https://doi.org/10.1145/3006384

A Survey of Anticipatory Mobile Networking: Context-Based Classification, Prediction Methodologies, and Optimization Techniques

Nicola Bui, Matteo Cesana, S. Amir Hosseini, et al.
IEEE Communications Surveys & Tutorials 19 (3) 1790 (2017)
https://doi.org/10.1109/COMST.2017.2694140

Entropy “2”-Soft Classification of Objects

Yuri Popkov, Zeev Volkovich, Yuri Dubnov, Renata Avros and Elena Ravve
Entropy 19 (4) 178 (2017)
https://doi.org/10.3390/e19040178

Efficient Regression in Metric Spaces via Approximate Lipschitz Extension

Lee-Ad Gottlieb, Aryeh Kontorovich and Robert Krauthgamer
IEEE Transactions on Information Theory 63 (8) 4838 (2017)
https://doi.org/10.1109/TIT.2017.2713820

Optimal Rates for the Regularized Learning Algorithms under General Source Condition

Abhishake Rastogi and Sivananthan Sampath
Frontiers in Applied Mathematics and Statistics 3 (2017)
https://doi.org/10.3389/fams.2017.00003

Advances in Multimedia Information Processing - PCM 2016

Xiang-Jun Shen, Wen-Chao Zhang, Wei Cai, et al.
Lecture Notes in Computer Science, Advances in Multimedia Information Processing - PCM 2016 9916 211 (2016)
https://doi.org/10.1007/978-3-319-48890-5_21

Classification in general finite dimensional spaces with the k-nearest neighbor rule

Sébastien Gadat, Thierry Klein and Clément Marteau
The Annals of Statistics 44 (3) (2016)
https://doi.org/10.1214/15-AOS1395

Nonparametric Decentralized Detection and Sparse Sensor Selection Via Weighted Kernel

Weiguang Wang, Yingbin Liang, Eric P. Xing and Lixin Shen
IEEE Transactions on Signal Processing 64 (2) 306 (2016)
https://doi.org/10.1109/TSP.2015.2474297

Bidding Wind Energy Exploiting Wind Speed Forecasts

Antonio Giannitrapani, Simone Paoletti, Antonio Vicino and Donato Zarrilli
IEEE Transactions on Power Systems 31 (4) 2647 (2016)
https://doi.org/10.1109/TPWRS.2015.2477942

Неравенства концентрации для выборок без возвращений

Ilya O Tolstikhin and Илья Олегович Толстихин
Теория вероятностей и ее применения 61 (3) 464 (2016)
https://doi.org/10.4213/tvp5069

Minimax fast rates for discriminant analysis with errors in variables

Sébastien Loustau and Clément Marteau
Bernoulli 21 (1) (2015)
https://doi.org/10.3150/13-BEJ564

Bandwidth selection in kernel empirical risk minimization via the gradient

Michaël Chichignoud and Sébastien Loustau
The Annals of Statistics 43 (4) (2015)
https://doi.org/10.1214/15-AOS1318