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1012.0729
Cited By
Agnostic Learning of Monomials by Halfspaces is Hard
3 December 2010
Vitaly Feldman
V. Guruswami
P. Raghavendra
Yi Wu
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Papers citing
"Agnostic Learning of Monomials by Halfspaces is Hard"
50 / 53 papers shown
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Smoothed Analysis for Learning Concepts with Low Intrinsic Dimension
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Hardness of Learning Boolean Functions from Label Proportions
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On Learning Latent Models with Multi-Instance Weak Supervision
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An efficient, provably optimal algorithm for the 0-1 loss linear classification problem
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Does it pay to optimize AUC?
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Steven Skiena
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Fine-grained Analysis of Non-parametric Estimation for Pairwise Learning
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Shuo Huang
Han Feng
Puyu Wang
Ding-Xuan Zhou
467
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31 May 2023
A Moment-Matching Approach to Testable Learning and a New Characterization of Rademacher Complexity
Symposium on the Theory of Computing (STOC), 2022
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Adam R. Klivans
Pravesh Kothari
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191
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23 Nov 2022
Symbolic Regression is NP-hard
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03 Jul 2022
Multiclass learning with margin: exponential rates with no bias-variance trade-off
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Stefano Vigogna
Giacomo Meanti
Ernesto De Vito
Lorenzo Rosasco
199
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03 Feb 2022
Minimax risk classifiers with 0-1 loss
Journal of machine learning research (JMLR), 2022
Santiago Mazuelas
Mauricio Romero
Peter Grünwald
670
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17 Jan 2022
Boosting in the Presence of Massart Noise
Annual Conference Computational Learning Theory (COLT), 2021
Ilias Diakonikolas
R. Impagliazzo
D. Kane
Rex Lei
Jessica Sorrell
Christos Tzamos
156
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14 Jun 2021
Statistical optimality conditions for compressive ensembles
Henry W. J. Reeve
A. Kabán
230
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A Symmetric Loss Perspective of Reliable Machine Learning
Nontawat Charoenphakdee
Jongyeong Lee
Masashi Sugiyama
320
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Provably Training Overparameterized Neural Network Classifiers with Non-convex Constraints
Electronic Journal of Statistics (EJS), 2020
You-Lin Chen
Zhaoran Wang
Mladen Kolar
243
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30 Dec 2020
Fair for All: Best-effort Fairness Guarantees for Classification
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
A. Krishnaswamy
Zhihao Jiang
Kangning Wang
Yu Cheng
Kamesh Munagala
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671
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18 Dec 2020
PAC-Learning for Strategic Classification
International Conference on Machine Learning (ICML), 2020
Ravi Sundaram
A. Vullikanti
Haifeng Xu
Fan Yao
AAML
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06 Dec 2020
The Complexity of Adversarially Robust Proper Learning of Halfspaces with Agnostic Noise
Neural Information Processing Systems (NeurIPS), 2020
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D. Kane
Pasin Manurangsi
291
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30 Jul 2020
Calibrated Surrogate Losses for Adversarially Robust Classification
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Han Bao
Clayton Scott
Masashi Sugiyama
282
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28 May 2020
Learning Only from Relevant Keywords and Unlabeled Documents
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
Nontawat Charoenphakdee
Jongyeong Lee
Yiping Jin
Dittaya Wanvarie
Masashi Sugiyama
242
10
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10 Oct 2019
Calibrated Surrogate Maximization of Linear-fractional Utility in Binary Classification
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Han Bao
Masashi Sugiyama
211
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29 May 2019
An Algorithmic Framework for Fairness Elicitation
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Michael Kearns
Seth Neel
Aaron Roth
Logan Stapleton
Zhiwei Steven Wu
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229
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25 May 2019
Solving Empirical Risk Minimization in the Current Matrix Multiplication Time
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Y. Lee
Zhao Song
Qiuyi Zhang
325
133
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11 May 2019
Multi-Differential Fairness Auditor for Black Box Classifiers
International Joint Conference on Artificial Intelligence (IJCAI), 2019
Xavier Gitiaux
Huzefa Rangwala
FaML
253
8
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18 Mar 2019
Crowdsourced PAC Learning under Classification Noise
AAAI Conference on Human Computation & Crowdsourcing (HCOMP), 2019
Shelby Heinecke
L. Reyzin
183
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12 Feb 2019
Equal Opportunity in Online Classification with Partial Feedback
Yahav Bechavod
Katrina Ligett
Aaron Roth
Bo Waggoner
Zhiwei Steven Wu
FaML
266
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06 Feb 2019
Semi-Supervised Ordinal Regression Based on Empirical Risk Minimization
Neural Computation (Neural Comput.), 2019
Taira Tsuchiya
Nontawat Charoenphakdee
Issei Sato
Masashi Sugiyama
OffRL
357
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31 Jan 2019
On the Calibration of Multiclass Classification with Rejection
Neural Information Processing Systems (NeurIPS), 2019
Chenri Ni
Nontawat Charoenphakdee
Junya Honda
Masashi Sugiyama
297
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0
30 Jan 2019
Principled analytic classifier for positive-unlabeled learning via weighted integral probability metric
Yongchan Kwon
Wonyoung Hedge Kim
Masashi Sugiyama
M. Paik
725
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28 Jan 2019
On Symmetric Losses for Learning from Corrupted Labels
Nontawat Charoenphakdee
Jongyeong Lee
Masashi Sugiyama
NoLa
495
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27 Jan 2019
Uncertainty Sampling is Preconditioned Stochastic Gradient Descent on Zero-One Loss
Stephen Mussmann
Abigail Z. Jacobs
UQCV
152
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05 Dec 2018
How to Use Heuristics for Differential Privacy
IEEE Annual Symposium on Foundations of Computer Science (FOCS), 2018
Seth Neel
Aaron Roth
Zhiwei Steven Wu
176
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19 Nov 2018
Degree-
d
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Chow Parameters Robustly Determine Degree-
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Enrique Sanchez
D. Kane
111
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07 Nov 2018
Positive-Unlabeled Classification under Class Prior Shift and Asymmetric Error
Nontawat Charoenphakdee
Masashi Sugiyama
459
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19 Sep 2018
Unsupervised Domain Adaptation Based on Source-guided Discrepancy
Seiichi Kuroki
Nontawat Charoenphakdee
Han Bao
Junya Honda
Issei Sato
Masashi Sugiyama
395
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11 Sep 2018
Robust classification via MOM minimization
Guillaume Lecué
M. Lerasle
Timlothée Mathieu
247
54
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09 Aug 2018
Fairness Through Computationally-Bounded Awareness
Michael P. Kim
Omer Reingold
G. Rothblum
FaML
331
153
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08 Mar 2018
On the Rates of Convergence from Surrogate Risk Minimizers to the Bayes Optimal Classifier
Jingwei Zhang
Tongliang Liu
Dacheng Tao
195
7
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11 Feb 2018
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
Michael Kearns
Seth Neel
Aaron Roth
Zhiwei Steven Wu
FaML
985
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14 Nov 2017
Structured Prediction by Conditional Risk Minimization
Chong Yang Goh
Patrick Jaillet
TPM
151
4
0
21 Nov 2016
Multiclass Classification Calibration Functions
Bernardo Avila-Pires
Csaba Szepesvári
264
29
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20 Sep 2016
A Minimax Approach to Supervised Learning
Neural Information Processing Systems (NeurIPS), 2016
Farzan Farnia
David Tse
598
118
0
07 Jun 2016
A New Smooth Approximation to the Zero One Loss with a Probabilistic Interpretation
Md. Kamrul Hasan
C. Pal
149
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18 Nov 2015
Communication Efficient Distributed Agnostic Boosting
Shang-Tse Chen
Maria-Florina Balcan
Duen Horng Chau
FedML
247
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21 Jun 2015
On the Consistency of Ordinal Regression Methods
Journal of machine learning research (JMLR), 2014
Fabian Pedregosa
Francis R. Bach
Alexandre Gramfort
MoMe
567
78
0
11 Aug 2014
Construction of non-convex polynomial loss functions for training a binary classifier with quantum annealing
Ryan Babbush
Vasil S. Denchev
Nan Ding
Sergei Isakov
Hartmut Neven
219
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0
17 Jun 2014
Agnostic Learning of Disjunctions on Symmetric Distributions
Journal of machine learning research (JMLR), 2014
Vitaly Feldman
Pravesh Kothari
310
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27 May 2014
Approximate resilience, monotonicity, and the complexity of agnostic learning
ACM-SIAM Symposium on Discrete Algorithms (SODA), 2014
Dana Dachman-Soled
Vitaly Feldman
Li-Yang Tan
Andrew Wan
K. Wimmer
265
33
0
21 May 2014
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