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Efficient Classification for Metric Data
v1v2v3 (latest)

Efficient Classification for Metric Data

IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2013
11 June 2013
Lee-Ad Gottlieb
A. Kontorovich
Robert Krauthgamer
ArXiv (abs)PDFHTML

Papers citing "Efficient Classification for Metric Data"

34 / 34 papers shown
Transductive and Learning-Augmented Online Regression
Transductive and Learning-Augmented Online Regression
Vinod Raman
Shenghao Xie
Samson Zhou
AI4TS
158
0
0
04 Oct 2025
Information-theoretic Generalization Analysis for VQ-VAEs: A Role of Latent Variables
Information-theoretic Generalization Analysis for VQ-VAEs: A Role of Latent Variables
Futoshi Futami
Masahiro Fujisawa
DRLCML
523
0
0
26 May 2025
k-Center Clustering with Outliers in Sliding Windows
k-Center Clustering with Outliers in Sliding Windows
Paolo Pellizzoni
A. Pietracaprina
G. Pucci
169
8
0
07 Jan 2022
Fat-Shattering Dimension of $k$-fold Aggregations
Fat-Shattering Dimension of kkk-fold AggregationsJournal of machine learning research (JMLR), 2021
Idan Attias
A. Kontorovich
299
3
0
10 Oct 2021
Optimal Binary Classification Beyond Accuracy
Optimal Binary Classification Beyond Accuracy
Shashank Singh
Justin Khim
FaML
343
9
0
05 Jul 2021
Pay attention to your loss: understanding misconceptions about
  1-Lipschitz neural networks
Pay attention to your loss: understanding misconceptions about 1-Lipschitz neural networksNeural Information Processing Systems (NeurIPS), 2021
Louis Bethune
Thibaut Boissin
M. Serrurier
Franck Mamalet
Corentin Friedrich
Alberto González Sanz
535
34
0
11 Apr 2021
Stable Sample Compression Schemes: New Applications and an Optimal SVM
  Margin Bound
Stable Sample Compression Schemes: New Applications and an Optimal SVM Margin Bound
Steve Hanneke
A. Kontorovich
280
30
0
09 Nov 2020
Non-parametric Binary regression in metric spaces with KL loss
Non-parametric Binary regression in metric spaces with KL loss
Ariel Avital
K. Efremenko
A. Kontorovich
David Toplin
Bo Waggoner
129
1
0
19 Oct 2020
Fast Immune System Inspired Hypermutation Operators for Combinatorial
  Optimisation
Fast Immune System Inspired Hypermutation Operators for Combinatorial OptimisationIEEE Transactions on Evolutionary Computation (TEVC), 2020
Dogan Corus
P. S. Oliveto
Donya Yazdani
162
11
0
01 Sep 2020
Functions with average smoothness: structure, algorithms, and learning
Functions with average smoothness: structure, algorithms, and learningAnnual Conference Computational Learning Theory (COLT), 2020
Yair Ashlagi
Lee-Ad Gottlieb
A. Kontorovich
195
11
0
13 Jul 2020
Classifier-independent Lower-Bounds for Adversarial Robustness
Classifier-independent Lower-Bounds for Adversarial Robustness
Elvis Dohmatob
506
1
0
17 Jun 2020
Distributionally Robust Weighted $k$-Nearest Neighbors
Distributionally Robust Weighted kkk-Nearest Neighbors
Shixiang Zhu
Liyan Xie
Minghe Zhang
Rui Gao
Yao Xie
OOD
608
11
0
07 Jun 2020
A General Coreset-Based Approach to Diversity Maximization under Matroid
  Constraints
A General Coreset-Based Approach to Diversity Maximization under Matroid ConstraintsACM Transactions on Knowledge Discovery from Data (TKDD), 2020
Matteo Ceccarello
A. Pietracaprina
G. Pucci
147
13
0
08 Feb 2020
Fast and Bayes-consistent nearest neighbors
Fast and Bayes-consistent nearest neighborsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019
K. Efremenko
A. Kontorovich
Moshe Noivirt
319
3
0
07 Oct 2019
Classification in asymmetric spaces via sample compression
Classification in asymmetric spaces via sample compression
Lee-Ad Gottlieb
Shira Ozeri
107
1
0
22 Sep 2019
Rates of Convergence for Large-scale Nearest Neighbor Classification
Rates of Convergence for Large-scale Nearest Neighbor ClassificationNeural Information Processing Systems (NeurIPS), 2019
Xingye Qiao
Jiexin Duan
Guang Cheng
223
11
0
03 Sep 2019
Dreaming machine learning: Lipschitz extensions for reinforcement
  learning on financial markets
Dreaming machine learning: Lipschitz extensions for reinforcement learning on financial markets
J. Calabuig
H. Falciani
E. A. Sánchez-Pérez
215
29
0
09 Jul 2019
Robustness for Non-Parametric Classification: A Generic Attack and
  Defense
Robustness for Non-Parametric Classification: A Generic Attack and DefenseInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Yao-Yuan Yang
Cyrus Rashtchian
Yizhen Wang
Kamalika Chaudhuri
SILMAAML
293
44
0
07 Jun 2019
Distributed Nearest Neighbor Classification
Distributed Nearest Neighbor Classification
Jiexin Duan
Xingye Qiao
Guang Cheng
129
4
0
12 Dec 2018
Rademacher Complexity and Generalization Performance of Multi-category
  Margin Classifiers
Rademacher Complexity and Generalization Performance of Multi-category Margin Classifiers
Khadija Musayeva
Fabien Lauer
Y. Guermeur
247
15
0
03 Dec 2018
What is known about Vertex Cover Kernelization?
What is known about Vertex Cover Kernelization?
M. Fellows
L. Jaffke
A. Király
Frances A. Rosamond
Mathias Weller
154
28
0
23 Nov 2018
Improved Generalization Bounds for Adversarially Robust Learning
Improved Generalization Bounds for Adversarially Robust Learning
Idan Attias
A. Kontorovich
Yishay Mansour
407
22
0
04 Oct 2018
Metric Learning via Maximizing the Lipschitz Margin Ratio
Metric Learning via Maximizing the Lipschitz Margin Ratio
Mingzhi Dong
Xiaochen Yang
Yang Wu
Jing-Hao Xue
213
5
0
09 Feb 2018
Learning Local Metrics and Influential Regions for Classification
Learning Local Metrics and Influential Regions for Classification
Mingzhi Dong
Yujiang Wang
Xiaochen Yang
Jing-Hao Xue
200
23
0
09 Feb 2018
L p -norm Sauer-Shelah Lemma for Margin Multi-category Classifiers
L p -norm Sauer-Shelah Lemma for Margin Multi-category Classifiers
Y. Guermeur
203
24
0
26 Sep 2016
Active Nearest-Neighbor Learning in Metric Spaces
Active Nearest-Neighbor Learning in Metric Spaces
A. Kontorovich
Sivan Sabato
Ruth Urner
820
37
0
22 May 2016
MapReduce and Streaming Algorithms for Diversity Maximization in Metric
  Spaces of Bounded Doubling Dimension
MapReduce and Streaming Algorithms for Diversity Maximization in Metric Spaces of Bounded Doubling Dimension
Matteo Ceccarello
A. Pietracaprina
G. Pucci
E. Upfal
196
37
0
18 May 2016
Algorithms for Lipschitz Learning on Graphs
Algorithms for Lipschitz Learning on Graphs
Rasmus Kyng
Anup B. Rao
Sushant Sachdeva
D. Spielman
234
84
0
01 May 2015
Nearly optimal classification for semimetrics
Nearly optimal classification for semimetrics
Lee-Ad Gottlieb
A. Kontorovich
348
19
0
22 Feb 2015
A Bayes consistent 1-NN classifier
A Bayes consistent 1-NN classifierInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2014
A. Kontorovich
Roi Weiss
749
39
0
01 Jul 2014
Near-optimal sample compression for nearest neighbors
Near-optimal sample compression for nearest neighborsIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2014
Lee-Ad Gottlieb
A. Kontorovich
Pinhas Nisnevitch
610
49
0
13 Apr 2014
Maximum Margin Multiclass Nearest Neighbors
Maximum Margin Multiclass Nearest NeighborsInternational Conference on Machine Learning (ICML), 2014
A. Kontorovich
Roi Weiss
348
32
0
30 Jan 2014
Adaptive Metric Dimensionality Reduction
Adaptive Metric Dimensionality ReductionTheoretical Computer Science (TCS), 2013
Lee-Ad Gottlieb
A. Kontorovich
Robert Krauthgamer
475
40
0
12 Feb 2013
Efficient Regression in Metric Spaces via Approximate Lipschitz
  Extension
Efficient Regression in Metric Spaces via Approximate Lipschitz ExtensionIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2011
Lee-Ad Gottlieb
A. Kontorovich
Robert Krauthgamer
492
56
0
18 Nov 2011
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