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Marginal Singularity, and the Benefits of Labels in Covariate-Shift
v1v2v3 (latest)

Marginal Singularity, and the Benefits of Labels in Covariate-Shift

5 March 2018
Samory Kpotufe
Guillaume Martinet
ArXiv (abs)PDFHTML

Papers citing "Marginal Singularity, and the Benefits of Labels in Covariate-Shift"

17 / 67 papers shown
Title
Simple and near-optimal algorithms for hidden stratification and
  multi-group learning
Simple and near-optimal algorithms for hidden stratification and multi-group learning
Abdoreza Asadpour
Daniel J. Hsu
147
20
0
22 Dec 2021
Universal and data-adaptive algorithms for model selection in linear
  contextual bandits
Universal and data-adaptive algorithms for model selection in linear contextual bandits
Vidya Muthukumar
A. Krishnamurthy
71
5
0
08 Nov 2021
Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous
  Bias-Variance Reduction and Supercanonical Convergence
Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous Bias-Variance Reduction and Supercanonical Convergence
Henry Lam
Haofeng Zhang
52
4
0
23 Oct 2021
Adaptive transfer learning
Adaptive transfer learning
Henry W. J. Reeve
T. Cannings
R. Samworth
OOD
32
12
0
08 Jun 2021
How Fine-Tuning Allows for Effective Meta-Learning
How Fine-Tuning Allows for Effective Meta-Learning
Kurtland Chua
Qi Lei
Jason D. Lee
95
50
0
05 May 2021
Why do classifier accuracies show linear trends under distribution
  shift?
Why do classifier accuracies show linear trends under distribution shift?
Horia Mania
S. Sra
OOD
110
20
0
31 Dec 2020
A Computationally Efficient Classification Algorithm in Posterior Drift
  Model: Phase Transition and Minimax Adaptivity
A Computationally Efficient Classification Algorithm in Posterior Drift Model: Phase Transition and Minimax Adaptivity
Ruiqi Liu
Kexuan Li
Zuofeng Shang
30
4
0
09 Nov 2020
Theoretical bounds on estimation error for meta-learning
Theoretical bounds on estimation error for meta-learning
James Lucas
Mengye Ren
Irene Kameni
T. Pitassi
R. Zemel
51
12
0
14 Oct 2020
On Localized Discrepancy for Domain Adaptation
On Localized Discrepancy for Domain Adaptation
Yuchen Zhang
Mingsheng Long
Jianmin Wang
Michael I. Jordan
73
18
0
14 Aug 2020
Self-Tuning Bandits over Unknown Covariate-Shifts
Self-Tuning Bandits over Unknown Covariate-Shifts
Joe Suk
Samory Kpotufe
127
9
0
16 Jul 2020
A No-Free-Lunch Theorem for MultiTask Learning
A No-Free-Lunch Theorem for MultiTask Learning
Steve Hanneke
Samory Kpotufe
167
39
0
29 Jun 2020
Approximating a Target Distribution using Weight Queries
Approximating a Target Distribution using Weight Queries
Nadav Barak
Sivan Sabato
31
1
0
24 Jun 2020
Minimax optimal approaches to the label shift problem in non-parametric
  settings
Minimax optimal approaches to the label shift problem in non-parametric settings
Subha Maity
Yuekai Sun
Moulinath Banerjee
52
23
0
23 Mar 2020
To Split or Not to Split: The Impact of Disparate Treatment in
  Classification
To Split or Not to Split: The Impact of Disparate Treatment in Classification
Hao Wang
Hsiang Hsu
Mario Díaz
Flavio du Pin Calmon
115
23
0
12 Feb 2020
On the Value of Target Data in Transfer Learning
On the Value of Target Data in Transfer Learning
Steve Hanneke
Samory Kpotufe
83
74
0
12 Feb 2020
Transfer Learning for Nonparametric Classification: Minimax Rate and
  Adaptive Classifier
Transfer Learning for Nonparametric Classification: Minimax Rate and Adaptive Classifier
AI T.TONYC
EI Hongjiw
74
98
0
07 Jun 2019
The Label Complexity of Active Learning from Observational Data
The Label Complexity of Active Learning from Observational Data
Songbai Yan
Kamalika Chaudhuri
T. Javidi
21
9
0
29 May 2019
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