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2002.04747
Cited By
On the Value of Target Data in Transfer Learning
Neural Information Processing Systems (NeurIPS), 2020
12 February 2020
Steve Hanneke
Samory Kpotufe
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Papers citing
"On the Value of Target Data in Transfer Learning"
50 / 53 papers shown
Neyman-Pearson Classification under Both Null and Alternative Distributions Shift
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Yuyang Deng
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213
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Provable Benefits of Unsupervised Pre-training and Transfer Learning via Single-Index Models
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Aukosh Jagannath
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24 Feb 2025
Learning Neural Networks with Distribution Shift: Efficiently Certifiable Guarantees
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Adam R. Klivans
Lin Lin Lee
Konstantinos Stavropoulos
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254
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22 Feb 2025
On The Statistical Complexity of Offline Decision-Making
International Conference on Machine Learning (ICML), 2025
Thanh Nguyen-Tang
R. Arora
OffRL
528
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10 Jan 2025
Trans-Glasso: A Transfer Learning Approach to Precision Matrix Estimation
Boxin Zhao
Cong Ma
Mladen Kolar
315
1
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23 Nov 2024
Transformation-Invariant Learning and Theoretical Guarantees for OOD Generalization
Neural Information Processing Systems (NeurIPS), 2024
Omar Montasser
Han Shao
Emmanuel Abbe
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317
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30 Oct 2024
Learning with Shared Representations: Statistical Rates and Efficient Algorithms
Xiaochun Niu
Lili Su
Jiaming Xu
Pengkun Yang
FedML
473
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0
07 Sep 2024
Learning Tree-Structured Composition of Data Augmentation
Dongyue Li
Kailai Chen
P. Radivojac
Hongyang R. Zhang
333
1
0
26 Aug 2024
Transfer Learning for Latent Variable Network Models
Akhil Jalan
Arya Mazumdar
Soumendu Sundar Mukherjee
Purnamrita Sarkar
456
3
0
05 Jun 2024
Beyond Discrepancy: A Closer Look at the Theory of Distribution Shift
Robi Bhattacharjee
Nick Rittler
Kamalika Chaudhuri
255
1
0
29 May 2024
An adaptive transfer learning perspective on classification in non-stationary environments
Henry W J Reeve
269
0
0
28 May 2024
Understanding Forgetting in Continual Learning with Linear Regression
Meng Ding
Kaiyi Ji
Haiyan Zhao
Jinhui Xu
CLL
396
20
0
27 May 2024
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation
International Conference on Machine Learning (ICML), 2024
Haibo Yang
Pei-Yuan Qiu
Prashant Khanduri
Minghong Fang
Jia Liu
FedML
317
9
0
04 May 2024
Transfer Learning Study of Motion Transformer-based Trajectory Predictions
Lars Ullrich
Alex McMaster
Knut Graichen
298
12
0
12 Apr 2024
Transfer Learning Beyond Bounded Density Ratios
Alkis Kalavasis
Ilias Zadik
Manolis Zampetakis
304
6
0
18 Mar 2024
Model-free Test Time Adaptation for Out-Of-Distribution Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Yi-Fan Zhang
Qingsong Wen
Tian Zhou
Kun Yuan
Zhang Zhang
Liang Wang
Rong Jin
Tien-Ping Tan
TTA
OODD
245
5
0
28 Nov 2023
Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms
International Conference on Machine Learning (ICML), 2023
Ye Tian
Haolei Weng
Yang Feng
356
7
0
23 Oct 2023
Tight Rates in Supervised Outlier Transfer Learning
International Conference on Learning Representations (ICLR), 2023
Mohammadreza M. Kalan
Samory Kpotufe
159
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07 Oct 2023
Differentially Private Domain Adaptation with Theoretical Guarantees
International Conference on Machine Learning (ICML), 2023
Raef Bassily
Corinna Cortes
Anqi Mao
M. Mohri
305
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15 Jun 2023
Best-Effort Adaptation
Annals of Mathematics and Artificial Intelligence (AMAI), 2023
Pranjal Awasthi
Corinna Cortes
M. Mohri
265
12
0
10 May 2023
Classification Tree Pruning Under Covariate Shift
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2023
Nicholas Galbraith
Samory Kpotufe
278
3
0
07 May 2023
Limits of Model Selection under Transfer Learning
Annual Conference Computational Learning Theory (COLT), 2023
Steve Hanneke
Samory Kpotufe
Yasaman Mahdaviyeh
407
6
0
29 Apr 2023
AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation
International Conference on Machine Learning (ICML), 2023
Yi-Fan Zhang
Qingsong Wen
Kexin Jin
Kun Yuan
Zhang Zhang
Liang Wang
Rong Jin
Tien-Ping Tan
TTA
OOD
381
73
0
25 Apr 2023
Reliable learning in challenging environments
Neural Information Processing Systems (NeurIPS), 2023
Maria-Florina Balcan
Steve Hanneke
Rattana Pukdee
Dravyansh Sharma
OOD
304
8
0
06 Apr 2023
Identification of Negative Transfers in Multitask Learning Using Surrogate Models
Dongyue Li
Huy Le Nguyen
Hongyang R. Zhang
275
21
0
25 Mar 2023
Pseudo-Labeling for Kernel Ridge Regression under Covariate Shift
Kaizheng Wang
351
17
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20 Feb 2023
Transformers as Algorithms: Generalization and Stability in In-context Learning
International Conference on Machine Learning (ICML), 2023
Yingcong Li
M. E. Ildiz
Dimitris Papailiopoulos
Samet Oymak
421
237
0
17 Jan 2023
Transfer Learning for Contextual Multi-armed Bandits
Annals of Statistics (Ann. Stat.), 2022
Changxiao Cai
T. Tony Cai
Hongzhe Li
404
28
0
22 Nov 2022
The Value of Out-of-Distribution Data
International Conference on Machine Learning (ICML), 2022
Ashwin De Silva
Rahul Ramesh
Carey E. Priebe
Pratik Chaudhari
Joshua T. Vogelstein
OODD
423
16
0
23 Aug 2022
The Power and Limitation of Pretraining-Finetuning for Linear Regression under Covariate Shift
Neural Information Processing Systems (NeurIPS), 2022
Jingfeng Wu
Difan Zou
Vladimir Braverman
Quanquan Gu
Sham Kakade
209
24
0
03 Aug 2022
Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees
International Conference on Machine Learning (ICML), 2022
Haotian Ju
Dongyue Li
Hongyang R. Zhang
557
39
0
06 Jun 2022
Dimensionless machine learning: Imposing exact units equivariance
Journal of machine learning research (JMLR), 2022
Soledad Villar
Weichi Yao
D. Hogg
Ben Blum-Smith
Bianca Dumitrascu
322
34
0
02 Apr 2022
Connecting sufficient conditions for domain adaptation: source-guided uncertainty, relaxed divergences and discrepancy localization
Sofien Dhouib
S. Maghsudi
275
2
0
09 Mar 2022
Transfer-Learning Across Datasets with Different Input Dimensions: An Algorithm and Analysis for the Linear Regression Case
Journal of Computational Mathematics and Data Science (JCMDS), 2022
Luis P. Silvestrin
Harry Van Zanten
Mark Hoogendoorn
G. Koole
379
7
0
10 Feb 2022
Universal and data-adaptive algorithms for model selection in linear contextual bandits
Vidya Muthukumar
A. Krishnamurthy
307
5
0
08 Nov 2021
Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Yuheng Bu
Gholamali Aminian
Laura Toni
Miguel R. D. Rodrigues
G. Wornell
192
17
0
02 Nov 2021
Direct domain adaptation through reciprocal linear transformations
T. Alkhalifah
O. Ovcharenko
OOD
292
5
0
17 Aug 2021
Learning to Transfer: A Foliated Theory
Janith C. Petangoda
M. Deisenroth
N. Monk
195
0
0
22 Jul 2021
Near-Optimal Linear Regression under Distribution Shift
International Conference on Machine Learning (ICML), 2021
Qi Lei
Wei Hu
Jason D. Lee
OOD
176
45
0
23 Jun 2021
Adaptive transfer learning
Annals of Statistics (Ann. Stat.), 2021
Henry W. J. Reeve
T. Cannings
R. Samworth
OOD
304
26
0
08 Jun 2021
Model Zoo: A Growing "Brain" That Learns Continually
International Conference on Learning Representations (ICLR), 2021
Rahul Ramesh
Pratik Chaudhari
CLL
FedML
374
78
0
06 Jun 2021
Transfer Learning under High-dimensional Generalized Linear Models
Journal of the American Statistical Association (JASA), 2021
Ye Tian
Yang Feng
571
199
0
29 May 2021
Weighted Training for Cross-Task Learning
International Conference on Learning Representations (ICLR), 2021
Shuxiao Chen
K. Crammer
Han He
Dan Roth
Weijie J. Su
247
30
0
28 May 2021
How Fine-Tuning Allows for Effective Meta-Learning
Neural Information Processing Systems (NeurIPS), 2021
Kurtland Chua
Qi Lei
Jason D. Lee
256
56
0
05 May 2021
A Computationally Efficient Classification Algorithm in Posterior Drift Model: Phase Transition and Minimax Adaptivity
Ruiqi Liu
Kexuan Li
Zuofeng Shang
292
5
0
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Theoretical bounds on estimation error for meta-learning
James Lucas
Mengye Ren
Irene Kameni
T. Pitassi
R. Zemel
171
12
0
14 Oct 2020
Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation
Computer Vision and Pattern Recognition (CVPR), 2020
Yue Liu
Yezhen Wang
Shanghang Zhang
Dongsheng Li
Trevor Darrell
Kurt Keutzer
Han Zhao
OOD
364
114
0
09 Oct 2020
Trustworthy Convolutional Neural Networks: A Gradient Penalized-based Approach
Nicholas F Halliwell
Freddy Lecue
FAtt
282
9
0
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On Localized Discrepancy for Domain Adaptation
Yuchen Zhang
Mingsheng Long
Jianmin Wang
Sai Li
230
18
0
14 Aug 2020
Beyond
H
\mathcal{H}
H
-Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence
Changjian Shui
Qi Chen
Jun Wen
Fan Zhou
Christian Gagné
Boyu Wang
233
24
0
30 Jul 2020
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