On the Value of Target Data in Transfer Learning

12 February 2020

Papers citing "On the Value of Target Data in Transfer Learning"

50 / 52 papers shown

Title
Provable Benefits of Unsupervised Pre-training and Transfer Learning via Single-Index Models Taj Jones-McCormick Aukosh Jagannath S. Sen 119 0 0 24 Feb 2025
Learning Neural Networks with Distribution Shift: Efficiently Certifiable Guarantees Gautam Chandrasekaran Adam R. Klivans Lin Lin Lee Konstantinos Stavropoulos OOD 71 1 0 22 Feb 2025
On The Statistical Complexity of Offline Decision-Making Thanh Nguyen-Tang R. Arora OffRL 222 1 0 10 Jan 2025
Trans-Glasso: A Transfer Learning Approach to Precision Matrix Estimation Boxin Zhao Cong Ma Mladen Kolar 100 1 0 23 Nov 2024
Transformation-Invariant Learning and Theoretical Guarantees for OOD Generalization Omar Montasser Han Shao Emmanuel Abbe OOD 58 2 0 30 Oct 2024
Learning with Shared Representations: Statistical Rates and Efficient Algorithms Xiaochun Niu Lili Su Jiaming Xu Pengkun Yang FedML 68 2 0 07 Sep 2024
Learning Tree-Structured Composition of Data Augmentation Dongyue Li Kailai Chen P. Radivojac Hongyang R. Zhang 120 1 0 26 Aug 2024
Transfer Learning for Latent Variable Network Models Akhil Jalan Arya Mazumdar Soumendu Sundar Mukherjee Purnamrita Sarkar 123 1 0 05 Jun 2024
Beyond Discrepancy: A Closer Look at the Theory of Distribution Shift Robi Bhattacharjee Nick Rittler Kamalika Chaudhuri 87 1 0 29 May 2024
An adaptive transfer learning perspective on classification in non-stationary environments Henry W J Reeve 86 0 0 28 May 2024
Understanding Forgetting in Continual Learning with Linear Regression Meng Ding Kaiyi Ji Di Wang Jinhui Xu CLL 145 10 0 27 May 2024
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation Haibo Yang Pei-Yuan Qiu Prashant Khanduri Minghong Fang Jia Liu FedML 98 2 0 04 May 2024
Transfer Learning Study of Motion Transformer-based Trajectory Predictions Lars Ullrich Alex McMaster Knut Graichen 80 4 0 12 Apr 2024
Transfer Learning Beyond Bounded Density Ratios Alkis Kalavasis Ilias Zadik Manolis Zampetakis 94 5 0 18 Mar 2024
Model-free Test Time Adaptation for Out-Of-Distribution Detection Yi-Fan Zhang Xue Wang Tian Zhou Kun Yuan Zhang Zhang Liang Wang Rong Jin Tien-Ping Tan TTA OODD 80 4 0 28 Nov 2023
Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms Ye Tian Haolei Weng Yang Feng 74 4 0 23 Oct 2023
Tight Rates in Supervised Outlier Transfer Learning Mohammadreza M. Kalan Samory Kpotufe 38 1 0 07 Oct 2023
Differentially Private Domain Adaptation with Theoretical Guarantees Raef Bassily Corinna Cortes Anqi Mao M. Mohri 60 0 0 15 Jun 2023
Best-Effort Adaptation Pranjal Awasthi Corinna Cortes M. Mohri 91 8 0 10 May 2023
Classification Tree Pruning Under Covariate Shift Nicholas Galbraith Samory Kpotufe 81 1 0 07 May 2023
Limits of Model Selection under Transfer Learning Steve Hanneke Samory Kpotufe Yasaman Mahdaviyeh 116 6 0 29 Apr 2023
AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation Yi-Fan Zhang Xue Wang Kexin Jin Kun Yuan Zhang Zhang Liang Wang Rong Jin Tien-Ping Tan TTA OOD 93 44 0 25 Apr 2023
Reliable learning in challenging environments Maria-Florina Balcan Steve Hanneke Rattana Pukdee Dravyansh Sharma OOD 80 6 0 06 Apr 2023
Identification of Negative Transfers in Multitask Learning Using Surrogate Models Dongyue Li Huy Le Nguyen Hongyang R. Zhang 83 13 0 25 Mar 2023
Pseudo-Labeling for Kernel Ridge Regression under Covariate Shift Kaizheng Wang 66 12 0 20 Feb 2023
Transformers as Algorithms: Generalization and Stability in In-context Learning Yingcong Li M. E. Ildiz Dimitris Papailiopoulos Samet Oymak 112 174 0 17 Jan 2023
Transfer Learning for Contextual Multi-armed Bandits Changxiao Cai T. Tony Cai Hongzhe Li 127 19 0 22 Nov 2022
The Value of Out-of-Distribution Data Ashwin De Silva Rahul Ramesh Carey E. Priebe Pratik Chaudhari Joshua T. Vogelstein OODD 91 12 0 23 Aug 2022
The Power and Limitation of Pretraining-Finetuning for Linear Regression under Covariate Shift Jingfeng Wu Difan Zou Vladimir Braverman Quanquan Gu Sham Kakade 65 17 0 03 Aug 2022
Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees Haotian Ju Dongyue Li Hongyang R. Zhang 126 30 0 06 Jun 2022
Dimensionless machine learning: Imposing exact units equivariance Soledad Villar Weichi Yao D. Hogg Ben Blum-Smith Bianca Dumitrascu 58 27 0 02 Apr 2022
Connecting sufficient conditions for domain adaptation: source-guided uncertainty, relaxed divergences and discrepancy localization Sofien Dhouib S. Maghsudi 83 2 0 09 Mar 2022
Transfer-Learning Across Datasets with Different Input Dimensions: An Algorithm and Analysis for the Linear Regression Case Luis P. Silvestrin Harry Van Zanten Mark Hoogendoorn G. Koole 141 4 0 10 Feb 2022
Universal and data-adaptive algorithms for model selection in linear contextual bandits Vidya Muthukumar A. Krishnamurthy 71 5 0 08 Nov 2021
Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm Yuheng Bu Gholamali Aminian Laura Toni Miguel R. D. Rodrigues G. Wornell 59 14 0 02 Nov 2021
Direct domain adaptation through reciprocal linear transformations T. Alkhalifah O. Ovcharenko OOD 131 5 0 17 Aug 2021
Learning to Transfer: A Foliated Theory Janith C. Petangoda M. Deisenroth N. Monk 50 0 0 22 Jul 2021
Near-Optimal Linear Regression under Distribution Shift Qi Lei Wei Hu Jason D. Lee OOD 75 42 0 23 Jun 2021
Adaptive transfer learning Henry W. J. Reeve T. Cannings R. Samworth OOD 35 12 0 08 Jun 2021
Model Zoo: A Growing "Brain" That Learns Continually Rahul Ramesh Pratik Chaudhari CLL FedML 111 66 0 06 Jun 2021
Transfer Learning under High-dimensional Generalized Linear Models Ye Tian Yang Feng 93 126 0 29 May 2021
Weighted Training for Cross-Task Learning Shuxiao Chen K. Crammer Han He Dan Roth Weijie J. Su 83 28 0 28 May 2021
How Fine-Tuning Allows for Effective Meta-Learning Kurtland Chua Qi Lei Jason D. Lee 95 50 0 05 May 2021
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 James Lucas Mengye Ren Irene Kameni T. Pitassi R. Zemel 51 12 0 14 Oct 2020
Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation Yue Liu Yezhen Wang Shanghang Zhang Dongsheng Li Trevor Darrell Kurt Keutzer Han Zhao OOD 83 96 0 09 Oct 2020
Trustworthy Convolutional Neural Networks: A Gradient Penalized-based Approach Nicholas F Halliwell Freddy Lecue FAtt 118 9 0 29 Sep 2020
On Localized Discrepancy for Domain Adaptation Yuchen Zhang Mingsheng Long Jianmin Wang Michael I. Jordan 73 18 0 14 Aug 2020
$Beyond $\mathcal{H}$-Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence$ Beyond $\mathcal{H}$ -Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence Changjian Shui Qi Chen Jun Wen Fan Zhou Christian Gagné Boyu Wang 97 23 0 30 Jul 2020
A No-Free-Lunch Theorem for MultiTask Learning Steve Hanneke Samory Kpotufe 167 39 0 29 Jun 2020