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2002.08936
Cited By
Meta-learning for mixed linear regression
International Conference on Machine Learning (ICML), 2020
20 February 2020
Weihao Kong
Raghav Somani
Zhao Song
Sham Kakade
Sewoong Oh
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Papers citing
"Meta-learning for mixed linear regression"
48 / 48 papers shown
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Nicolas W. Hengartner
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How Many Domains Suffice for Domain Generalization? A Tight Characterization via the Domain Shattering Dimension
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Han Shao
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Improving Memory Efficiency for Training KANs via Meta Learning
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Jun Shu
Deyu Meng
Zongben Xu
193
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09 Jun 2025
Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination
Ilias Diakonikolas
Giannis Iakovidis
D. Kane
Thanasis Pittas
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20 Feb 2025
Entangled Mean Estimation in High-Dimensions
Symposium on the Theory of Computing (STOC), 2025
Ilias Diakonikolas
D. Kane
Sihan Liu
Thanasis Pittas
358
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10 Jan 2025
Learning with Shared Representations: Statistical Rates and Efficient Algorithms
Xiaochun Niu
Lili Su
Jiaming Xu
Pengkun Yang
FedML
487
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07 Sep 2024
F-FOMAML: GNN-Enhanced Meta-Learning for Peak Period Demand Forecasting with Proxy Data
Zexing Xu
Linjun Zhang
Sitan Yang
Rasoul Etesami
Hanghang Tong
Huan Zhang
Jiawei Han
AI4TS
219
6
0
23 Jun 2024
Leveraging Offline Data in Linear Latent Contextual Bandits
Chinmaya Kausik
Kevin Tan
Ambuj Tewari
OffRL
258
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27 May 2024
Collaborative Learning with Different Labeling Functions
Yuyang Deng
Mingda Qiao
443
2
0
16 Feb 2024
Metalearning with Very Few Samples Per Task
Maryam Aliakbarpour
Konstantina Bairaktari
Gavin Brown
Adam D. Smith
Nathan Srebro
Jonathan Ullman
VLM
421
11
0
21 Dec 2023
Initializing Services in Interactive ML Systems for Diverse Users
Avinandan Bose
Mihaela Curmei
Daniel L. Jiang
Jamie Morgenstern
Sarah Dean
Lillian J. Ratliff
Maryam Fazel
430
6
0
19 Dec 2023
Near-Optimal Mean Estimation with Unknown, Heteroskedastic Variances
Symposium on the Theory of Computing (STOC), 2023
Spencer Compton
Gregory Valiant
335
4
0
05 Dec 2023
Transformers can optimally learn regression mixture models
International Conference on Learning Representations (ICLR), 2023
Reese Pathak
Rajat Sen
Weihao Kong
Abhimanyu Das
232
15
0
14 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
379
7
0
23 Oct 2023
Estimation of Models with Limited Data by Leveraging Shared Structure
IEEE Conference on Decision and Control (CDC), 2023
Maryann Rui
Thibaut Horel
M. Dahleh
241
1
0
04 Oct 2023
Multi-dimensional domain generalization with low-rank structures
Journal of the American Statistical Association (JASA), 2023
Sai Li
Linjun Zhang
257
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0
18 Sep 2023
Linear Regression using Heterogeneous Data Batches
Neural Information Processing Systems (NeurIPS), 2023
Ayush Jain
Rajat Sen
Weihao Kong
Abhimanyu Das
A. Orlitsky
199
3
0
05 Sep 2023
Clustered Linear Contextual Bandits with Knapsacks
Yichuan Deng
M. Mamakos
Zhao Song
222
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0
21 Aug 2023
Nonlinear Meta-Learning Can Guarantee Faster Rates
SIAM Journal on Mathematics of Data Science (SIMODS), 2023
Dimitri Meunier
Zhu Li
Arthur Gretton
Samory Kpotufe
609
8
0
20 Jul 2023
Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems
International Conference on Machine Learning (ICML), 2023
Ainesh Bakshi
Allen Liu
Ankur Moitra
Morris Yau
307
11
0
13 Jul 2023
Mixed Regression via Approximate Message Passing
Journal of machine learning research (JMLR), 2023
Nelvin Tan
R. Venkataramanan
344
7
0
05 Apr 2023
Identification of Negative Transfers in Multitask Learning Using Surrogate Models
Dongyue Li
Huy Le Nguyen
Hongyang R. Zhang
278
21
0
25 Mar 2023
Provable Pathways: Learning Multiple Tasks over Multiple Paths
AAAI Conference on Artificial Intelligence (AAAI), 2023
Yingcong Li
Samet Oymak
MoE
256
4
0
08 Mar 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
426
237
0
17 Jan 2023
Efficient List-Decodable Regression using Batches
International Conference on Machine Learning (ICML), 2022
Abhimanyu Das
Ayush Jain
Weihao Kong
Rajat Sen
197
5
0
23 Nov 2022
Learning Mixtures of Markov Chains and MDPs
International Conference on Machine Learning (ICML), 2022
Chinmaya Kausik
Kevin Tan
Ambuj Tewari
327
13
0
17 Nov 2022
Subspace Recovery from Heterogeneous Data with Non-isotropic Noise
Neural Information Processing Systems (NeurIPS), 2022
John C. Duchi
Vitaly Feldman
Lunjia Hu
Kunal Talwar
FedML
223
14
0
24 Oct 2022
Understanding Benign Overfitting in Gradient-Based Meta Learning
Neural Information Processing Systems (NeurIPS), 2022
Lisha Chen
Songtao Lu
Tianyi Chen
MLT
283
19
0
27 Jun 2022
Provable Generalization of Overparameterized Meta-learning Trained with SGD
Neural Information Processing Systems (NeurIPS), 2022
Yu Huang
Yingbin Liang
Longbo Huang
MLT
330
13
0
18 Jun 2022
Global Convergence of Federated Learning for Mixed Regression
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2022
Lili Su
Jiaming Xu
Pengkun Yang
FedML
197
9
0
15 Jun 2022
Provable and Efficient Continual Representation Learning
Yingcong Li
Mingchen Li
M. Salman Asif
Samet Oymak
CLL
307
16
0
03 Mar 2022
Non-stationary Bandits and Meta-Learning with a Small Set of Optimal Arms
Javad Azizi
T. Duong
Yasin Abbasi-Yadkori
András Gyorgy
Claire Vernade
Mohammad Ghavamzadeh
773
8
0
25 Feb 2022
Learning Mixtures of Linear Dynamical Systems
International Conference on Machine Learning (ICML), 2022
Yanxi Chen
H. Vincent Poor
311
22
0
26 Jan 2022
Towards Sample-efficient Overparameterized Meta-learning
Neural Information Processing Systems (NeurIPS), 2022
Yue Sun
Adhyyan Narang
Halil Ibrahim Gulluk
Samet Oymak
Maryam Fazel
BDL
195
25
0
16 Jan 2022
A Representation Learning Perspective on the Importance of Train-Validation Splitting in Meta-Learning
International Conference on Machine Learning (ICML), 2021
Nikunj Saunshi
Arushi Gupta
Wei Hu
SSL
279
19
0
29 Jun 2021
Sample Efficient Linear Meta-Learning by Alternating Minimization
K. K. Thekumparampil
Prateek Jain
Praneeth Netrapalli
Sewoong Oh
304
27
0
18 May 2021
How to distribute data across tasks for meta-learning?
AAAI Conference on Artificial Intelligence (AAAI), 2021
Alexandru Cioba
Michael Bromberg
Qian Wang
R. Niyogi
Georgios Batzolis
Jezabel R. Garcia
Da-shan Shiu
A. Bernacchia
FedML
229
9
0
15 Mar 2021
Sample Efficient Subspace-based Representations for Nonlinear Meta-Learning
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021
Halil Ibrahim Gulluk
Yue Sun
Samet Oymak
Maryam Fazel
235
2
0
14 Feb 2021
Exploiting Shared Representations for Personalized Federated Learning
International Conference on Machine Learning (ICML), 2021
Liam Collins
Hamed Hassani
Aryan Mokhtari
Sanjay Shakkottai
FedML
OOD
471
1,055
0
14 Feb 2021
Meta-learning with negative learning rates
International Conference on Learning Representations (ICLR), 2021
A. Bernacchia
196
17
0
01 Feb 2021
Spectral Methods for Data Science: A Statistical Perspective
Yuxin Chen
Yuejie Chi
Jianqing Fan
Cong Ma
694
213
0
15 Dec 2020
On InstaHide, Phase Retrieval, and Sparse Matrix Factorization
International Conference on Learning Representations (ICLR), 2020
Sitan Chen
Xiaoxiao Li
Zhao Song
Danyang Zhuo
314
14
0
23 Nov 2020
Stochastic Linear Bandits with Protected Subspace
Advait Parulekar
Soumya Basu
Aditya Gopalan
Karthikeyan Shanmugam
Sanjay Shakkottai
428
2
0
02 Nov 2020
How Does the Task Landscape Affect MAML Performance?
Liam Collins
Aryan Mokhtari
Sanjay Shakkottai
409
5
0
27 Oct 2020
Learning Mixtures of Low-Rank Models
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
Yanxi Chen
Cong Ma
H. Vincent Poor
Yuxin Chen
363
16
0
23 Sep 2020
Robust Meta-learning for Mixed Linear Regression with Small Batches
Weihao Kong
Raghav Somani
Sham Kakade
Sewoong Oh
OOD
260
38
0
17 Jun 2020
Understanding and Improving Information Transfer in Multi-Task Learning
International Conference on Learning Representations (ICLR), 2020
Sen Wu
Hongyang R. Zhang
Christopher Ré
254
181
0
02 May 2020
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