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Robust Learning from Untrusted Sources
International Conference on Machine Learning (ICML), 2019
29 January 2019
Nikola Konstantinov
Christoph H. Lampert
FedML
OOD
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Papers citing
"Robust Learning from Untrusted Sources"
38 / 38 papers shown
Bringing Balance to Hand Shape Classification: Mitigating Data Imbalance Through Generative Models
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P. D. Bianco
Franco Ronchetti
F. Quiroga
Oscar Stanchi
Santiago Ponte Ahón
Waldo Hasperué
GAN
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269
0
0
22 Jul 2025
Federated Adapter on Foundation Models: An Out-Of-Distribution Approach
Yiyuan Yang
Guodong Long
Wanrong Zhu
Qinghua Lu
Shanshan Ye
Jing Jiang
OODD
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3
0
02 May 2025
SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation
International Conference on Learning Representations (ICLR), 2024
Mucong Ding
Bang An
Yuancheng Xu
Anirudh Satheesh
Furong Huang
279
1
0
03 Oct 2024
AdaTrans: Feature-wise and Sample-wise Adaptive Transfer Learning for High-dimensional Regression
Zelin He
Ying Sun
Jingyuan Liu
Runze Li
288
5
0
20 Mar 2024
Collaborative Learning with Different Labeling Functions
Yuyang Deng
Mingda Qiao
392
1
0
16 Feb 2024
Distributed Personalized Empirical Risk Minimization
Neural Information Processing Systems (NeurIPS), 2023
Yuyang Deng
Mohammad Mahdi Kamani
Pouria Mahdavinia
M. Mahdavi
252
6
0
26 Oct 2023
Robust and Actively Secure Serverless Collaborative Learning
Neural Information Processing Systems (NeurIPS), 2023
Olive Franzese
Adam Dziedzic
Christopher A. Choquette-Choo
Mark R. Thomas
Muhammad Ahmad Kaleem
Stephan Rabanser
Cong Fang
Somesh Jha
Nicolas Papernot
Xiao Wang
OOD
222
5
0
25 Oct 2023
R-divergence for Estimating Model-oriented Distribution Discrepancy
Neural Information Processing Systems (NeurIPS), 2023
Zhilin Zhao
Longbing Cao
382
2
0
02 Oct 2023
Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation
Neural Information Processing Systems (NeurIPS), 2023
Yuyang Deng
Ilja Kuzborskij
M. Mahdavi
OOD
231
2
0
19 Sep 2023
Rank-Aware Negative Training for Semi-Supervised Text Classification
Transactions of the Association for Computational Linguistics (TACL), 2023
Ahmed Murtadha
Shengfeng Pan
Wen Bo
Jianlin Su
Xinxin Cao
Wenze Zhang
Yunfeng Liu
200
9
0
13 Jun 2023
Best-Effort Adaptation
Annals of Mathematics and Artificial Intelligence (AMAI), 2023
Pranjal Awasthi
Corinna Cortes
M. Mohri
198
12
0
10 May 2023
Algorithm-Dependent Bounds for Representation Learning of Multi-Source Domain Adaptation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Qi Chen
M. Marchand
OOD
224
11
0
04 Apr 2023
An Experimental Study of Byzantine-Robust Aggregation Schemes in Federated Learning
IEEE Transactions on Big Data (IEEE Trans. Big Data), 2023
Shenghui Li
Edith C.H. Ngai
Thiemo Voigt
FedML
AAML
224
94
0
14 Feb 2023
Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels
European Conference on Computer Vision (ECCV), 2022
Ganlong Zhao
Guanbin Li
Yipeng Qin
Feng Liu
Yizhou Yu
NoLa
262
32
0
29 Jul 2022
Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer
Yingyi Chen
Xiaoke Shen
Yahui Liu
Qinghua Tao
Johan A. K. Suykens
AAML
ViT
193
37
0
25 Jul 2022
Uncertainty-Aware Learning Against Label Noise on Imbalanced Datasets
AAAI Conference on Artificial Intelligence (AAAI), 2022
Yingsong Huang
Bing Bai
Shengwei Zhao
Kun Bai
Haiwei Yang
NoLa
177
61
0
12 Jul 2022
Gray Learning from Non-IID Data with Out-of-distribution Samples
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Zhilin Zhao
LongBing Cao
Changbao Wang
OOD
OODD
160
2
0
19 Jun 2022
Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning
International Conference on Learning Representations (ICLR), 2022
Jiahui Gao
Renjie Pi
Yong Lin
Hang Xu
Jiacheng Ye
Zhiyong Wu
Weizhong Zhang
Xiaodan Liang
Zhenguo Li
Lingpeng Kong
SyDa
VLM
304
58
0
25 May 2022
Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning
IEEE Robotics and Automation Letters (RA-L), 2022
Mathias Lechner
Alexander Amini
Daniela Rus
T. Henzinger
AAML
252
11
0
15 Apr 2022
Multitask Learning and Bandits via Robust Statistics
Management Sciences (MS), 2021
Kan Xu
Hamsa Bastani
394
9
0
28 Dec 2021
DistFL: Distribution-aware Federated Learning for Mobile Scenarios
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies (IMWUT), 2021
Bingyan Liu
Y. Cai
Ziqi Zhang
Yan Liang
Leye Wang
Ding Li
Yao Guo
Xiangqun Chen
OOD
FedML
116
10
0
22 Oct 2021
FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data
Eugenia Iofinova
Nikola Konstantinov
Christoph H. Lampert
FaML
372
0
0
22 Jun 2021
Aggregating From Multiple Target-Shifted Sources
International Conference on Machine Learning (ICML), 2021
Changjian Shui
Zijian Li
Jiaqi Li
Christian Gagné
Charles Ling
Boyu Wang
241
34
0
09 May 2021
Fairness-Aware PAC Learning from Corrupted Data
Journal of machine learning research (JMLR), 2021
Nikola Konstantinov
Christoph H. Lampert
278
22
0
11 Feb 2021
Probabilistic Inference for Learning from Untrusted Sources
D. Nguyen
Shiau Hong Lim
L. Wynter
D. Cai
FedML
123
0
0
15 Jan 2021
Auto-weighted Robust Federated Learning with Corrupted Data Sources
ACM Transactions on Intelligent Systems and Technology (ACM TIST), 2021
Shenghui Li
Edith C.H. Ngai
Fanghua Ye
Thiemo Voigt
FedML
225
34
0
14 Jan 2021
Active Learning for Noisy Data Streams Using Weak and Strong Labelers
Taraneh Younesian
Dick H. J. Epema
L. Chen
134
12
0
27 Oct 2020
Byzantine Resilient Distributed Multi-Task Learning
Neural Information Processing Systems (NeurIPS), 2020
Jiani Li
W. Abbas
X. Koutsoukos
194
9
0
25 Oct 2020
A Discriminative Technique for Multiple-Source Adaptation
Corinna Cortes
M. Mohri
A. Suresh
Ningshan Zhang
190
1
0
25 Aug 2020
A Theory of Multiple-Source Adaptation with Limited Target Labeled Data
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Yishay Mansour
M. Mohri
Jae Hun Ro
A. Suresh
Ke Wu
279
29
0
19 Jul 2020
Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing
IEEE Transactions on Parallel and Distributed Systems (TPDS), 2020
Jed Mills
Jia Hu
Geyong Min
FedML
290
253
0
17 Jul 2020
TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise
Amirmasoud Ghiassi
Taraneh Younesian
Robert Birke
L. Chen
NoLa
145
6
0
13 Jul 2020
Learning while Respecting Privacy and Robustness to Distributional Uncertainties and Adversarial Data
A. Sadeghi
Gang Wang
Meng Ma
G. Giannakis
OOD
FedML
111
4
0
07 Jul 2020
On the Sample Complexity of Adversarial Multi-Source PAC Learning
International Conference on Machine Learning (ICML), 2020
Nikola Konstantinov
Elias Frantar
Dan Alistarh
Christoph H. Lampert
270
18
0
24 Feb 2020
Byzantine-resilient Decentralized Stochastic Gradient Descent
Shangwei Guo
Tianwei Zhang
Hanzhou Yu
Xiaofei Xie
Lei Ma
Tao Xiang
Yang Liu
223
64
0
20 Feb 2020
DivideMix: Learning with Noisy Labels as Semi-supervised Learning
International Conference on Learning Representations (ICLR), 2020
Junnan Li
R. Socher
Guosheng Lin
NoLa
452
1,229
0
18 Feb 2020
Attack-Resistant Federated Learning with Residual-based Reweighting
Shuhao Fu
Chulin Xie
Yue Liu
Qifeng Chen
FedML
AAML
286
103
0
24 Dec 2019
A Principled Approach for Learning Task Similarity in Multitask Learning
International Joint Conference on Artificial Intelligence (IJCAI), 2019
Changjian Shui
Mahdieh Abbasi
Louis-Émile Robitaille
Boyu Wang
Christian Gagné
242
61
0
21 Mar 2019
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