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SOSELETO: A Unified Approach to Transfer Learning and Training with
  Noisy Labels

SOSELETO: A Unified Approach to Transfer Learning and Training with Noisy Labels

24 May 2018
Or Litany
Daniel Freedman
    NoLa
ArXivPDFHTML

Papers citing "SOSELETO: A Unified Approach to Transfer Learning and Training with Noisy Labels"

4 / 4 papers shown
Title
Handling Label Noise via Instance-Level Difficulty Modeling and Dynamic Optimization
Handling Label Noise via Instance-Level Difficulty Modeling and Dynamic Optimization
Kuan Zhang
Chengliang Chai
Jingzhe Xu
Chi Zhang
Ye Yuan
Guoren Wang
Lei Cao
NoLa
66
0
0
01 May 2025
Learning from Noisy Labels with Coarse-to-Fine Sample Credibility
  Modeling
Learning from Noisy Labels with Coarse-to-Fine Sample Credibility Modeling
Boshen Zhang
Yuxi Li
Yuanpeng Tu
Jinlong Peng
Yabiao Wang
Cunlin Wu
Yanghua Xiao
Cairong Zhao
NoLa
38
6
0
23 Aug 2022
Investigating Bi-Level Optimization for Learning and Vision from a
  Unified Perspective: A Survey and Beyond
Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond
Risheng Liu
Jiaxin Gao
Jin Zhang
Deyu Meng
Zhouchen Lin
AI4CE
59
223
0
27 Jan 2021
Borrowing Treasures from the Wealthy: Deep Transfer Learning through
  Selective Joint Fine-tuning
Borrowing Treasures from the Wealthy: Deep Transfer Learning through Selective Joint Fine-tuning
Weifeng Ge
Yizhou Yu
94
233
0
28 Feb 2017
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