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Bridging the Theoretical Bound and Deep Algorithms for Open Set Domain
  Adaptation

Bridging the Theoretical Bound and Deep Algorithms for Open Set Domain Adaptation

23 June 2020
Li Zhong
Zhen Fang
Feng Liu
Bo Yuan
Guangquan Zhang
Jie Lu
    AAML
ArXivPDFHTML

Papers citing "Bridging the Theoretical Bound and Deep Algorithms for Open Set Domain Adaptation"

6 / 6 papers shown
Title
Learning Bounds for Open-Set Learning
Learning Bounds for Open-Set Learning
Zhen Fang
Jie Lu
Anjin Liu
Feng Liu
Guangquan Zhang
18
60
0
30 Jun 2021
TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation
TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation
Haoang Chi
Feng Liu
Wenjing Yang
L. Lan
Tongliang Liu
Bo Han
William Cheung
James T. Kwok
35
27
0
11 Jun 2021
How does the Combined Risk Affect the Performance of Unsupervised Domain
  Adaptation Approaches?
How does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches?
Zhong Li
Zhen Fang
Feng Liu
Jie Lu
Bo Yuan
Guangquan Zhang
25
54
0
30 Dec 2020
I3DOL: Incremental 3D Object Learning without Catastrophic Forgetting
I3DOL: Incremental 3D Object Learning without Catastrophic Forgetting
Jiahua Dong
Yang Cong
Gan Sun
Bingtao Ma
Lichen Wang
3DPC
CLL
43
32
0
16 Dec 2020
Transfer Adaptation Learning: A Decade Survey
Transfer Adaptation Learning: A Decade Survey
Lei Zhang
Xinbo Gao
OOD
58
184
0
12 Mar 2019
Domain Adaptation: Learning Bounds and Algorithms
Domain Adaptation: Learning Bounds and Algorithms
Yishay Mansour
M. Mohri
Afshin Rostamizadeh
179
790
0
19 Feb 2009
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