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Do We Really Need to Access the Source Data? Source Hypothesis Transfer
  for Unsupervised Domain Adaptation

Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation

20 February 2020
Jian Liang
Dapeng Hu
Jiashi Feng
ArXivPDFHTML

Papers citing "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"

25 / 625 papers shown
Title
ConDA: Continual Unsupervised Domain Adaptation
ConDA: Continual Unsupervised Domain Adaptation
A. M. N. Taufique
C. S. Jahan
Andreas E. Savakis
TTA
CLL
14
10
0
19 Mar 2021
Refining Language Models with Compositional Explanations
Refining Language Models with Compositional Explanations
Huihan Yao
Ying Chen
Qinyuan Ye
Xisen Jin
Xiang Ren
20
35
0
18 Mar 2021
Self-Supervised Noisy Label Learning for Source-Free Unsupervised Domain
  Adaptation
Self-Supervised Noisy Label Learning for Source-Free Unsupervised Domain Adaptation
Weijie Chen
Luojun Lin
Shicai Yang
Di Xie
Shiliang Pu
Yueting Zhuang
Wenqi Ren
NoLa
SSL
30
57
0
23 Feb 2021
On Interaction Between Augmentations and Corruptions in Natural
  Corruption Robustness
On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness
Eric Mintun
A. Kirillov
Saining Xie
20
89
0
22 Feb 2021
Domain Adaptation for Medical Image Analysis: A Survey
Domain Adaptation for Medical Image Analysis: A Survey
Hao Guan
Mingxia Liu
OOD
36
529
0
18 Feb 2021
Domain Impression: A Source Data Free Domain Adaptation Method
Domain Impression: A Source Data Free Domain Adaptation Method
V. Kurmi
Venkatesh Subramanian
Vinay P. Namboodiri
TTA
151
150
0
17 Feb 2021
Meta Discovery: Learning to Discover Novel Classes given Very Limited
  Data
Meta Discovery: Learning to Discover Novel Classes given Very Limited Data
Haoang Chi
Feng Liu
Bo Han
Wenjing Yang
L. Lan
Tongliang Liu
Gang Niu
Mingyuan Zhou
Masashi Sugiyama
26
42
0
08 Feb 2021
Complementary Pseudo Labels For Unsupervised Domain Adaptation On Person
  Re-identification
Complementary Pseudo Labels For Unsupervised Domain Adaptation On Person Re-identification
Hao Feng
Minghao Chen
Jinming Hu
Dong Shen
Haifeng Liu
Deng Cai
21
65
0
29 Jan 2021
Source-free Domain Adaptation via Distributional Alignment by Matching
  Batch Normalization Statistics
Source-free Domain Adaptation via Distributional Alignment by Matching Batch Normalization Statistics
Masato Ishii
Masashi Sugiyama
OOD
17
40
0
19 Jan 2021
Mining Data Impressions from Deep Models as Substitute for the
  Unavailable Training Data
Mining Data Impressions from Deep Models as Substitute for the Unavailable Training Data
Gaurav Kumar Nayak
Konda Reddy Mopuri
Saksham Jain
Anirban Chakraborty
11
12
0
15 Jan 2021
Unsupervised Domain Adaptation of Black-Box Source Models
Unsupervised Domain Adaptation of Black-Box Source Models
Haojian Zhang
Yabin Zhang
Kui Jia
Lei Zhang
124
51
0
08 Jan 2021
Hypothesis Disparity Regularized Mutual Information Maximization
Hypothesis Disparity Regularized Mutual Information Maximization
Qicheng Lao
Xiang Jiang
Mohammad Havaei
30
24
0
15 Dec 2020
Source Data-absent Unsupervised Domain Adaptation through Hypothesis
  Transfer and Labeling Transfer
Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer
Jian Liang
Dapeng Hu
Yunbo Wang
Ran He
Jiashi Feng
151
250
0
14 Dec 2020
Select, Label, and Mix: Learning Discriminative Invariant Feature
  Representations for Partial Domain Adaptation
Select, Label, and Mix: Learning Discriminative Invariant Feature Representations for Partial Domain Adaptation
Aadarsh Sahoo
Rameswar Panda
Rogerio Feris
Kate Saenko
Abir Das
VLM
47
20
0
06 Dec 2020
Effective Label Propagation for Discriminative Semi-Supervised Domain
  Adaptation
Effective Label Propagation for Discriminative Semi-Supervised Domain Adaptation
Zhiyong Huang
Kekai Sheng
Weiming Dong
Xing Mei
Chongyang Ma
Feiyue Huang
D. Zhou
Changsheng Xu
15
7
0
04 Dec 2020
Data Augmentation with norm-VAE for Unsupervised Domain Adaptation
Data Augmentation with norm-VAE for Unsupervised Domain Adaptation
Qian Wang
Fanlin Meng
T. Breckon
12
16
0
01 Dec 2020
Unsupervised BatchNorm Adaptation (UBNA): A Domain Adaptation Method for
  Semantic Segmentation Without Using Source Domain Representations
Unsupervised BatchNorm Adaptation (UBNA): A Domain Adaptation Method for Semantic Segmentation Without Using Source Domain Representations
Marvin Klingner
Jan-Aike Termöhlen
Jacob Ritterbach
Tim Fingscheidt
25
39
0
17 Nov 2020
Casting a BAIT for Offline and Online Source-free Domain Adaptation
Casting a BAIT for Offline and Online Source-free Domain Adaptation
Shiqi Yang
Yaxing Wang
Joost van de Weijer
Luis Herranz
Shangling Jui
TTA
91
45
0
23 Oct 2020
Open-Set Hypothesis Transfer with Semantic Consistency
Open-Set Hypothesis Transfer with Semantic Consistency
Zeyu Feng
Chang Xu
Dacheng Tao
8
12
0
01 Oct 2020
A Survey on Negative Transfer
A Survey on Negative Transfer
Wen Zhang
Lingfei Deng
Lei Zhang
Dongrui Wu
AAML
27
205
0
02 Sep 2020
Transductive Information Maximization For Few-Shot Learning
Transductive Information Maximization For Few-Shot Learning
Malik Boudiaf
Imtiaz Masud Ziko
Jérôme Rony
José Dolz
Pablo Piantanida
Ismail Ben Ayed
VLM
12
76
0
25 Aug 2020
Overcoming Concept Shift in Domain-Aware Settings through Consolidated
  Internal Distributions
Overcoming Concept Shift in Domain-Aware Settings through Consolidated Internal Distributions
Mohammad Rostami
Aram Galstyan
CLL
OffRL
6
26
0
01 Jul 2020
Tent: Fully Test-time Adaptation by Entropy Minimization
Tent: Fully Test-time Adaptation by Entropy Minimization
Dequan Wang
Evan Shelhamer
Shaoteng Liu
Bruno A. Olshausen
Trevor Darrell
OOD
37
53
0
18 Jun 2020
Learning Smooth Representation for Unsupervised Domain Adaptation
Learning Smooth Representation for Unsupervised Domain Adaptation
Guanyu Cai
Lianghua He
Mengchu Zhou
H. Alhumade
D. Hu
27
16
0
26 May 2019
Transfer Adaptation Learning: A Decade Survey
Transfer Adaptation Learning: A Decade Survey
Lei Zhang
Xinbo Gao
OOD
50
184
0
12 Mar 2019
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