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Multi-domain learning (MDL) aims at obtaining a model with minimal average risk across multiple domains.
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Domain adaptation for statistical classifiers
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Jiayuan Huang, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, and Bernhard Scholkopf · 2006
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Dynamic proteomics in individual human cells uncovers widespread cell-cycle dependence of nuclear proteins
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Discriminative learning for differing training and test distributions
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A kernel method for the two-sample-problem
Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, and Alexander J. Smola · 2007
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Domain adaptation with multiple sources
Yishay Mansour, Mehryar Mohri, and Afshin Rostamizadeh · 2008
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An empirical analysis of domain adaptation algorithms for genomic sequence analysis
Gabriele Schweikert, Christian Widmer, Bernhard Schölkopf, and Gunnar Rätsch · 2008
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Statistical methods for analysis of high-throughput RNA interference screens
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Learning and domain adaptation
Yishay Mansour · 2009
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Globally optimal stitching of tiled 3D microscopic image acquisitions
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High-content phenotypic profiling of drug response signatures across distinct cancer cells
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Multi-domain learning by confidence-weighted parameter combination
Mark Dredze, Alex Kulesza, and Koby Crammer · 2010
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A survey on transfer learning
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Adapting visual category models to new domains
Kate Saenko, Brian Kulis, Mario Fritz, and Trevor Darrell · 2010
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Torch7: A matlab-like environment for machine learning
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A Survey of Transfer and Multitask Learning in Bioinformatics
Qian Xu and Qiang Yang · 2011
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A method for traffic sign detection in an image with learning from synthetic data
Alexander Chigorin, Gleb Krivovyaz, Alexander Velizhev, and Anton Konushin · 2012
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Annotated high-throughput microscopy image sets for validation
V. Ljosa, K. L. Sokolnicki, and A. E. Carpenter · 2012
Deep reconstruction-classification networks for unsupervised domain adaptation
Muhammad Ghifary, W. Bastiaan Kleijn, Mengjie Zhang, David Balduzzi, and Wen Li · 2016
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Improving drug discovery with high-content phenotypic screens by systematic selection of reporter cell lines
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Domain adaptation by mixture of alignments of second- or higher-order scatter tensors
Piotr Koniusz, Yusuf Tas, and Fatih Porikli · 2016
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Deep transfer learning with joint adaptation networks
Mingsheng Long, Jianmin Wang, and Michael I. Jordan · 2016
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Deep coral: Correlation alignment for deep domain adaptation
Baochen Sun and Kate Saenko · 2016
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NIH Image to ImageJ: 25 years of image analysis
C. A. Schneider, W. S. Rasband, and K. W. Eliceiri · 2012
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Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition
J. Stallkamp, M. Schlipsing, J. Salmen, and C. Igel · 2012
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Generalization bounds for domain adaptation
Chao Zhang, Lei Zhang, and Jieping Ye · 2012
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Connecting the dots with landmarks: Discriminatively learning domain-invariant features for unsupervised domain adaptation
Boqing Gong, Kristen Grauman, and Fei Sha · 2013
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Domain generalization via invariant feature representation
Krikamol Muandet, David Balduzzi, and Bernhard Schölkopf · 2013
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Caffe: Convolutional architecture for fast feature embedding
Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, and Trevor Darrell · 2014
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Return of frustratingly easy domain adaptation
Baochen Sun, Jiashi Feng, and Kate Saenko · 2016
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Unsupervised cross-domain image generation
Yaniv Taigman, Adam Polyak, and Lior Wolf · 2016
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Learning deep feature representations with domain guided dropout for person re-identification
Tong Xiao, Hongsheng Li, Wanli Ouyang, and Xiaogang Wang · 2016
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Improving phenotypic measurements in high-content imaging screens
D. Michael Ando, Cory McLean, and Marc Berndl · 2017
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Combogan: Unrestrained scalability for image domain translation
Asha Anoosheh, Eirikur Agustsson, Radu Timofte, and Luc Van Gool · 2017
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Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros · 2017
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Unsupervised domain adaptation in brain lesion segmentation with adversarial networks
Konstantinos Kamnitsas, Christian Baumgartner, Christian Ledig, Virginia Newcombe, Joanna Simpson, Andrew Kane, David Menon, Aditya Nori, Antonio Criminisi, Daniel Rueckert, and Ben Glocker · 2017
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Unsupervised image-to-image translation networks
Ming-Yu Liu, Thomas Breuel, and Jan Kautz · 2017
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Domain adaptation with randomized multilinear adversarial networks
Mingsheng Long, Zhangjie Cao, Jianmin Wang, and Michael I. Jordan · 2017
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Unified deep supervised domain adaptation and generalization
Saeid Motiian, Marco Piccirilli, Donald A. Adjeroh, and Gianfranco Doretto · 2017
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Generate to adapt: Aligning domains using generative adversarial networks
Swami Sankaranarayanan, Yogesh Balaji, Carlos D. Castillo, and Rama Chellappa · 2017
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Adversarial discriminative domain adaptation
Eric Tzeng, Judy Hoffman, Kate Saenko, and Trevor Darrell · 2017
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Leveraging heterogeneity across multiple data sets increases accuracy of cell-mixture deconvolution and reduces biological and technical biases
Francesco Vallania, Andrew Tam, Shane Lofgren, Steven Schaffert, Tej D. Azad, Erika Bongen, Meia Alsup, Michael Alonso, Mark Davis, Edgar Engleman, and Purvesh Khatri · 2017
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Dualgan: Unsupervised dual learning for image-to-image translation
Zili Yi, Hao (Richard) Zhang, Ping Tan, and Minglun Gong · 2017
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Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A. Efros · 2017
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Partial transfer learning with selective adversarial networks
Zhangjie Cao, Mingsheng Long, Jianmin Wang, and Michael I. Jordan · 2018
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Stargan: Unified generative adversarial networks for multi-domain image-to-image translation
Yunjey Choi, Minje Choi, Munyoung Kim, Jung-Woo Ha, Sunghun Kim, and Jaegul Choo · 2018
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Deepjdot: Deep joint distribution optimal transport for unsupervised domain adaptation
Bharath Bhushan Damodaran, Benjamin Kellenberger, Rémi Flamary, Devis Tuia, and Nicolas Courty · 2018
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Multi-adversarial domain adaptation
Zhongyi Pei, Zhangjie Cao, Mingsheng Long, and Jianmin Wang · 2018
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A DIRT-T approach to unsupervised domain adaptation
Rui Shu, Hung H. Bui, Hirokazu Narui, and Stefano Ermon · 2018
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Importance weighted adversarial nets for partial domain adaptation
Jing Zhang, Zewei Ding, Wanqing Li, and Philip Ogunbona · 2018
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