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Recently, DNN model compression based on network architecture design, e.g., SqueezeNet, attracted a lot attention.
Improving Predictive Inference under Convriate Shift by Weighting the Log-Likelihood Function
H. Shimodaira · 2000
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Correcting Sample Selection Bias by Unlabeled Data
J. Huang, A. J. Smola, A. Gretton, K. M. Borgwardt, and B. Scholkopf · 2006
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A Kernel Method for the Two-Sample-Problem
A. Gretton, K. M. Borgwardt, M. Rasch, B. Scholkopf, and A. J. Smola · 2006
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Caltech-256 Object Category Dataset
G. Griffin, A. Holub, and P. Perona · 2007
Earlier work this paper cites.
Adapting Visual Category Models to New Domains
K. Saenko, B. Kulis, M. Fritz, and T. Darrell · 2010
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Domain adaptation for large-scale sentiment classification: A deep learning approach
X. Glorot, A. Bordes, and Y. Bengio · 2011
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Domain Adaptation via Transfer Component Analysis
S. J. Pan, I. W. Tsang, J. T. Kwok, and Q. Yang · 2011
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Unbiased look at dataset bias
A. Torralba and A. Efros · 2011
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ImageNet Classification with Deep Convolutional Neural Network
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Geodesic Flow Kernel for Unsupervised Domain Adaptation
B. Gong, Y. Shi, F. Sha, and K. Grauman · 2012
Earlier work this paper cites.
Optimal Kernel Choice for Large-Scale Two-Sample Tests
A. Gretton, B. Sriperumbudur, D. Sejdinovic, H. Strathmann, S. Balakrishnan, M. Pontil, and K. Fukumizu · 2012
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Generalized Domain-Adaptive Dictionaries
S. Shekhar, V. M. Patel, H. V. Nguyen, and R. Chellappa · 2013
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Unsupervised Visual Domain Adaptation Using Subspace Alignment
B. Fernando, A. Habrard, M. Sebban, and T. Tuytelaars · 2013
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DLID: Deep Learning for Domain Adaptation by Interpolating between Domains
S. Chopra, S. Balakrishnan, and R. Gopalan · 2013
Cited alongside, same era.
Rotation, Scaling and Deformation Invariant Scattering for Texture Discrimination
L. Sifre and S. Mallat · 2013
Cited alongside, same era.
Connecting the DOTs with Landmarks: Discriminatively Learning Domain-Invariant Features for Unsupervised Domain Adaptation
B. Gong, K. Grauman, and F. Sha · 2013
Cited alongside, same era.
Deep Domain Confusion: Maximizing for Domain Invariance
E. Tzeng, J. Hoffman, N. Zhang, K. Saenko, and T. Darrell · 2014
Cited alongside, same era.
Learning Deconvolution Network for Semantic Segmentation
H. Noh, S. Hong, and B. Han · 2015
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Decoupled Deep Network for Semi-Supervised Semantic Segmentation
S. Hong, H. Noh, and B. Han · 2015
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SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
V. Badrinarayanan, A. Kendall, and R. Cipolla · 2015
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Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan and A. Zisserman · 2015
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Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
S. Han, H. Mao, and W. J. Dally · 2016
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Learning Structured Sparsity in Deep Neural Networks
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Caffe: Convolutional Architecture for Fast Feature Embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell · 2014
Cited alongside, same era.
Sparse Convolutional Neural Networks
B. Liu, M. Wang, H. Foroosh, M. Tappen, and M. Pensky · 2015
Cited alongside, same era.
Going Deeper with Convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, and S. Reed · 2015
Cited alongside, same era.
ImageNet Large Scale Visual Recognition Challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and F. F. Li · 2015
Cited alongside, same era.
Unsupervised Domain Adaptation by Backpropagation
Y. Ganin and V. Lempitsky · 2015
Cited alongside, same era.
Deep Residual Learning for Image Recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2015
Cited alongside, same era.
Image Super-Resolution Using Deep Convolutional Networks
C. Dong, C. C. Loy, K. He, and X. Tang · 2015
Cited alongside, same era.
W. Wen, C. Wu, Y. Wang, Y. Chen, and H. Li · 2016
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SqueezeNet: AlexNet-level Accuracy with 50x Fewer Parameters and
F. N. Iandola, S. Han, M. W. Moskewicz, K. Ashraf, W. J. Dally, and K. Keutzer · 2016
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Factorized Convolutional Neural Networks
M. Wang, B. Liu, and H. Foroosh · 2016
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ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
A. Paszke, A. Chaurasia, S. Kim, and E. Culurciello · 2016
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Unsupervised Domain Adaptation with Residual Transfer Networks
M. Long, J. Wang, and M. I. Jordan · 2016
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Learning Transferrable Representations for Unsupervised Domain Adaptation
O. Sener, H. O. Song, A. Saxena, and S. Savarese · 2016
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Multi-scale Context Aggregation by Dilated Convolutions
F. Yu and V. Koltun · 2016
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