Yangqing Jia
Yangqing Jia
VP, Alibaba Group
Verified email at daggerfs.com - Homepage
Cited by
Cited by
Going deeper with convolutions
C Szegedy, W Liu, Y Jia, P Sermanet, S Reed, D Anguelov, D Erhan, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2015
Tensorflow: A system for large-scale machine learning
M Abadi, P Barham, J Chen, Z Chen, A Davis, J Dean, M Devin, ...
12th {USENIX} symposium on operating systems design and implementation …, 2016
Caffe: Convolutional architecture for fast feature embedding
Y Jia, E Shelhamer, J Donahue, S Karayev, J Long, R Girshick, ...
Proceedings of the 22nd ACM international conference on Multimedia, 675-678, 2014
TensorFlow: Large-scale machine learning on heterogeneous systems
M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ...
Decaf: A deep convolutional activation feature for generic visual recognition
J Donahue, Y Jia, O Vinyals, J Hoffman, N Zhang, E Tzeng, T Darrell
International conference on machine learning, 647-655, 2014
Accurate, large minibatch sgd: Training imagenet in 1 hour
P Goyal, P Dollár, R Girshick, P Noordhuis, L Wesolowski, A Kyrola, ...
arXiv preprint arXiv:1706.02677, 2017
Matchnet: Unifying feature and metric learning for patch-based matching
X Han, T Leung, Y Jia, R Sukthankar, AC Berg
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015
A category-level 3d object dataset: Putting the kinect to work
A Janoch, S Karayev, Y Jia, JT Barron, M Fritz, K Saenko, T Darrell
Consumer depth cameras for computer vision, 141-165, 2013
Fbnet: Hardware-aware efficient convnet design via differentiable neural architecture search
B Wu, X Dai, P Zhang, Y Wang, F Sun, Y Wu, Y Tian, P Vajda, Y Jia, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
Deep convolutional ranking for multilabel image annotation
Y Gong, Y Jia, T Leung, A Toshev, S Ioffe
arXiv preprint arXiv:1312.4894, 2013
Large-scale object classification using label relation graphs
J Deng, N Ding, Y Jia, A Frome, K Murphy, S Bengio, Y Li, H Neven, ...
European conference on computer vision, 48-64, 2014
SNAS: stochastic neural architecture search
S Xie, H Zheng, C Liu, L Lin
arXiv preprint arXiv:1812.09926, 2018
Trace ratio criterion for feature selection
F Nie, S Xiang, Y Jia, C Zhang, S Yan
Proceedings of the 23rd national conference on Artificial intelligence 2 …, 2008
Beyond spatial pyramids: Receptive field learning for pooled image features
Y Jia, C Huang, T Darrell
2012 IEEE Conference on Computer Vision and Pattern Recognition, 3370-3377, 2012
TensorFlow: Large-scale machine learning on heterogeneous systems, software available from tensorflow. org (2015)
M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ...
URL https://www. tensorflow. org, 2015
Applied machine learning at facebook: A datacenter infrastructure perspective
K Hazelwood, S Bird, D Brooks, S Chintala, U Diril, D Dzhulgakov, ...
2018 IEEE International Symposium on High Performance Computer Architecture …, 2018
Trace ratio problem revisited
Y Jia, F Nie, C Zhang
IEEE Transactions on Neural Networks 20 (4), 729-735, 2009
Learning cross-modality similarity for multinomial data
Y Jia, M Salzmann, T Darrell
2011 International Conference on Computer Vision, 2407-2414, 2011
Tensorflow: large-scale machine learning on heterogeneous distributed systems (2016)
M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ...
arXiv preprint arXiv:1603.04467 172, 2015
Factorized latent spaces with structured sparsity
Y Jia, M Salzmann, T Darrell
Advances in Neural Information Processing Systems 23, 982-990, 2010
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