I am a deputy engeering director of
Baidu, managing the company's multimedia department. My team innovates search technologies and products everyday, by making better use of
speech, images, videos, and musics. Before April 2012, I led the media analytics department of NEC Labs in northen California,
developing intelligent systems involving machine learning, image recognition, multimedia search,
data mining, and human-computer interface. Before joining NEC, I was a senior research scientist at Siemens.
I obtained PhD in Computer Science at
University of Munich, Germany, in July 2004.
2012 Object-centric
Spatial Pooling for Image Classification [pdf] Olga Russakovsky, Yuanqing
Lin, Kai Yu, and Fei-Fei Li To appear in Proceedings of the 12th European Conference on Computer
Vision (ECCV 2012) Multi-Component
Models for Object Detection [pdf] Chunhui Gu,
Pablo Arbelaez, Yuanqing
Lin, Kai Yu, and Jitendra Malik To appear in Proceedings of the 12th European Conference on Computer
Vision (ECCV 2012) Query Specific
Fusion for Image Retrieval [pdf] Shaoting Zhang, Ming Yang, Timothee Cour, Kai Yu, and Dimitris Metaxas To appear in Proceedings of the 12th European Conference on Computer
Vision (ECCV 2012) 3D Convolutional
Neural Networks for Human Action Recognition [pdf] Shuiwang Ji,
Wei Xu, Ming Yang, and Kai Yu To appear in IEEE Transactions on Pattern Analysis and Machine
Intelligence (TPAMI) 2011 Contextual
Weighting for Vocabulary Tree based Image Retrieval [pdf] Xiaoyu Wang, Ming Yang, Timothee Cour, Shenghuo Zhu, Kai Yu, and Tony X. Han Proceedings of IEEE International Conference on Computer Vision (ICCV
2011) Real-time clothing
recognition in surveillance videos [pdf] Ming Yang and Kai Yu To Appear in Proceedings of IEEE Conference on Image Processing (ICIP
2011) Correspondence
Driven Adaptation for Human Profile Recognition [pdf] Ming Yang, Shenghuo Zhu, Fengjun
Lv, and Kai Yu Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
(CVPR 2011) Improve any surveillance system without any labeling Large-scale Image
Classification: Fast Feature Extraction and SVM Training [pdf] Yuanqing Lin, Fengjun
Lv, Shenghuo Zhu, Ming
Yang, Timothee Cour, Kai
Yu, Liangliang Cao, and Thomas Huang Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
(CVPR 2011) Want to know how we won ImageNet 2010? Learning Image
Representations from the Pixel Level via Hierarchical Sparse Coding [pdf] Kai Yu, Yuanqing Lin, and John Lafferty Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
(CVPR 2011) A two-layer sparse coding model that beats sparse coding on SIFT … 2010 Deep Coding
Networks [pdf] Yuanqing Lin, Tong Zhang, Shenghuo Zhu, and Kai Yu Advances in Neural Information Processing Systems 23 (NIPS 2010) Let LCC go deeper … Predicting Facial
Beauty without Landmarks [pdf] Douglas Gray, Kai Yu, Wei Xu, and Yihong Gong Proceedings of the 11th European Conference on Computer Vision (ECCV
2010) A fully automatically trained model to tell how attractive you are … Image
Classification using Super-Vector Coding of Local Image Descriptors [pdf]
Xi Zhou, Kai Yu, Tong Zhang, and Thomas Huang Proceedings of the 11th European Conference on Computer Vision (ECCV
2010) You may not know, this is in fact a special case
of the local tangent stuff. Efficient Highly
Over-Complete Sparse Coding using a Mixture Model [pdf] Jianchao Yang, Kai Yu, and Thomas Huang Proceedings of the 11th European Conference on Computer Vision (ECCV
2010) Making sparse coding a bit more complex … Improved Local
Coordinate Coding using Local Tangents [pdf] Kai Yu, Tong Zhang Proceedings of the 27th International Conference on Machine Learning (ICML
2010) Okay, a simple way to further improve LCC, and
even sparse coding. 3D Convolutional
Neural Networks for Human Action Recognition
[pdf] Shuiwang Ji,
Wei Xu, Ming Yang, and Kai Yu Proceedings of the 27th International Conference on Machine Learning (ICML
2010) First such fully trained deep model for action recognition. Supervised
Translation-Invariant Sparse Coding [pdf] Jianchao Yang, Kai Yu, Thomas Huang Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
(CVPR 2010) Supervised training to further improve sparse coding for classification Learning
Locality-constrained Linear Coding for Image Classification [pdf] Jingjun Wang, Jianchao
Yang, Kai Yu, Fengjun Lv,
Thomas Huang, and Yihong Gong Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
(CVPR 2010) A fast & simplified implementation of
LCC that leads to state-of-the-art performance. 2009 Nonlinear Learning
using Local Coordinate Coding [pdf]
[appendix] Kai Yu, Tong Zhang, and Yihong Gong Advances in Neural Information Processing Systems 22 (NIPS 2009) A longer version in Technical Report arXiv:0906.5190v1 [pdf] A theoretical perspective trying to understand
sparse coding and develop a better one. UCSC at Relevance
Feedback Track [pdf] Lanbo Zhang, Yi Zhang, Jadiel de Arma, and Kai Yu In Proceedings of the 17th Text REtrieval
Conference (TREC), Gaithersburg, USA, 2009 (TREC 2009) We are No.2 position. Active learning using Transductive
Experimental Design rocks! Human Action
Detection by Boosting Efficient Motion Features
[pdf] Ming Yang, Fengjun Lv,
Wei Xu, Kai Yu, Yihong Gong.. IEEE Workshop on Video-oriented Object and Event Classification in
Conjunction with ICCV (VOEC'2009) See how we achieve the best performance of action recognition in TRECVID! Detecting Video
Events Based on Action Recognition in Complex Scenes using Spatio-temporal
Descriptor [pdf] Guangyu Zhu, Ming Yang, Kai Yu, Wei Xu, Yihong Gong. ACM International Conference on Multimedia (ACM MM'2009) Large-scale
Collaborative Prediction Using a Nonparametric Random Effects Model [pdf] [slides] Kai Yu, John Lafferty, Shenghuo Zhu, and Yihong Gong Proceedings of the 26th International Conference on Machine Learning (ICML
2009) A note on inverted Wishart distributions. Beyond matrix factorization – use user and item attributes! Fast Nonparametric
Matrix Factorization for Large-scale Collaborative Filtering [pdf] [code]
Kai Yu, Shenghuo Zhu, John Lafferty, and Yihong Gong Proceedings of the 32nd Annual International ACM SIGIR Conference (SIGIR
2009) One of the best matrix factorization you can find, in accuracy and
efficiency! Linear Spatial
Pyramid Matching Using Sparse Coding for Image Classification [more info] Jianchao Yang, Kai Yu, Yihong Gong, and Thomas Huang IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2009) Can’t believe, linear SVM + Sparse Coding = 73% on Caltech-101! Deep Learning with
Kernel Regularization for Visual Recognition [pdf] Kai Yu, Wei Xu, and Yihong
Gong Advances in Neural Information Processing Systems 21 (NIPS 2008) (Eds.) D. Koller, Y. Bengio,
D. Schuurmans and L. Bottou,
MIT Press, Cambridge, MA, USA, 2009 Stochastic
Relational Models for Large-scale Dyadic Data using MCMC [pdf] [code] Shenghuo Zhu, Kai Yu and Yihong Gong Advances in Neural Information Processing Systems 21 (NIPS 2008) (Eds.) D. Koller, Y. Bengio,
D. Schuurmans and L. Bottou,
MIT Press, Cambridge, MA, USA, 2009 2008 Training
Hierarchical Feed-forward Visual Recognition Models Using Transfer Learning
from Pseudo Tasks [pdf] Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong and Eric P. Xing The 10th European Conference on Computer Vision, (ECCV 08) Oral presentation, acceptance rate 4.6%
Feature Selection
for Gene Expression using Model-based Entropy [draft] Shenghuo Zhu, Dingding
Wang, Kai Yu, Tao Li, and Yihong Gong. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2008 Nonparametric
Relational Learning for Social Network Analysis [pdf] Zhao Xu, Volker Tresp,
Shipeng Yu, and Kai Yu. The 2nd KDD workshop on Social Network Mining and Analysis, (SNA-KDD 08) Non-greedy Active
Learning for Text Categorization using Convex Transductive
Experimental Design [pdf] Kai Yu, Shenghuo Zhu, Wei Xu,
and Yihong Gong Proceedings of the 31st Annual International ACM SIGIR Conference (SIGIR
08) Learning Multiple
Graphs for Document Recommendations [pdf]
Ding Zhou, Shenghuo Zhu, Kai Yu, Xiaodan Song, Belle Tseng, Hongyuan
Zha, and C.Lee Giles Proceedings of the 17th International World Wide Web Conference (WWW08) Gaussian Process
Models for Link Analysis and Transfer Learning [pdf] Kai Yu and Wei Chu Advances in Neural Information Processing Systems 20 (NIPS 2007) (Eds.) Platt, J. C., D. Koller, Y. Singer, S. Roweis, MIT Press, Cambridge, MA, USA, 2008 Predictive Matrix-Variate t Models [pdf]
Shenghuo Zhu, Kai Yu and Yihong Gong Advances in Neural Information Processing Systems 20 (NIPS 2007) (Eds.) Platt, J. C., D. Koller, Y. Singer, S. Roweis, MIT Press, Cambridge, MA, USA, 2008 2007 Robust Multi-Task
Learning with t-Processes [pdf] Shipeng Yu, Volker Tresp,
Kai Yu, and Bharat Rao Proceedings of the 24th International Conference on Machine Learning (ICML
2007) Local Learning
Projection [pdf] Mingrui Wu, Kai Yu, Shipeng
Yu, and Bernhard Schölkopf Proceedings of the 24th International Conference on Machine Learning (ICML
2007) Combining Contents
and Links for Classification using Matrix Factorization [pdf] Shenghuo Zhu, Kai Yu, Yun Chi, and Yihong Gong Proceedings of the 30th Annual International ACM SIGIR Conference (SIGIR
2007) Stochastic
Relational Models for Discriminative Link Prediction [pdf] [data] Kai Yu, Wei Chu, Shipeng Yu, Volker Tresp, and Zhao Xu Advances in Neural Information Processing Systems 19 (NIPS 2006), (Eds.) B. Schölkopf, J. C. Platt and T.
Hofmann, MIT Press, Cambridge, MA USA, 2007 2006 Multi-Output
Regularized Feature Projection [Link] Shipeng Yu, Kai Yu, Volker Tresp, and Hans-Peter Kriegel. IEEE Transactions on Knowledge and Data Engineering (TKDE), 18 (22), pp. 1600-1613,
December 2006. Variational Bayesian Dirichlet-Multinomial
Allocation for Exponential Family Mixtures
Shipeng Yu, Kai Yu, and Volker Tresp, Proceedings of the 17th European Conference on Machine Learning (ECML 2006), 2006 Supervised
Probabilistic Principal Component Analysis [pdf] Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel, and Mingrui Wu Proceedings of the 12th International Conference on Knowledge Discovery
and Data Mining (SIGKDD 2006), 2006
(Acceptance Rate <11%) Infinite Hidden
Relational Models [pdf] Zhao Xu, Volker Tresp,
Kai Yu, and Hans-Peter Kriegel, Proceedings of the 22nd International Conference on Uncertainty in
Artificial Intelligence (UAI 2006), 2006
Active Learning
via Transductive Experimental Design [pdf] [matlab code &
data] Kai Yu, Jinbo Bi, and Volker Tresp, Proceedings of the 23rd
International Conference on Machine Learning (ICML 2006),
2006 Collaborative
Ordinal Regression [pdf] Shipeng Yu, Kai Yu, and Volker Tresp, Proceedings of the 23rd
International Conference on Machine Learning (ICML 2006),
2006 Soft Clustering on
Graphs [pdf] Kai Yu, Shipeng Yu, and Volker Tresp, Advances in Neural Information Processing Systems 18 (NIPS 2005), (Eds.) Y. Weiss, B. Schölkopf, and J. Platt,
MIT Press, Cambridge, MA USA, 2006 2005 Learning to Learn
and Collaborative Filtering [pdf] Kai Yu and Volker Tresp, Workshop on Inductive Transfer: 10 Years Later (NIPS*05 Workshop), Whistler, Canada, Dec. 2005 A Probabilistic
Clustering-Projection Model for Discrete Data [pdf] Shipeng Yu, Kai Yu, Volker Tresp, and Hans-Peter Kriegel, Proceedings of the 9th European Conference on Principles and Practice of
Knowledge Discovery in Databases (PKDD 2005), Porto, Portugal, October 3-7, 2005. (Best Paper Runner-up Award) Learning Gaussian
Processes from Multiple Tasks [pdf]
[slides] Kai Yu, Volker Tresp, and Anton Schwaighofer, Proceedings of the 22nd International Conference on Machine Learning (ICML
2005), Bonn, Germany, 7-11 August, 2005 Dirichlet Enhanced Probabilistic Relational
Model [pdf] Zhao Xu, Volker Tresp,
Kai Yu, Shipeng Yu, and Hans-Peter Kriegel, Proceedings of the 22nd International Conference on Machine Learning (ICML
2005), Bonn, Germany, 7-11 August, 2005 Blockwise Supervised Inference on Large
Graphs [pdf] Kai Yu, Shipeng Yu, and Volker Tresp, Workshop on Learning with Partially Classified Training Data (ICML
2005 Workshop), at the 22nd International
Conference on Machine Learning, Bonn, Germany, 7-11 August, 2005 Multi-Output
Regularized Projection
[pdf] Kai Yu, Shipeng Yu, and Volker Tresp, Proceedings of International IEEE Conference on Computer Vision and
Pattern Recognition (CVPR 2005), San Diego, CA, USA,
June 20-26, 2005. Learning Gaussian
Process Kernels via Hierarchical Bayes [pdf] Anton Schwaighofer, Volker Tresp,
and Kai Yu, Advances in Neural Information Processing Systems 17
(NIPS 2004). (Eds.) Saul, L.K., Y. Weiss and L. Bottou, MIT
Press, Cambridge, MA, USA, 2005. Dirichlet Enhanced Latent Semantic Analysis [pdf] Kai Yu, Shipeng Yu, and Volker Tresp, Proceedings of Artificial Intelligence & Statistics (AISTATS 2005),
Barbados, January 6-8, 2005. Multi-Label
Informed Latent Semantic Indexing
[pdf] Kai Yu, Shipeng Yu, and Volker Tresp, Proceedings of the 28th International ACM SIGIR Conference on Research
and Development in Information Retrieval (SIGIR 2005), August 15-19, 2005, in Salvador, Brazil. 2004 A Nonparametric
Hierarchical Bayesian Framework for Information Filtering [pdf] Kai Yu, Volker Tresp, and Shipeng
Yu, Proceedings of the 27th International ACM SIGIR Conference on Research
and Development in Information Retrieval (SIGIR 2004), Sheffield, UK, July 25 - 29, 2004. An introduction to
nonparametric hierarchical Bayesian modelling with a
focus on multi-agent learning [pdf] Volker Tresp and Kai Yu. book chapter, Switching and Learning
in Feedback Systems. Springer, 2004. Probabilistic
Memory-Based Collaborative Filtering [draft] Kai Yu, Anton Schwaighofer, Volker Tresp, Xiaowei Xu, Hans-Peter Kriegel IEEE Transactions on Knowledge and Data Engineering
(TKDE), Vol.16, No.1, pp. 56--69, 2004. 2003 Approximate
Solutions to Nonparametric Bayesian Hierarchical Modelling
with Applications to Information Filtering [link] Volker Tresp, Kai Yu, Anton Schwaighofer,
Nonparametric Bayesian Methods and Infinite Models, (NIPS*03 Workshop),
Vancouver, Dec. 2003. Collaborative
Ensemble Learning: Combining Collaborative and Content-Based Information
Filtering via Hierarchical Bayes [pdf] Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying Ma, Hongjiang
Zhang, Proceedings of the 19th International Conference on Uncertainty in
Artificial Intelligence (UAI 2003), Acapulco, Mexico, August 7-10, 2003. (Plenary oral presentation, 11%
accepted) Knowing a Tree
from the Forest: Art Image Retrieval using a Society of Profiles [pdf] Kai Yu, Wei-Ying Ma, Volker Tresp, Zhao Xu, Xiaofei He, Hongjiang Zhang and Hans-Peter Kriegel,
Proceedings of the 11th Annual ACM International Conference on Multimedia
(ACM Multimedia 2003), Berkeley, CA, USA, November 2-8, 2003.
Selected Publications