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ORCIDKai Yu 0001
Person information
- affiliation: Baidu Inc., Institute of Deep Learning, Beijing, China
- affiliation (former): NEC Laboratories America, Cupertino, CA, USA
- affiliation (former): Siemens AG, Corporate Technology, Munich, Germany
- affiliation (PhD 2004): Ludwig Maximilian University of Munich, Germany
Other persons with the same name
- Kai Yu — disambiguation page
- Kai Yu 0002 — Royal Institute of Technology, Stockholm, Sweden
- Kai Yu 0003
![[0000-0002-4778-4389]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0002-4778-4389")
— University of Minnesota, Department of Biomedical Engineering, Minneapolis, MN, USA - Kai Yu 0004 — Shanghai Jiao Tong University, Computer Science and Engineering Department, China (and 1 more)
- Kai Yu 0005 — Zhejiang University, State Key Laboratory of Industrial Control Technology, Hangzhou, China
- Kai Yu 0006 — Beijing Normal University, School of Geography, China (and 1 more)
- Kai Yu 0007 — Hohai University, College of Oceanography, Nanjing, China (and 2 more)
- Kai Yu 0008 — Guangdong University of Technology, School of Information Engineering, School of Integrated Circuits, China (and 1 more)
- Kai Yu 0009 — Soochow University, School of Electronics and Information Engineering, Jiangsu, China (and 1 more)
- Kai Yu 0010 — Nanjing University, School of Electronic Science and Engineering, China
- Kai Yu 0011 — Sun Yat-Sen University, Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, China
- Kai Yu 0012 — Chinese Academy of Sciences, Shanghai Institute of Microsystem and Information Technology, China
- Kai Yu 0013 — Beihang University, School of Computer Science and Engineering, State Key Laboratory of Software Development Environment, China
- Kai Yu 0014 — Nanjing University of Aeronautics and Astronautics, College of Electronic and Information Engineering, China
- Kai Yu 0015 — Shandong University of Science and Technology, College of Mining and Safety Engineering, Qingdao, China
- Kai Yu 0016 — Intel Corporation, Hillsboro, OR, USA (and 1 more)
- Kai Yu 0017 — Nankai University, Chern Institute of Mathematics and LPMC, Tianjin, China
- Kai Yu 0018 — Hangzhou Normal University, Department of Information Science and Technology, China (and 2 more)
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2010 – 2019
- 2016
[j7]Krishnakumar Balasubramanian, Kai Yu, Guy Lebanon:
Smooth sparse coding via marginal regression for learning sparse representations. Artif. Intell. 238: 83-95 (2016)- 2015
- [j6]Shaoting Zhang, Ming Yang, Timothée Cour, Kai Yu, Dimitris N. Metaxas:
Query Specific Rank Fusion for Image Retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 37(4): 803-815 (2015) - [c71]Andrei Z. Broder, Lada A. Adamic, Michael J. Franklin, Maarten de Rijke, Eric P. Xing, Kai Yu:
Big Data: New Paradigm or "Sound and Fury, Signifying Nothing"? WSDM 2015: 5-6 - [i6]Zhiheng Huang, Wei Xu, Kai Yu:
Bidirectional LSTM-CRF Models for Sequence Tagging. CoRR abs/1508.01991 (2015) - 2013
- [j5]Shuiwang Ji, Wei Xu, Ming Yang, Kai Yu:
3D Convolutional Neural Networks for Human Action Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 35(1): 221-231 (2013) - [c70]Kai Yu:
Large-scale deep learning at Baidu. CIKM 2013: 2211-2212 - [c69]Krishnakumar Balasubramanian, Kai Yu, Guy Lebanon:
Smooth Sparse Coding via Marginal Regression for Learning Sparse Representations. ICML (3) 2013: 289-297 - [c68]Krishnakumar Balasubramanian, Kai Yu, Tong Zhang:
High-dimensional Joint Sparsity Random Effects Model for Multi-task Learning. UAI 2013 - [i5]Krishnakumar Balasubramanian, Kai Yu, Tong Zhang:
High-dimensional Joint Sparsity Random Effects Model for Multi-task Learning. CoRR abs/1309.6814 (2013) - 2012
- [c67]Olga Russakovsky, Yuanqing Lin, Kai Yu, Li Fei-Fei:
Object-Centric Spatial Pooling for Image Classification. ECCV (2) 2012: 1-15 - [c66]Chunhui Gu, Pablo Andrés Arbeláez, Yuanqing Lin, Kai Yu, Jitendra Malik:
Multi-component Models for Object Detection. ECCV (4) 2012: 445-458 - [c65]Shaoting Zhang, Ming Yang, Timothée Cour, Kai Yu, Dimitris N. Metaxas:
Query Specific Fusion for Image Retrieval. ECCV (2) 2012: 660-673 - [c64]Will Y. Zou, Andrew Y. Ng, Shenghuo Zhu, Kai Yu:
Deep Learning of Invariant Features via Simulated Fixations in Video. NIPS 2012: 3212-3220 - [i4]Zhao Xu, Volker Tresp, Kai Yu, Hans-Peter Kriegel:
Infinite Hidden Relational Models. CoRR abs/1206.6864 (2012) - [i3]Krishnakumar Balasubramanian, Kai Yu, Guy Lebanon:
Smooth Sparse Coding via Marginal Regression for Learning Sparse Representations. CoRR abs/1210.1121 (2012) - [i2]Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying Ma, HongJiang Zhang:
Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes. CoRR abs/1212.2508 (2012) - [i1]Chang Huang, Shenghuo Zhu, Kai Yu:
Large Scale Strongly Supervised Ensemble Metric Learning, with Applications to Face Verification and Retrieval. CoRR abs/1212.6094 (2012) - 2011
- [c63]Xiaoyu Wang, Ming Yang, Kai Yu:
Efficient re-ranking in vocabulary tree based image retrieval. ACSCC 2011: 855-859 - [c62]Ming Yang, Shenghuo Zhu, Fengjun Lv, Kai Yu:
Correspondence driven adaptation for human profile recognition. CVPR 2011: 505-512 - [c61]Yuanqing Lin, Fengjun Lv, Shenghuo Zhu, Ming Yang, Timothée Cour, Kai Yu, Liangliang Cao, Thomas S. Huang:
Large-scale image classification: Fast feature extraction and SVM training. CVPR 2011: 1689-1696 - [c60]Kai Yu, Yuanqing Lin, John D. Lafferty:
Learning image representations from the pixel level via hierarchical sparse coding. CVPR 2011: 1713-1720 - [c59]Xiaoyu Wang, Ming Yang, Timothée Cour, Shenghuo Zhu, Kai Yu, Tony X. Han:
Contextual weighting for vocabulary tree based image retrieval. ICCV 2011: 209-216 - [c58]Ming Yang, Kai Yu:
Real-time clothing recognition in surveillance videos. ICIP 2011: 2937-2940 - 2010
- [j4]Shenghuo Zhu, Dingding Wang, Kai Yu, Tao Li, Yihong Gong:
Feature Selection for Gene Expression Using Model-Based Entropy. IEEE ACM Trans. Comput. Biol. Bioinform. 7(1): 25-36 (2010) - [c57]Jinjun Wang, Jianchao Yang, Kai Yu, Fengjun Lv, Thomas S. Huang, Yihong Gong:
Locality-constrained Linear Coding for image classification. CVPR 2010: 3360-3367 - [c56]Jianchao Yang, Kai Yu, Thomas S. Huang:
Supervised translation-invariant sparse coding. CVPR 2010: 3517-3524 - [c55]Jianchao Yang, Kai Yu, Thomas S. Huang:
Efficient Highly Over-Complete Sparse Coding Using a Mixture Model. ECCV (5) 2010: 113-126 - [c54]Xi Zhou, Kai Yu, Tong Zhang, Thomas S. Huang:
Image Classification Using Super-Vector Coding of Local Image Descriptors. ECCV (5) 2010: 141-154 - [c53]Douglas Gray, Kai Yu, Wei Xu, Yihong Gong:
Predicting Facial Beauty without Landmarks. ECCV (6) 2010: 434-447 - [c52]Shuiwang Ji, Wei Xu, Ming Yang, Kai Yu:
3D Convolutional Neural Networks for Human Action Recognition. ICML 2010: 495-502 - [c51]Kai Yu, Tong Zhang:
Improved Local Coordinate Coding using Local Tangents. ICML 2010: 1215-1222 - [c50]Yuanqing Lin, Tong Zhang, Shenghuo Zhu, Kai Yu:
Deep Coding Network. NIPS 2010: 1405-1413 - [c49]Ming Yang, Yuanqing Lin, Fengjun Lv, Shenghuo Zhu, Kai Yu, Mert Dikmen, Liangliang Cao, Thomas S. Huang:
Videos Semantic Indexing using Image Classification. TRECVID 2010
2000 – 2009
- 2009
- [c48]Jianchao Yang, Kai Yu, Yihong Gong, Thomas S. Huang:
Linear spatial pyramid matching using sparse coding for image classification. CVPR 2009: 1794-1801 - [c47]Ming Yang, Fengjun Lv, Wei Xu, Kai Yu, Yihong Gong:
Human action detection by boosting efficient motion features. ICCV Workshops 2009: 522-529 - [c46]Volker Tresp, Kai Yu:
Tutorial summary: Learning with dependencies between several response variables. ICML 2009: 14 - [c45]Kai Yu, John D. Lafferty, Shenghuo Zhu, Yihong Gong:
Large-scale collaborative prediction using a nonparametric random effects model. ICML 2009: 1185-1192 - [c44]Guangyu Zhu, Ming Yang, Kai Yu, Wei Xu, Yihong Gong:
Detecting video events based on action recognition in complex scenes using spatio-temporal descriptor. ACM Multimedia 2009: 165-174 - [c43]Kai Yu, Tong Zhang, Yihong Gong:
Nonlinear Learning using Local Coordinate Coding. NIPS 2009: 2223-2231 - [c42]Kai Yu, Shenghuo Zhu, John D. Lafferty, Yihong Gong:
Fast nonparametric matrix factorization for large-scale collaborative filtering. SIGIR 2009: 211-218 - [c41]Lanbo Zhang, Jadiel de Arma, Kai Yu:
UCSC at Relevance Feedback Track. TREC 2009 - [c40]Ming Yang, Shuiwang Ji, Wei Xu, Jinjun Wang, Fengjun Lv, Kai Yu, Yihong Gong, Mert Dikmen, Dennis J. Lin, Thomas S. Huang:
Detecting Human Actions in Surveillance Videos. TRECVID 2009 - 2008
- [c39]Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xing:
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks. ECCV (3) 2008: 69-82 - [c38]Kai Yu, Wei Xu, Yihong Gong:
Deep Learning with Kernel Regularization for Visual Recognition. NIPS 2008: 1889-1896 - [c37]Shenghuo Zhu, Kai Yu, Yihong Gong:
Stochastic Relational Models for Large-scale Dyadic Data using MCMC. NIPS 2008: 1993-2000 - [c36]Kai Yu, Shenghuo Zhu, Wei Xu, Yihong Gong:
Non-greedy active learning for text categorization using convex transductive experimental design. SIGIR 2008: 635-642 - [c35]Mert Dikmen, Huazhong Ning, Dennis J. Lin, Liangliang Cao, Vuong Le, Shen-Fu Tsai, Kai-Hsiang Lin, Zhen Li, Jianchao Yang, Thomas S. Huang, Fengjun Lv, Wei Xu, Ming Yang, Kai Yu, Guangyu Zhu, Yihong Gong:
Surveillance Event Detection. TRECVID 2008 - [c34]Ding Zhou, Shenghuo Zhu, Kai Yu, Xiaodan Song, Belle L. Tseng, Hongyuan Zha, C. Lee Giles:
Learning multiple graphs for document recommendations. WWW 2008: 141-150 - 2007
- [c33]Mingrui Wu, Kai Yu, Shipeng Yu, Bernhard Schölkopf:
Local learning projections. ICML 2007: 1039-1046 - [c32]Shipeng Yu, Volker Tresp, Kai Yu:
Robust multi-task learning with t-processes. ICML 2007: 1103-1110 - [c31]Zhao Xu, Volker Tresp, Shipeng Yu, Kai Yu, Hans-Peter Kriegel:
Fast Inference in Infinite Hidden Relational Models. MLG 2007 - [c30]Kai Yu, Wei Chu:
Gaussian Process Models for Link Analysis and Transfer Learning. NIPS 2007: 1657-1664 - [c29]Shenghuo Zhu, Kai Yu, Yihong Gong:
Predictive Matrix-Variate t Models. NIPS 2007: 1721-1728 - [c28]Shenghuo Zhu, Kai Yu, Yun Chi, Yihong Gong:
Combining content and link for classification using matrix factorization. SIGIR 2007: 487-494 - 2006
- [j3]Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel:
Multi-Output Regularized Feature Projection. IEEE Trans. Knowl. Data Eng. 18(12): 1600-1613 (2006) - [c27]Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel:
Variational Bayesian Dirichlet-Multinomial Allocation for Exponential Family Mixtures. ECML 2006: 841-848 - [c26]Kai Yu, Jinbo Bi, Volker Tresp:
Active learning via transductive experimental design. ICML 2006: 1081-1088 - [c25]Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel:
Collaborative ordinal regression. ICML 2006: 1089-1096 - [c24]Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel, Mingrui Wu:
Supervised probabilistic principal component analysis. KDD 2006: 464-473 - [c23]Kai Yu, Wei Chu, Shipeng Yu, Volker Tresp, Zhao Xu:
Stochastic Relational Models for Discriminative Link Prediction. NIPS 2006: 1553-1560 - [c22]Zhao Xu, Volker Tresp, Kai Yu, Hans-Peter Kriegel:
Infinite Hidden Relational Models. UAI 2006 - 2005
- [c21]Kai Yu, Shipeng Yu, Volker Tresp:
Dirichlet Enhanced Latent Semantic Analysis. AISTATS 2005: 437-444 - [c20]Kai Yu, Shipeng Yu, Volker Tresp:
Multi-Output Regularized Projection. CVPR (2) 2005: 597-602 - [c19]Yi Huang, Kai Yu, Matthias Schubert, Shipeng Yu, Volker Tresp, Hans-Peter Kriegel:
Hierarchy-Regularized Latent Semantic Indexing. ICDM 2005: 178-185 - [c18]Zhao Xu, Volker Tresp, Kai Yu, Shipeng Yu, Hans-Peter Kriegel:
Dirichlet enhanced relational learning. ICML 2005: 1004-1011 - [c17]Kai Yu, Volker Tresp, Anton Schwaighofer:
Learning Gaussian processes from multiple tasks. ICML 2005: 1012-1019 - [c16]Shipeng Yu, Kai Yu, Volker Tresp:
Soft Clustering on Graphs. NIPS 2005: 1553-1560 - [c15]Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel:
A Probabilistic Clustering-Projection Model for Discrete Data. PKDD 2005: 417-428 - [c14]Kai Yu, Shipeng Yu, Volker Tresp:
Multi-label informed latent semantic indexing. SIGIR 2005: 258-265 - 2004
- [b1]Kai Yu:
Statistical learning approaches to information filtering. Ludwig Maximilian University of Munich, Germany, 2004, pp. 1-123 - [j2]Kai Yu, Anton Schwaighofer, Volker Tresp, Xiaowei Xu, Hans-Peter Kriegel:
Probabilistic Memory-Based Collaborative Filtering. IEEE Trans. Knowl. Data Eng. 16(1): 56-69 (2004) - [c13]Kai Yu, Volker Tresp:
Heterogenous Data Fusion via a Probabilistic Latent-Variable Model. ARCS 2004: 20-30 - [c12]Kai Yu, Shipeng Yu, Volker Tresp:
Dirichlet Enhanced Latent Semantic Analysis. LWA 2004: 221-226 - [c11]Anton Schwaighofer, Volker Tresp, Kai Yu:
Learning Gaussian Process Kernels via Hierarchical Bayes. NIPS 2004: 1209-1216 - [c10]Kai Yu, Volker Tresp, Shipeng Yu:
A nonparametric hierarchical bayesian framework for information filtering. SIGIR 2004: 353-360 - 2003
- [j1]Kai Yu, Xiaowei Xu, Martin Ester, Hans-Peter Kriegel:
Feature Weighting and Instance Selection for Collaborative Filtering: An Information-Theoretic Approach*. Knowl. Inf. Syst. 5(2): 201-224 (2003) - [c9]Zhao Xu, Xiaowei Xu, Kai Yu, Volker Tresp:
A Hybrid Relevance-Feedback Approach to Text Retrieval. ECIR 2003: 281-293 - [c8]Zhao Xu, Kai Yu, Volker Tresp, Xiaowei Xu, Jizhi Wang:
Representative Sampling for Text Classification Using Support Vector Machines. ECIR 2003: 393-407 - [c7]Volker Tresp, Kai Yu:
An Introduction to Nonparametric Hierarchical Bayesian Modelling with a Focus on Multi-agent Learning. European Summer School on Multi-AgentControl 2003: 290-312 - [c6]Kai Yu, Wei-Ying Ma, Volker Tresp, Zhao Xu, Xiaofei He, HongJiang Zhang, Hans-Peter Kriegel:
Knowing a tree from the forest: art image retrieval using a society of profiles. ACM Multimedia 2003: 622-631 - [c5]Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying Ma, HongJiang Zhang:
Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes. UAI 2003: 616-623 - 2002
- [c4]Kai Yu, Xiaowei Xu, Anton Schwaighofer, Volker Tresp, Hans-Peter Kriegel:
Removing redundancy and inconsistency in memory-based collaborative filtering. CIKM 2002: 52-59 - [c3]Kai Yu, Xiaowei Xu, Jianjua Tao, Martin Ester, Hans-Peter Kriegel:
Instance Selection Techniques for Memory-based Collaborative Filtering. SDM 2002: 59-74 - 2001
- [c2]Kai Yu, Xiaowei Xu, Martin Ester, Hans-Peter Kriegel:
Selecting Relevant Instances for Efficient and Accurate Collaborative Filtering. CIKM 2001: 239-246 - [c1]Kai Yu, Zhong Wen, Xiaowei Xu, Martin Ester:
Feature Weighting Methods for Improving the Accuracy of Collaborative Filtering (Invited Address). DEXA Workshop 2001: 285-290
Coauthor Index
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