BibSLEIGH — Jian

Travelled to:

1 × Australia
1 × Austria
1 × Chile
1 × France
1 × Japan
1 × Spain
1 × USA
2 × China
2 × United Kingdom

Collaborated with:

H.Lu C.Leng Q.Liu K.Wang X.Zhang Z.Li T.Yuan J.Wang J.Wu S.Qiu Q.Song L.Ma Y.Fu Y.Chen S.Ma S.Drüe G.Hartmann J.Thiem Z.Zhu K.Chen C.Huo Z.Zhou H.Zhang J.Wang X.Bai J.Zhou H.Zhao Y.Fang J.Liu

Talks about:

base (6) imag (4) recommend (3) object (3) kernel (3) detect (3) multi (3) learn (3) constraint (2) approach (2)

Person: Jian Cheng

DBLP: Cheng:Jian

Contributed to:

2015

2014

2012

2008

2006

2004

2000

Wrote 17 papers:

ICML-2015-LengWCZL #distributed: Hashing for Distributed Data (CL, JW, JC, XZ, HL), pp. 1642–1650.
RecSys-2015-SongCL #incremental #matrix #recommendation: Incremental Matrix Factorization via Feature Space Re-learning for Recommender System (QS, JC, HL), pp. 277–280.
SIGIR-2015-ZhangCQZL #multi #personalisation #recommendation #similarity: When Personalization Meets Conformity: Collective Similarity based Multi-Domain Recommendation (XZ, JC, SQ, ZZ, HL), pp. 1019–1022.
CIKM-2014-LengCWZL #constraints: Supervised Hashing with Soft Constraints (CL, JC, JW, XZ, HL), pp. 1851–1854.
SIGIR-2014-ChengYWL #behaviour #multi #recommendation: Group latent factor model for recommendation with multiple user behaviors (JC, TY, JW, HL), pp. 995–998.
SIGIR-2014-LengCL #image #learning #random #retrieval #scalability: Random subspace for binary codes learning in large scale image retrieval (CL, JC, HL), pp. 1031–1034.
SIGIR-2014-QiuCYLL #learning #personalisation #ranking: Item group based pairwise preference learning for personalized ranking (SQ, JC, TY, CL, HL), pp. 1219–1222.
ICPR-2012-ZhangWBZCZ #detection #feature model: Object detection via foreground contour feature selection and part-based shape model (HZ, JW, XB, JZ, JC, HZ), pp. 2524–2527.
ICPR-2008-ChenHCZL #adaptation #detection #markov #random: Change detection based on adaptive Markov Random Fields (KC, CH, JC, ZZ, HL), pp. 1–4.
ICPR-2008-FangCWWLL #recognition: Hand posture recognition with co-training (YF, JC, JW, KW, JL, HL), pp. 1–4.
ICPR-2008-FuCLL #approach #automation #segmentation: Saliency Cuts: An automatic approach to object segmentation (YF, JC, ZL, HL), pp. 1–4.
ICPR-2008-LiLCL #approach #image #segmentation: A variational inference based approach for image segmentation (ZL, QL, JC, HL), pp. 1–4.
ICPR-2008-MaCL #collaboration #constraints #invariant #kernel #multi: Multi-cue collaborative kernel tracking with cross ratio invariant constraint (LM, JC, HL), pp. 1–4.
ICPR-v2-2006-ChengW #feedback #image #multi #retrieval: Multi-View Sampling for Relevance Feedback in Image Retrieval (JC, KW), pp. 881–884.
ICPR-v1-2004-ChengLLC #classification #component #independence #kernel #using: Texture Classification Using Kernel Independent Component Analysi (JC, QL, HL, YWC), pp. 620–623.
ICPR-v3-2004-LiuCLM #distance #image #kernel #re-engineering: Distance Based Kernel PCA Image Reconstruction (QL, JC, HL, SM), pp. 670–673.
ICPR-v1-2000-ChengDHT #detection #performance: Efficient Detection and Extraction of Color Objects from Complex Scenes (JC, SD, GH, JT), pp. 1668–1671.