BibSLEIGH — Yihong

Travelled to:

1 × Brazil
1 × Finland
1 × Singapore
1 × Spain
1 × Sweden
1 × The Netherlands
1 × Turkey
1 × United Kingdom
2 × Canada
3 × China
5 × USA

Collaborated with:

S.Zhu W.Xu X.Liu Y.Chi K.Yu D.Wang T.Li M.Han J.D.Lafferty Z.Guo Z.Zhang Y.Zhang X.Ji X.Zhang J.Wang S.Zhang S.Zhang H.Ning Y.Zhou T.S.Huang Z.Chen D.Kong H.Tao

Talks about:

document (8) cluster (6) use (6) factor (5) model (4) classif (3) summar (3) matrix (3) video (3) learn (3)

Person: Yihong Gong

DBLP: Gong:Yihong

Contributed to:

2014

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

Wrote 21 papers:

ICPR-2014-ZhangWGZZ #analysis #using #verification: Low Computation Face Verification Using Class Center Analysis (XZ, JW, YG, SZ, SZ), pp. 4543–4547.
ICPR-2010-GuoZCZG #documentation #learning: Unsupervised Learning from Linked Documents (ZG, SZ, YC, ZZ, YG), pp. 730–733.
CIKM-2009-WangZLG #comparative #documentation #summary: Comparative document summarization via discriminative sentence selection (DW, SZ, TL, YG), pp. 1963–1966.
ICML-2009-YuLZG #collaboration #parametricity #predict #random #scalability #using: Large-scale collaborative prediction using a nonparametric random effects model (KY, JDL, SZ, YG), pp. 1185–1192.
SIGIR-2009-GuoZCZG #documentation #topic: A latent topic model for linked documents (ZG, SZ, YC, ZZ, YG), pp. 720–721.
SIGIR-2009-YuZLG #collaboration #matrix #parametricity #performance #scalability: Fast nonparametric matrix factorization for large-scale collaborative filtering (KY, SZ, JDL, YG), pp. 211–218.
CIKM-2008-ChiZGZ #personalisation #probability #recommendation: Probabilistic polyadic factorization and its application to personalized recommendation (YC, SZ, YG, YZ), pp. 941–950.
CIKM-2008-WangZLCG #clustering #comprehension #documentation #multi #summary: Integrating clustering and multi-document summarization to improve document understanding (DW, SZ, TL, YC, YG), pp. 1435–1436.
ICPR-2008-NingXZGH #detection #difference #learning: Temporal difference learning to detect unsafe system states (HN, WX, YZ, YG, TSH), pp. 1–4.
SIGIR-2008-YuZXG #categorisation #design #learning #using: trNon-greedy active learning for text categorization using convex ansductive experimental design (KY, SZ, WX, YG), pp. 635–642.
VLDB-2008-ZhuLCWG #database: Dynamic active probing of helpdesk databases (SZ, TL, ZC, DW, YG), pp. 748–760.
SIGIR-2007-ZhuYCG #classification #matrix #using: Combining content and link for classification using matrix factorization (SZ, KY, YC, YG), pp. 487–494.
ICPR-v1-2006-HanXG #clustering #segmentation #video: Video Foreground Segmentation Based on Sequential Feature Clustering (MH, WX, YG), pp. 492–496.
ICPR-v3-2006-KongHXTG #random #video: A Conditional Random Field Model for Video Super-resolution (DK, MH, WX, HT, YG), pp. 619–622.
SIGIR-2005-ZhuJXG #classification #multi #using: Multi-labelled classification using maximum entropy method (SZ, XJ, WX, YG), pp. 274–281.
SIGIR-2004-XuG #clustering #concept #documentation: Document clustering by concept factorization (WX, YG), pp. 202–209.
SIGIR-2003-XuLG #clustering #documentation #matrix: Document clustering based on non-negative matrix factorization (WX, XL, YG), pp. 267–273.
SIGIR-2002-LiuGXZ #clustering #documentation #refinement: Document clustering with cluster refinement and model selection capabilities (XL, YG, WX, SZ), pp. 191–198.
ICDAR-2001-GongL #summary: Creating Generic Text Summaries (YG, XL), pp. 903–907.
SIGIR-2001-GongL #analysis #semantics #summary #using: Generic Text Summarization Using Relevance Measure and Latent Semantic Analysis (YG, XL), pp. 19–25.
ICPR-v1-2000-GongL #classification #segmentation #video: Video Shot Segmentation and Classification (YG, XL), pp. 1860–1863.