BibSLEIGH — Changshui

Travelled to:

1 × Australia
1 × Canada
1 × Finland
1 × Germany
1 × Portugal
1 × Taiwan
1 × The Netherlands
2 × China
2 × United Kingdom
6 × USA

Collaborated with:

F.Wang Y.Song B.Zhao M.Qian T.Li Z.Bian P.Gong J.Ye S.Chen Y.Jia S.Wang B.Zhang F.Nie X.Yi Z.Kou F.Wu Y.Zhou H.Peng J.Zhang S.Liu S.Chen B.Liu Y.Xia S.Weng S.Li S.Xiang X.Chen N.Lu J.Lee J.Wang J.He M.Li H.Zhang Z.Lu J.Huang T.Ban S.Abe T.Takahashi Y.Kadobayashi B.Zhang W.J.Yin J.Dong

Talks about:

supervis (5) learn (5) semi (5) regular (4) applic (3) dimension (2) algorithm (2) recognit (2) manifold (2) unlabel (2)

Person: Changshui Zhang

DBLP: Zhang:Changshui

Contributed to:

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

1998

Wrote 23 papers:

ICML-c2-2013-GongZLHY #algorithm #optimisation #problem: A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems (PG, CZ, ZL, JH, JY), pp. 37–45.
KDD-2012-GongYZ #learning #multi #robust: Robust multi-task feature learning (PG, JY, CZ), pp. 895–903.
SAC-2011-BanZATK #mining: Mining interlacing manifolds in high dimensional spaces (TB, CZ, SA, TT, YK), pp. 942–949.
KDD-2010-ZhangSZL #corpus #correlation #multi #process: Evolutionary hierarchical dirichlet processes for multiple correlated time-varying corpora (JZ, YS, CZ, SL), pp. 1079–1088.
CIKM-2009-ChenLQZ #classification: Instance- and bag-level manifold regularization for aggregate outputs classification (SC, BL, MQ, CZ), pp. 1593–1596.
CIKM-2009-QianNZ #multi #performance: Efficient multi-class unlabeled constrained semi-supervised SVM (MQ, FN, CZ), pp. 1665–1668.
CIKM-2008-ChenWSZ #ranking: Semi-supervised ranking aggregation (SC, FW, YS, CZ), pp. 1427–1428.
CIKM-2008-WangCZL #constraints #learning #metric: Semi-supervised metric learning by maximizing constraint margin (FW, SC, CZ, TL), pp. 1457–1458.
ICML-2008-ZhaoWZ #clustering #multi #performance: Efficient multiclass maximum margin clustering (BZ, FW, CZ), pp. 1248–1255.
ICPR-2008-JiaZ #reduction: Local Regularized Least-Square Dimensionality Reduction (YJ, CZ), pp. 1–4.
ICPR-2008-WangZ #collaboration #distributed #learning: Collaborative learning by boosting in distributed environments (SW, CZ), pp. 1–4.
KDD-2008-ZhaoWZ #algorithm #named #performance #virtual machine: Cuts3vm: a fast semi-supervised svm algorithm (BZ, FW, CZ), pp. 830–838.
CIKM-2007-SongZYZD #distance #estimation #learning #metric #ranking: Ranking with semi-supervised distance metric learning and its application to housing potential estimation (YS, BZ, WJY, CZ, JD), pp. 975–978.
SIGIR-2007-WangZL #clustering #documentation: Regularized clustering for documents (FW, CZ, TL), pp. 95–102.
ICML-2006-WangZ #linear: Label propagation through linear neighborhoods (FW, CZ), pp. 985–992.
MLDM-2005-XiaWZL #data mining #mining #modelling #random: Mixture Random Effect Model Based Meta-analysis for Medical Data Mining (YX, SW, CZ, SL), pp. 630–640.
MLDM-2005-XiangZCL #approach #recognition #sequence: A New Approach to Human Motion Sequence Recognition with Application to Diving Actions (SX, CZ, XC, NL), pp. 487–496.
MLDM-2005-ZhangZ #component #finite #modelling: Finite Mixture Models with Negative Components (BZ, CZ), pp. 31–41.
ICML-2004-LeeWZB #perspective #probability: Probabilistic tangent subspace: a unified view (JL, JW, CZ, ZB).
ICPR-v1-2004-HeLZZ #classification #image #web: W-Boost and Its Application to Web Image Classification (JH, ML, HZ, CZ), pp. 148–151.
ICPR-v1-2004-YiKZ #classification #learning: Classifier Combination based on Active Learning (XY, ZK, CZ), pp. 184–187.
ICPR-v3-2004-WuZZ #feature model #linear #using: Relevant Linear Feature Extraction Using Side-information and Unlabeled Data (FW, YZ, CZ), pp. 582–585.
ICPR-1998-PengZB #automation #recognition: A fully automated face recognition system under different conditions (HP, CZ, ZB), pp. 1223–1225.