BibSLEIGH — Qiang

Travelled to:

1 × Brazil
1 × China
1 × Finland
1 × Israel
1 × Singapore
1 × Spain
18 × USA
2 × Australia
2 × Germany
2 × United Kingdom
3 × Canada

Collaborated with:

Z.Chen Y.Yu N.N.Liu G.Xue D.Shen W.Dai J.Sun E.Zhong B.Cao M.Zhao H.Zeng Y.Song E.W.Xiang H.Wang H.Zha S.G.Woods B.Tan F.Wang Y.Zhu W.Chen O.Jin B.Zhang W.Ma K.Zhang M.Yuan J.Zeng H.Cao E.Chen K.Mo B.Li X.Xue H.H.Zhang I.T.Y.Li A.Quilici S.Woods S.J.Pan V.W.Zheng M.Jiang P.Cui W.Zhu S.Yang D.H.Hu Y.Lu T.Chen H.Li Z.Lu C.W.Leung W.Fan Y.Zhang D.Wang X.Meng C.Liu H.Qin D.Xing C.X.Ling J.Wang S.Zhang H.Li W.Xi J.Yan S.Yan K.Deng Y.Li B.Ni J.Fu R.Poss C.R.Jesshope C.Zhang C.Liu H.Xiong G.Jiang Y.Wei Y.Zhen B.Liu B.Wu A.Horner K.Zhao T.Bao J.Tian X.Ling X.Wang M.Zhou Q.Wang J.T.Kwok I.Marsic R.Hu P.Bai Y.Lu R.Liu J.Wu Y.Li D.Jiang J.Hu L.Fang Y.Cao R.Pan J.Zhao J.J.Pan C.Lin X.Hu J.Yao Y.Deng L.Chen H.Guan N.Liu F.Bai Y.Huang F.Zhu X.He W.Fan Q.Cheng L.Wang J.Zhan C.Luo Y.Zhu Y.He W.Gao Z.Jia Y.Shi S.Zhang C.Zheng G.Lu K.Zhan X.Li B.Qiu

Talks about:

classif (10) data (9) transfer (8) model (8) learn (8) text (8) collabor (7) filter (6) domain (6) web (6)

Person: Qiang Yang

DBLP: Yang:Qiang

Facilitated 3 volumes:

Contributed to:

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2001

1996

Wrote 56 papers:

KDD-2015-TanSZ0 #learning #transitive: Transitive Transfer Learning (BT, YS, EZ, QY), pp. 1155–1164.
SIGMOD-2015-HuangZYDLND0Z #big data #predict: Telco Churn Prediction with Big Data (YH, FZ, MY, KD, YL, BN, WD, QY, JZ), pp. 607–618.
VLDB-2015-HuYYDCYGZ #big data #difference #framework #platform #privacy: Differential Privacy in Telco Big Data Platform (XH, MY, JY, YD, LC, QY, HG, JZ), pp. 1692–1703.
DATE-2014-Fu0PJZ #data flow #detection #fault #parallel #thread: A fault detection mechanism in a Data-flow scheduled Multithreaded processor (JF, QY, RP, CRJ, CZ), pp. 1–4.
HPCA-2014-WangZLZYHGJSZZLZLQ #benchmark #big data #internet #metric #named: BigDataBench: A big data benchmark suite from internet services (LW, JZ, CL, YZ, QY, YH, WG, ZJ, YS, SZ, CZ, GL, KZ, XL, BQ), pp. 488–499.
KDD-2014-LiuZXJ0 #categorisation #visualisation: Temporal skeletonization on sequential data: patterns, categorization, and visualization (CL, KZ, HX, GJ, QY), pp. 1336–1345.
KDD-2014-WeiSZL0 #scalability: Scalable heterogeneous translated hashing (YW, YS, YZ, BL, QY), pp. 791–800.
KDD-2014-WuZTH0 #crowdsourcing #modelling #personalisation #topic #using #video: Crowdsourced time-sync video tagging using temporal and personalized topic modeling (BW, EZ, BT, AH, QY), pp. 721–730.
VLDB-2014-YuanDZLNHWDY #distributed #mobile #named #scalability: OceanST: A Distributed Analytic System for Large-Scale Spatiotemporal Mobile Broadband Data (MY, KD, JZ, YL, BN, XH, FW, WD, QY), pp. 1561–1564.
CIKM-2013-ZhuZPWZY #network #predict #process #social: Predicting user activity level in social networks (YZ, EZ, SJP, XW, MZ, QY), pp. 159–168.
ICML-c1-2013-ChenLYY #functional #matrix #using: General Functional Matrix Factorization Using Gradient Boosting (TC, HL, QY, YY), pp. 436–444.
ICML-c3-2013-ZhangZWKYM #kernel: Covariate Shift in Hilbert Space: A Solution via Sorrogate Kernels (KZ, VWZ, QW, JTYK, QY, IM), pp. 388–395.
KDD-2013-MoZY #crowdsourcing: Cross-task crowdsourcing (KM, EZ, QY), pp. 677–685.
KDD-2013-SongLLY #classification #collaboration #microblog #process: Collaborative boosting for activity classification in microblogs (YS, ZL, CWkL, QY), pp. 482–490.
KDD-2013-ZhongFZY #modelling #network #social: Modeling the dynamics of composite social networks (EZ, WF, YZ, QY), pp. 937–945.
CIKM-2012-JiangCLYWZY #recommendation #social: Social contextual recommendation (MJ, PC, RL, QY, FW, WZ, SY), pp. 45–54.
CIKM-2012-JiangCWYZY #multi #recommendation #relational #social: Social recommendation across multiple relational domains (MJ, PC, FW, QY, WZ, SY), pp. 1422–1431.
CIKM-2011-JinLZYY #clustering #topic: Transferring topical knowledge from auxiliary long texts for short text clustering (OJ, NNL, KZ, YY, QY), pp. 775–784.
KDD-2011-ZhangCWY #behaviour #comprehension #modelling #predict: User-click modeling for understanding and predicting search-behavior (YZ, WC, DW, QY), pp. 1388–1396.
RecSys-2011-LiuMLY #elicitation #rating #recommendation: Wisdom of the better few: cold start recommendation via representative based rating elicitation (NNL, XM, CL, QY), pp. 37–44.
CIKM-2010-CaoBYCT #approach #effectiveness #mining #mobile: An effective approach for mining mobile user habits (HC, TB, QY, EC, JT), pp. 1677–1680.
CIKM-2010-LiuXZY #collaboration #feedback: Unifying explicit and implicit feedback for collaborative filtering (NNL, EWX, MZ, QY), pp. 1445–1448.
ICML-2010-CaoLY #learning #multi #predict: Transfer Learning for Collective Link Prediction in Multiple Heterogenous Domains (BC, NNL, QY), pp. 159–166.
RecSys-2010-LiuZXY #collaboration #online: Online evolutionary collaborative filtering (NNL, MZ, EWX, QY), pp. 95–102.
CIKM-2009-CaoSXHYC #classification #named #personalisation #query: PQC: personalized query classification (BC, JTS, EWX, DHH, QY, ZC), pp. 1217–1226.
CIKM-2009-LiuZY #analysis #collaboration #probability: Probabilistic latent preference analysis for collaborative filtering (NNL, MZ, QY), pp. 759–766.
CIKM-2009-ShenWCSYCL #classification: Exploiting term relationship to boost text classification (DS, JW, BC, JTS, QY, ZC, YL), pp. 1637–1640.
ICML-2009-DaiJXYY #framework #learning #named: EigenTransfer: a unified framework for transfer learning (WD, OJ, GRX, QY, YY), pp. 193–200.
ICML-2009-LiYX #collaboration #generative #learning: Transfer learning for collaborative filtering via a rating-matrix generative model (BL, QY, XX), pp. 617–624.
SIGIR-2009-CaoHSJSCY #classification #query: Context-aware query classification (HC, DHH, DS, DJ, JTS, EC, QY), pp. 3–10.
ICML-2008-DaiYXY #clustering #self: Self-taught clustering (WD, QY, GRX, YY), pp. 200–207.
ICML-2008-WangYQZ #analysis #component #composition #feature model: Dirichlet component analysis: feature extraction for compositional data (HYW, QY, HQ, HZ), pp. 1128–1135.
ICML-2008-WangYZ #adaptation #kernel #learning #multi: Adaptive p-posterior mixture-model kernels for multiple instance learning (HYW, QY, HZ), pp. 1136–1143.
KDD-2008-LingDXYY #learning: Spectral domain-transfer learning (XL, WD, GRX, QY, YY), pp. 488–496.
SIGIR-2008-HuCBLCY #mining #query #web: Web query translation via web log mining (RH, WC, PB, YL, ZC, QY), pp. 749–750.
SIGIR-2008-HuFCZLYC #clustering #semantics #wiki: Enhancing text clustering by leveraging Wikipedia semantics (JH, LF, YC, HJZ, HL, QY, ZC), pp. 179–186.
SIGIR-2008-LiuY #approach #collaboration #named: EigenRank: a ranking-oriented approach to collaborative filtering (NNL, QY), pp. 83–90.
SIGIR-2008-XueDYY #classification #topic: Topic-bridged PLSA for cross-domain text classification (GRX, WD, QY, YY), pp. 627–634.
SIGIR-2008-XueXYY #classification #scalability: Deep classification in large-scale text hierarchies (GRX, DX, QY, YY), pp. 619–626.
ICML-2007-CaoSSYC #feature model #kernel: Feature selection in a kernel space (BC, DS, JTS, QY, ZC), pp. 121–128.
ICML-2007-DaiYXY #learning: Boosting for transfer learning (WD, QY, GRX, YY), pp. 193–200.
KDD-2007-DaiXYY #classification #clustering #documentation: Co-clustering based classification for out-of-domain documents (WD, GRX, QY, YY), pp. 210–219.
KDD-2007-PanZZPSPY #mining #modelling #network: Domain-constrained semi-supervised mining of tracking models in sensor networks (RP, JZ, VWZ, JJP, DS, SJP, QY), pp. 1023–1027.
CIKM-2006-ShenSYC #classification #modelling #multi: Text classification improved through multigram models (DS, JTS, QY, ZC), pp. 672–681.
SIGIR-2006-ShenSYC #classification #query #web: Building bridges for web query classification (DS, JTS, QY, ZC), pp. 131–138.
SIGIR-2006-ShenYSC #concurrent #detection #thread: Thread detection in dynamic text message streams (DS, QY, JTS, ZC), pp. 35–42.
SIGIR-2005-SunSZYLC #summary #using: Web-page summarization using clickthrough data (JTS, DS, HJZ, QY, YL, ZC), pp. 194–201.
SIGIR-2005-XueLYXZYC #clustering #collaboration #scalability #using: Scalable collaborative filtering using cluster-based smoothing (GRX, CL, QY, WX, HJZ, YY, ZC), pp. 114–121.
SIGIR-2005-XueYZYC #analysis: Exploiting the hierarchical structure for link analysis (GRX, QY, HJZ, YY, ZC), pp. 186–193.
CIKM-2004-LiuZYYYCBM #learning #metric #similarity: Learning similarity measures in non-orthogonal space (NL, BZ, JY, QY, SY, ZC, FB, WYM), pp. 334–341.
ICML-2004-LingYWZ #low cost: Decision trees with minimal costs (CXL, QY, JW, SZ).
KDD-2004-YanZYYLCXFMC #incremental #named: IMMC: incremental maximum margin criterion (JY, BZ, SY, QY, HL, ZC, WX, WF, WYM, QC), pp. 725–730.
SIGIR-2004-ShenCYZZLM #classification #summary: Web-page classification through summarization (DS, ZC, QY, HJZ, BZ, YL, WYM), pp. 242–249.
KDD-2001-YangZL #mining #modelling #predict #web: Mining web logs for prediction models in WWW caching and prefetching (QY, HHZ, ITYL), pp. 473–478.
ICSE-1996-WoodsY #analysis #approach #comprehension #heuristic #problem: The Program Understanding Problem: Analysis and a Heuristic Approach (SGW, QY), pp. 6–15.
KBSE-1996-QuiliciYW #algorithm #comprehension #recognition: Applying Plan Recognition Algorithms to Program Understanding (AQ, QY, SW), p. 15.