BibSLEIGH — Tie-Yan

Travelled to:

1 × Brazil
1 × Canada
1 × Chile
1 × Finland
1 × Ireland
1 × Italy
1 × Portugal
1 × Singapore
1 × Switzerland
1 × The Netherlands
1 × United Kingdom
3 × China
8 × USA

Collaborated with:

H.Li T.Qin B.Gao W.Ma Z.Ma T.Wang X.Zhang ∅ Y.Lan X.Geng X.Zheng M.Tsai J.Xu J.Bian Y.Bao K.Salomatin Y.Yang Y.Zhang J.Yan D.Shen S.Kim H.Yu Q.Zhao S.S.Bhowmick S.Liu Y.Zhang W.Wei F.Xia J.Wang W.Zhang M.Lu L.Yang L.Qi Y.Zhao H.Yang L.Zhang Z.Cao H.Chen Q.Cheng Z.Chen S.Huang S.Wang J.Ma Z.Chen J.Veijalainen W.Zhang Y.Yu X.Yuan A.Arnold H.Shum D.Wang W.Lai Y.Cao Y.Huang H.Hon C.Xu Y.Bai G.Wang X.Liu Y.Liu S.He G.Feng Y.Wang

Talks about:

rank (16) learn (7) search (5) web (5) approach (4) advertis (4) listwis (4) general (4) optim (4) graph (4)

Person: Tie-Yan Liu

DBLP: Liu:Tie=Yan

Contributed to:

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

Wrote 29 papers:

SIGIR-2015-HuangWLMCV #collaboration: Listwise Collaborative Filtering (SH, SW, TYL, JM, ZC, JV), pp. 343–352.
CIKM-2014-XuBBGWLL #framework #named #word: RC-NET: A General Framework for Incorporating Knowledge into Word Representations (CX, YB, JB, BG, GW, XL, TYL), pp. 1219–1228.
KDD-2013-WangBLZL #predict: Psychological advertising: exploring user psychology for click prediction in sponsored search (TW, JB, SL, YZ, TYL), pp. 563–571.
SIGIR-2013-GaoYSL #internet #theory and practice: Internet advertising: theory and practice (BG, JY, DS, TYL), p. 1135.
CIKM-2012-SalomatinLY #framework #online #optimisation: A unified optimization framework for auction and guaranteed delivery in online advertising (KS, TYL, YY), pp. 2005–2009.
KDD-2012-ZhangZGYYL #optimisation: Joint optimization of bid and budget allocation in sponsored search (WZ, YZ, BG, YY, XY, TYL), pp. 1177–1185.
SIGIR-2012-GaoWL #graph #information retrieval #learning #mining #scalability: Large-scale graph mining and learning for information retrieval (BG, TW, TYL), pp. 1194–1195.
CIKM-2011-KimQYL #approach #behaviour: Advertiser-centric approach to understand user click behavior in sponsored search (SK, TQ, HY, TYL), pp. 2121–2124.
KDD-2011-GaoLWWL #graph #metadata #ranking #scalability: Semi-supervised ranking on very large graphs with rich metadata (BG, TYL, WW, TW, HL), pp. 96–104.
SIGIR-2010-Liu #information retrieval #learning #rank: Learning to rank for information retrieval (TYL), p. 904.
CIKM-2009-GaoLMWL #framework #markov: A general markov framework for page importance computation (BG, TYL, ZM, TW, HL), pp. 1835–1838.
ICML-2009-LanLML #algorithm #analysis #ranking: Generalization analysis of listwise learning-to-rank algorithms (YL, TYL, ZM, HL), pp. 577–584.
ICML-2008-LanLQML #learning #rank: Query-level stability and generalization in learning to rank (YL, TYL, TQ, ZM, HL), pp. 512–519.
ICML-2008-XiaLWZL #algorithm #approach #learning #rank: Listwise approach to learning to rank: theory and algorithm (FX, TYL, JW, WZ, HL), pp. 1192–1199.
SIGIR-2008-GengLQALS #nearest neighbour #query #ranking #using: Query dependent ranking using K-nearest neighbor (XG, TYL, TQ, AA, HL, HYS), pp. 115–122.
SIGIR-2008-LiuGLZMHL #named #rank #web: BrowseRank: letting web users vote for page importance (YL, BG, TYL, YZ, ZM, SH, HL), pp. 451–458.
SIGIR-2008-XuLLLM #evaluation #learning #metric #optimisation #rank: Directly optimizing evaluation measures in learning to rank (JX, TYL, ML, HL, WYM), pp. 107–114.
CIKM-2007-YangQZGL #analysis #graph #using #web: Link analysis using time series of web graphs (LY, LQ, YPZ, BG, TYL), pp. 1011–1014.
ECIR-2007-LiuYZQM #clustering #optimisation #performance #scalability: Fast Large-Scale Spectral Clustering by Sequential Shrinkage Optimization (TYL, HYY, XZ, TQ, WYM), pp. 319–330.
ECIR-2007-ZhangQLBL #rank #web: N -Step PageRank for Web Search (LZ, TQ, TYL, YB, HL), pp. 653–660.
ICML-2007-CaoQLTL #approach #learning #rank: Learning to rank: from pairwise approach to listwise approach (ZC, TQ, TYL, MFT, HL), pp. 129–136.
SIGIR-2007-GengLQL #feature model #ranking: Feature selection for ranking (XG, TYL, TQ, HL), pp. 407–414.
SIGIR-2007-QinZWLLL #multi #ranking: Ranking with multiple hyperplanes (TQ, XDZ, DSW, TYL, WL, HL), pp. 279–286.
SIGIR-2007-TsaiLQCM #named #ranking: FRank: a ranking method with fidelity loss (MFT, TYL, TQ, HHC, WYM), pp. 383–390.
KDD-2006-ZhaoLBM #detection #evolution: Event detection from evolution of click-through data (QZ, TYL, SSB, WYM), pp. 484–493.
SIGIR-2006-CaoXLLHH #adaptation #documentation #ranking #retrieval: Adapting ranking SVM to document retrieval (YC, JX, TYL, HL, YH, HWH), pp. 186–193.
SIGIR-2006-FengLWBMZM #named #order #web: AggregateRank: bringing order to web sites (GF, TYL, YW, YB, ZM, XDZ, WYM), pp. 75–82.
KDD-2005-GaoLZCM #clustering #consistency #graph #higher-order #semistructured data: Consistent bipartite graph co-partitioning for star-structured high-order heterogeneous data co-clustering (BG, TYL, XZ, QC, WYM), pp. 41–50.
SIGIR-2005-QinLZCM #case study #web: A study of relevance propagation for web search (TQ, TYL, XDZ, ZC, WYM), pp. 408–415.