Travelled to:1 × Australia
1 × Canada
1 × France
1 × Singapore
1 × The Netherlands
1 × United Kingdom
3 × USA
Collaborated with:M.Richardson R.J.Mooney R.W.White S.Basu H.A.Koepke S.Gupta S.Cucerzan G.C.Murray A.P.Heath K.Tran S.Hosseini L.Xiao T.Finley
Talks about:search (3) use (3) supervis (2) predict (2) cluster (2) enhanc (2) learn (2) walk (2) talk (2) semi (2)
Person: Mikhail Bilenko
DBLP: Bilenko:Mikhail
Contributed to:
2015
201220112009
20082007200420042003Wrote 10 papers:
- KDD-2015-TranHXFB #coordination #probability #scalability
- Scaling Up Stochastic Dual Coordinate Ascent (KT, SH, LX, TF, MB), pp. 1185–1194.
- ICML-2012-KoepkeB #performance #predict
- Fast Prediction of New Feature Utility (HAK, MB), p. 130.
- KDD-2011-BilenkoR #personalisation #predict
- Predictive client-side profiles for personalized advertising (MB, MR), pp. 413–421.
- KDD-2009-GuptaBR #learning
- Catching the drift: learning broad matches from clickthrough data (SG, MB, MR), pp. 1165–1174.
- SIGIR-2008-BilenkoWRM #query
- Talking the talk vs. walking the walk: salience of information needs in querying vs. browsing (MB, RWW, MR, GCM), pp. 705–706.
- SIGIR-2008-WhiteRBH #multi #web
- Enhancing web search by promoting multiple search engine use (RWW, MR, MB, APH), pp. 43–50.
- SIGIR-2007-WhiteBC #interactive #using #web
- Studying the use of popular destinations to enhance web search interaction (RWW, MB, SC), pp. 159–166.
- ICML-2004-BilenkoBM #clustering #constraints #learning #metric
- Integrating constraints and metric learning in semi-supervised clustering (MB, SB, RJM).
- KDD-2004-BasuBM #clustering #framework #probability
- A probabilistic framework for semi-supervised clustering (SB, MB, RJM), pp. 59–68.
- KDD-2003-BilenkoM #adaptation #detection #metric #similarity #string #using
- Adaptive duplicate detection using learnable string similarity measures (MB, RJM), pp. 39–48.