Travelled to:1 × Australia
1 × Canada
1 × China
1 × Finland
1 × Switzerland
1 × The Netherlands
1 × United Kingdom
3 × USA
Collaborated with:T.Joachims F.Radlinski S.Liu R.Krishnan S.A.Hong C.Guestrin T.Kim S.L.Taylor I.Matthews T.Finley S.Ross J.Zhou D.Dey D.Bagnell Y.Gao O.Chapelle Y.Zhang
Talks about:retriev (3) predict (3) bandit (3) contextu (2) optim (2) learn (2) evalu (2) use (2) spatiotempor (1) submodular (1)
Person: Yisong Yue
DBLP: Yue:Yisong
Contributed to:
2015
2013201320122011
20112010200920082007Wrote 10 papers:
- KDD-2015-KimYTM #framework #predict #sequence
- A Decision Tree Framework for Spatiotemporal Sequence Prediction (TK, YY, SLT, IM), pp. 577–586.
- ICML-c3-2013-RossZYDB #learning #policy #predict
- Learning Policies for Contextual Submodular Prediction (SR, JZ, YY, DD, DB), pp. 1364–1372.
- KDD-2013-LiuYK #adaptation #modelling #process #using
- Adaptive collective routing using gaussian process dynamic congestion models (SL, YY, RK), pp. 704–712.
- ICML-2012-YueHG
- Hierarchical Exploration for Accelerating Contextual Bandits (YY, SAH, CG), p. 128.
- ICML-2011-YueJ
- Beat the Mean Bandit (YY, TJ), pp. 241–248.
- SIGIR-2011-RadlinskiY #evaluation #online #retrieval
- Practical online retrieval evaluation (FR, YY), pp. 1301–1302.
- SIGIR-2010-YueGCZJ #evaluation #learning #retrieval #statistics
- Learning more powerful test statistics for click-based retrieval evaluation (YY, YG, OC, YZ, TJ), pp. 507–514.
- ICML-2009-YueJ #information retrieval #optimisation #problem
- Interactively optimizing information retrieval systems as a dueling bandits problem (YY, TJ), pp. 1201–1208.
- ICML-2008-YueJ #predict #set #using
- Predicting diverse subsets using structural SVMs (YY, TJ), pp. 1224–1231.
- SIGIR-2007-YueFRJ #optimisation #precise
- A support vector method for optimizing average precision (YY, TF, FR, TJ), pp. 271–278.