Travelled to:1 × Australia
1 × France
1 × USA
1 × United Kingdom
Collaborated with:C.Szepesvári E.P.Xing D.Schuurmans X.Zheng X.Chang Y.Yang H.Cheng J.Neufeld X.Zhang R.Kiros Q.Ho W.Dai J.K.Kim J.Wei S.Lee P.Xie A.Kumar
Talks about:use (2) new (2) represent (1) nonlinear (1) distribut (1) dimension (1) character (1) supervis (1) platform (1) composit (1)
Person: Yaoliang Yu
DBLP: Yu:Yaoliang
Contributed to:
2015
201520132012Wrote 6 papers:
- ICML-2015-ChangYXY #detection #semantics #using
- Complex Event Detection using Semantic Saliency and Nearly-Isotonic SVM (XC, YY, EPX, YY), pp. 1348–1357.
- KDD-2015-XingHDKWLZXKY #big data #distributed #framework #machine learning #named #platform
- Petuum: A New Platform for Distributed Machine Learning on Big Data (EPX, QH, WD, JKK, JW, SL, XZ, PX, AK, YY), pp. 1335–1344.
- KDD-2015-ZhengYX #composition #linear #modelling #topic #using
- Linear Time Samplers for Supervised Topic Models using Compositional Proposals (XZ, YY, EPX), pp. 1523–1532.
- ICML-c1-2013-YuCSS #theorem
- Characterizing the Representer Theorem (YY, HC, DS, CS), pp. 570–578.
- ICML-2012-NeufeldYZKS #reduction
- Regularizers versus Losses for Nonlinear Dimensionality Reduction: A Factored View with New Convex Relaxations (JN, YY, XZ, RK, DS), p. 191.
- ICML-2012-YuS #analysis #kernel
- Analysis of Kernel Mean Matching under Covariate Shift (YY, CS), p. 150.