Travelled to:1 × Australia
1 × Finland
1 × United Kingdom
2 × Canada
3 × USA
Collaborated with:M.Welling A.Mnih B.Lakshminarayanan D.M.Roy M.Rosen-Zvi S.Kakade S.T.Roweis C.Chen V.Rao W.L.Buntine J.V.Gael Y.Saatçi Z.Ghahramani E.P.Xing K.Sohn M.I.Jordan F.Wood C.Archambeau J.Gasthaus L.James
Talks about:bayesian (3) stochast (2) markov (2) model (2) infer (2) probabilist (1) markovian (1) dirichlet (1) algorithm (1) langevin (1)
Person: Yee Whye Teh
DBLP: Teh:Yee_Whye
Contributed to:
20132012201120092008200620042002Wrote 9 papers:
- ICML-c3-2013-ChenRBT #metric #normalisation #random
- Dependent Normalized Random Measures (CC, VR, WLB, YWT), pp. 969–977.
- ICML-c3-2013-LakshminarayananRT #top-down
- Top-down particle filtering for Bayesian decision trees (BL, DMR, YWT), pp. 280–288.
- ICML-2012-MnihT #algorithm #modelling #performance #probability
- A fast and simple algorithm for training neural probabilistic language models (AM, YWT), p. 58.
- ICML-2011-WellingT #learning #probability
- Bayesian Learning via Stochastic Gradient Langevin Dynamics (MW, YWT), pp. 681–688.
- ICML-2009-WoodAGJT #probability #sequence
- A stochastic memoizer for sequence data (FW, CA, JG, LJ, YWT), pp. 1129–1136.
- ICML-2008-GaelSTG #infinity #markov
- Beam sampling for the infinite hidden Markov model (JVG, YS, YWT, ZG), pp. 1088–1095.
- ICML-2006-XingSJT #multi #process #type inference
- Bayesian multi-population haplotype inference via a hierarchical dirichlet process mixture (EPX, KAS, MIJ, YWT), pp. 1049–1056.
- ICML-2004-WellingRT #approximate #markov
- Approximate inference by Markov chains on union spaces (MW, MRZ, YWT).
- ICML-2002-KakadeTR #markov
- An Alternate Objective Function for Markovian Fields (SK, YWT, STR), pp. 275–282.