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Travelled to:
1 × China
1 × Finland
1 × France
1 × Germany
1 × Spain
1 × United Kingdom
2 × Canada
7 × USA
Collaborated with:
J.M.Hernández-Lobato D.A.Knowles K.A.Heller N.Houlsby Y.Gal C.Heaukulani K.Palla W.Chu A.Shah Y.Chen J.V.Gael D.Lopez-Paz C.Reed R.P.Adams F.Doshi-Velez A.Azran E.Snelson A.Scibior D.Hernández-Lobato Y.Wu T.Iwata S.Mohamed B.Póczos J.G.Schneider A.G.Wilson S.Williamson D.L.Wild R.Salakhutdinov S.T.Roweis X.Zhu J.D.Lafferty A.D.Gordon H.Ge M.Wan S.Bratieres N.Quadrianto S.Nowozin Y.Saatçi Y.W.Teh Y.(.Qi T.P.Minka R.W.Picard N.J.Adams A.J.Storkey C.K.I.Williams M.A.Gelbart M.W.Hoffman R.P.Adams S.Sra A.J.Smola B.Schölkopf D.K.Duvenaud J.R.Lloyd R.B.Grosse J.B.Tenenbaum S.Lacoste-Julien A.Davies G.Kasneci T.Graepel O.Kammar M.Vákár S.Staton H.Yang Y.Cai K.Ostermann Sean K. Moss C.Heunen
Talks about:
process (11) model (9) gaussian (6) bayesian (6) probabilist (5) predict (5) learn (5) infer (5) latent (4) data (4)

Person: Zoubin Ghahramani

DBLP DBLP: Ghahramani:Zoubin

Facilitated 1 volumes:

ICML 2007Ed

Contributed to:

ICML 20152015
ICML c2 20142014
ICML c1 20132013
ICML c2 20132013
ICML c3 20132013
KDD 20132013
ICML 20122012
ICML 20112011
ICML 20092009
ICML 20082008
ICML 20062006
ICML 20052005
ICML 20042004
ICML 20032003
ICPR v3 20002000
Haskell 20152015
POPL 20182018

Wrote 40 papers:

ICML-2015-GalCG #category theory #estimation #multi #process
Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data (YG, YC, ZG), pp. 645–654.
ICML-2015-GeCWG #distributed #modelling #process
Distributed Inference for Dirichlet Process Mixture Models (HG, YC, MW, ZG), pp. 2276–2284.
ICML-2015-Hernandez-Lobato #feature model #multi #probability
A Probabilistic Model for Dirty Multi-task Feature Selection (DHL, JMHL, ZG), pp. 1073–1082.
ICML-2015-Hernandez-Lobato15a #constraints #optimisation #predict
Predictive Entropy Search for Bayesian Optimization with Unknown Constraints (JMHL, MAG, MWH, RPA, ZG), pp. 1699–1707.
ICML-2015-ShahKG #algorithm #empirical #probability #process
An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process (AS, DAK, ZG), pp. 1594–1603.
ICML-c2-2014-BratieresQNG #graph #grid #predict #process #scalability
Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications (SB, NQ, SN, ZG), pp. 334–342.
ICML-c2-2014-GalG #parallel #process #using
Pitfalls in the use of Parallel Inference for the Dirichlet Process (YG, ZG), pp. 208–216.
ICML-c2-2014-HeaukulaniKG
Beta Diffusion Trees (CH, DAK, ZG), pp. 1809–1817.
ICML-c2-2014-Hernandez-LobatoHG #matrix #modelling #probability #scalability
Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices (JMHL, NH, ZG), pp. 379–387.
ICML-c2-2014-Hernandez-LobatoHG14a #matrix #probability
Probabilistic Matrix Factorization with Non-random Missing Data (JMHL, NH, ZG), pp. 1512–1520.
ICML-c2-2014-HoulsbyHG #learning #matrix #robust
Cold-start Active Learning with Robust Ordinal Matrix Factorization (NH, JMHL, ZG), pp. 766–774.
ICML-c2-2014-KnowlesGP #infinity #metric #normalisation #random #using
A reversible infinite HMM using normalised random measures (DAK, ZG, KP), pp. 1998–2006.
ICML-c2-2014-Lopez-PazSSGS #analysis #component #random
Randomized Nonlinear Component Analysis (DLP, SS, AJS, ZG, BS), pp. 1359–1367.
ICML-c1-2013-HeaukulaniG #modelling #network #probability #social
Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks (CH, ZG), pp. 275–283.
ICML-c2-2013-Lopez-PazHG #dependence #multi #process
Gaussian Process Vine Copulas for Multivariate Dependence (DLP, JMHL, ZG), pp. 10–18.
ICML-c3-2013-DuvenaudLGTG #composition #kernel #parametricity
Structure Discovery in Nonparametric Regression through Compositional Kernel Search (DKD, JRL, RBG, JBT, ZG), pp. 1166–1174.
ICML-c3-2013-ReedG #process #scalability
Scaling the Indian Buffet Process via Submodular Maximization (CR, ZG), pp. 1013–1021.
ICML-c3-2013-WuHG #modelling #multi
Dynamic Covariance Models for Multivariate Financial Time Series (YW, JMHL, ZG), pp. 558–566.
KDD-2013-IwataSG #online #process #social
Discovering latent influence in online social activities via shared cascade poisson processes (TI, AS, ZG), pp. 266–274.
KDD-2013-Lacoste-JulienPDKGG #knowledge base #named #scalability
SIGMa: simple greedy matching for aligning large knowledge bases (SLJ, KP, AD, GK, TG, ZG), pp. 572–580.
ICML-2012-MohamedHG #learning
Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning (SM, KAH, ZG), p. 91.
ICML-2012-PallaKG #infinity #network
An Infinite Latent Attribute Model for Network Data (KP, DAK, ZG), p. 55.
ICML-2012-PoczosGS #dependence #kernel #metric
Copula-based Kernel Dependency Measures (BP, ZG, JGS), p. 213.
ICML-2012-WilsonKG #network #process
Gaussian Process Regression Networks (AGW, DAK, ZG), p. 149.
ICML-2011-KnowlesGG #algorithm #message passing
Message Passing Algorithms for the Dirichlet Diffusion Tree (DAK, JVG, ZG), pp. 721–728.
ICML-2009-AdamsG #learning #named #parametricity
Archipelago: nonparametric Bayesian semi-supervised learning (RPA, ZG), pp. 1–8.
ICML-2009-Doshi-VelezG #process
Accelerated sampling for the Indian Buffet Process (FDV, ZG), pp. 273–280.
ICML-2008-GaelSTG #infinity #markov
Beam sampling for the infinite hidden Markov model (JVG, YS, YWT, ZG), pp. 1088–1095.
ICML-2008-HellerWG #modelling #statistics
Statistical models for partial membership (KAH, SW, ZG), pp. 392–399.
ICML-2006-AzranG #approach #clustering #data-driven
A new approach to data driven clustering (AA, ZG), pp. 57–64.
ICML-2005-ChuG #learning #process
Preference learning with Gaussian processes (WC, ZG), pp. 137–144.
ICML-2005-HellerG #clustering
Bayesian hierarchical clustering (KAH, ZG), pp. 297–304.
ICML-2005-SnelsonG #approximate #predict
Compact approximations to Bayesian predictive distributions (ES, ZG), pp. 840–847.
ICML-2004-ChuGW #predict #visual notation
A graphical model for protein secondary structure prediction (WC, ZG, DLW).
ICML-2004-QiMPG #automation #predict
Predictive automatic relevance determination by expectation propagation (Y(Q, TPM, RWP, ZG).
ICML-2003-SalakhutdinovRG #optimisation
Optimization with EM and Expectation-Conjugate-Gradient (RS, STR, ZG), pp. 672–679.
ICML-2003-ZhuGL #learning #using
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions (XZ, ZG, JDL), pp. 912–919.
ICPR-v3-2000-AdamsSWG #named
MFDTs: Mean Field Dynamic Trees (NJA, AJS, CKIW, ZG), pp. 3151–3154.
Haskell-2015-ScibiorGG #monad #probability #programming
Practical probabilistic programming with monads (AS, ZG, ADG), pp. 165–176.
POPL-2018-ScibiorKVSYCOMH #higher-order #validation
Denotational validation of higher-order Bayesian inference (AS, OK, MV, SS, HY, YC, KO, SKM, CH, ZG), p. 29.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
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