Travelled to:1 × Australia
1 × Finland
1 × Germany
1 × USA
2 × China
Collaborated with:M.Cuturi F.Caron S.I.Hill R.Bardenet C.C.Holmes S.Tham K.Ramamohanarao M.Klaas M.Briers N.d.Freitas S.Maskell D.Lang
Talks about:bayesian (2) regress (2) particl (2) classif (2) markov (2) spars (2) class (2) chain (2) carlo (2) adapt (2)
Person: Arnaud Doucet
DBLP: Doucet:Arnaud
Contributed to:
201420142008200620052002Wrote 6 papers:
- ICML-c1-2014-BardenetDH #adaptation #approach #markov #monte carlo #scalability #towards
- Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach (RB, AD, CCH), pp. 405–413.
- ICML-c2-2014-CuturiD #performance
- Fast Computation of Wasserstein Barycenters (MC, AD), pp. 685–693.
- ICML-2008-CaronD #parametricity
- Sparse Bayesian nonparametric regression (FC, AD), pp. 88–95.
- ICML-2006-KlaasBFDML #performance
- Fast particle smoothing: if I had a million particles (MK, MB, NdF, AD, SM, DL), pp. 481–488.
- ICML-2005-HillD #adaptation #classification #problem
- Adapting two-class support vector classification methods to many class problems (SIH, AD), pp. 313–320.
- ICML-2002-ThamDR #classification #learning #markov #monte carlo #using
- Sparse Bayesian Learning for Regression and Classification using Markov Chain Monte Carlo (SST, AD, KR), pp. 634–641.