Travelled to:1 × Canada
1 × Finland
1 × Israel
1 × United Kingdom
3 × USA
Collaborated with:H.Nickisch Y.J.Ko ∅ C.K.I.Williams J.Langford N.Megiddo M.E.Khan A.Y.Aravkin M.P.Friedlander N.Srinivas A.Krause S.Kakade
Talks about:variat (4) infer (4) gaussian (3) bayesian (3) scale (3) model (3) experiment (2) classifi (2) design (2) larg (2)
Person: Matthias W. Seeger
DBLP: Seeger:Matthias_W=
Contributed to:
2013201220102009200820012000Wrote 8 papers:
- ICML-c3-2013-KhanAFS #modelling #performance
- Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models (MEK, AYA, MPF, MWS), pp. 951–959.
- ICML-2012-KoS #modelling #scalability
- Large Scale Variational Bayesian Inference for Structured Scale Mixture Models (YJK, MWS), p. 229.
- ICML-2010-Seeger #scalability
- Gaussian Covariance and Scalable Variational Inference (MWS), pp. 967–974.
- ICML-2010-SrinivasKKS #design #optimisation #process
- Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design (NS, AK, SK, MWS), pp. 1015–1022.
- ICML-2009-NickischS #linear #modelling #scalability
- Convex variational Bayesian inference for large scale generalized linear models (HN, MWS), pp. 761–768.
- ICML-2008-SeegerN #design
- Compressed sensing and Bayesian experimental design (MWS, HN), pp. 912–919.
- ICML-2001-LangfordSM #bound #classification #predict
- An Improved Predictive Accuracy Bound for Averaging Classifiers (JL, MWS, NM), pp. 290–297.
- ICML-2000-WilliamsS #classification #kernel
- The Effect of the Input Density Distribution on Kernel-based Classifiers (CKIW, MWS), pp. 1159–1166.