Travelled to:1 × Canada
1 × France
1 × United Kingdom
2 × USA
Collaborated with:F.Denis C.N.Magnan M.Amini E.Morvant S.Koço R.Bailly M.Kowalski M.Szafranski P.Machart T.Peel S.Anthoine H.Glotin
Talks about:learn (3) classif (2) kernel (2) class (2) indefinit (1) stochast (1) concentr (1) classifi (1) bayesian (1) variabl (1)
Person: Liva Ralaivola
DBLP: Ralaivola:Liva
Contributed to:
20152012201120092006Wrote 7 papers:
- ICML-2015-RalaivolaA
- Entropy-Based Concentration Inequalities for Dependent Variables (LR, MRA), pp. 2436–2444.
- ICML-2012-MorvantKR #bound #classification #matrix #multi
- PAC-Bayesian Generalization Bound on Confusion Matrix for Multi-Class Classification (EM, SK, LR), p. 158.
- ICML-2011-MachartPARG #kernel #learning #probability #rank
- Stochastic Low-Rank Kernel Learning for Regression (PM, TP, SA, LR, HG), pp. 969–976.
- ICML-2009-BaillyDR #analysis #component #grammar inference #problem
- Grammatical inference as a principal component analysis problem (RB, FD, LR), pp. 33–40.
- ICML-2009-KowalskiSR #kernel #learning #multi
- Multiple indefinite kernel learning with mixed norm regularization (MK, MS, LR), pp. 545–552.
- ICML-2006-DenisMR #classification #learning #naive bayes #performance
- Efficient learning of Naive Bayes classifiers under class-conditional classification noise (FD, CNM, LR), pp. 265–272.
- ICML-2006-RalaivolaDM
- CN = CPCN (LR, FD, CNM), pp. 721–728.