#pacbayes 搜尋結果
Triggered by some recent papers, Nick and I wrote about Deep Ensembles, Bayes ensembles, and PAC-Bayesian ensembling: arxiv.org/pdf/2406.05469 Let us know what you think. #deeplearning #PACBayes #BayesianML #ML
And if you missed the poster session, do not worry, the paper will be presented on Friday, as a contributed talk at #PACBayes meets interactive learning workshop, see you there!
Announcing the speakers of the "#PACBayes meets interactive learning" workshop at #ICML2023! Thanks to the co-organizers @flynn_hamish, @audurand, @bguedj, and @TheBayesist for the great teamwork. @icmlconf
RT Theory of learning — a Bayesian perspective of generalization dlvr.it/S51r6k #machinelearningtheory #pacbayes #bayesianmachinelearning
Forthcoming on Dec 8th! Remote PhD defense of Leo Gautheron under supervision of M. Sebban @EmilieMorvant & A. Habrard. Excellent work on #MachineLearning #PACBayes! Many thanks Leo for all your work for the lab far beyond the thesis! @Univ_St_Etienne @INSIS_CNRS @InstitutOptique
Check out our paper with @KloneRobbi on PAC-Bayesian high dimensional bipartite ranking, published in Journal of Statistical Planning and Inference #machinelearning #pacbayes #ranking authors.elsevier.com/a/1WjsL1M25yBe…
We had a fantastic PAC-Bayes workshop last Saturday at @NipsConference The slides and some pictures are now online! Videos are on their way. bguedj.github.io/nips2017/50sha… #machinelearning #NIPS2017 #pacbayes #feelthepaclearn @MLpager @BachFrancis @Inria_Lille @element_ai
Our new paper with @PierreAlquier is now available online! #machinelearning #pacbayes
The website and schedule of our @NipsConference workshop on PAC-Bayes and Bayesian learning are now finalized! Looking forward to a fantastic series of talks @MLpager @BachFrancis @Inria @Inria_Lille #machinelearning #pacbayes #nips2017 bguedj.github.io/nips2017/50sha…
Our paper with S. Robbiano on PAC-Bayesian bounds for high-dimensional bipartite ranking is published in JSPI! #machinelearning #ranking #PACBayes doi.org/10.1016/j.jspi…
And now A. Goyal are talking about #multiviewLearning and #PACBayes theory #MachineLearning #Cap16 #LabCurien
Our work on #pacbayes #transferlearning has been accepted at @tlworkshop2015 :) #machinelearning our research report arxiv.org/abs/1506.04573
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