Self‐certifying classification by linearized deep assignment
We propose a novel class of deep stochastic predictors for classifying metric data on graphs
within the PAC‐Bayes risk certification paradigm. Classifiers are realized as linearly …
within the PAC‐Bayes risk certification paradigm. Classifiers are realized as linearly …
[PDF][PDF] Self-Certifying Classification by Linearized Deep Assignment
B Boll, A Zeilmann, S Petra, C Schnörr - 2023 - ipa.iwr.uni-heidelberg.de
Self-certified learning is the task of using the entirety of available data to find a good model
and to simultaneously certify its performance on unseen data from the same underlying …
and to simultaneously certify its performance on unseen data from the same underlying …
[PDF][PDF] Self-Certifying Classification by Linearized Deep Assignment
B Boll, A Zeilmann, S Petra, C Schnörr - 2023 - ipa.math.uni-heidelberg.de
Self-certified learning is the task of using the entirety of available data to find a good model
and to simultaneously certify its performance on unseen data from the same underlying …
and to simultaneously certify its performance on unseen data from the same underlying …
Self‐certifying classification by linearized deep assignment
B Boll, A Zeilmann, S Petra, C Schnörr - 2023 - opus.bibliothek.uni-augsburg.de
Self-certified learning is the task of using the entirety of available data to find a good model
and to simultaneously certify its performance on unseen data from the same underlying …
and to simultaneously certify its performance on unseen data from the same underlying …
[PDF][PDF] SELF-CERTIFYING CLASSIFICATION BY LINEARIZED DEEP ASSIGNMENT
B BOLL, A ZEILMANN, S PETRA, C SCHNÖRR - ipa.math.uni-heidelberg.de
We propose a novel class of deep stochastic predictors for classifying metric data on graphs
within the PAC-Bayes risk certification paradigm. Classifiers are realized as linearly …
within the PAC-Bayes risk certification paradigm. Classifiers are realized as linearly …
[PDF][PDF] SELF-CERTIFYING CLASSIFICATION BY LINEARIZED DEEP ASSIGNMENT
B BOLL, A ZEILMANN, S PETRA, C SCHNÖRR - ipa.iwr.uni-heidelberg.de
We propose a novel class of deep stochastic predictors for classifying metric data on graphs
within the PAC-Bayes risk certification paradigm. Classifiers are realized as linearly …
within the PAC-Bayes risk certification paradigm. Classifiers are realized as linearly …