Missing Information Impediments to Learnability

Loizos Michael
Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:825-828, 2011.

Abstract

To what extent is learnability impeded when information is missing in learning instances? We present relevant known results and concrete open problems, in the context of a natural extension of the PAC learning model that accounts for arbitrarily missing information.

Cite this Paper

BibTeX
@InProceedings{pmlr-v19-michael11a, title = {Missing Information Impediments to Learnability}, author = {Michael, Loizos}, booktitle = {Proceedings of the 24th Annual Conference on Learning Theory}, pages = {825--828}, year = {2011}, editor = {Kakade, Sham M. and von Luxburg, Ulrike}, volume = {19}, series = {Proceedings of Machine Learning Research}, address = {Budapest, Hungary}, month = {09--11 Jun}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v19/michael11a/michael11a.pdf}, url = {https://proceedings.mlr.press/v19/michael11a.html}, abstract = {To what extent is learnability impeded when information is missing in learning instances? We present relevant known results and concrete open problems, in the context of a natural extension of the PAC learning model that accounts for arbitrarily missing information.} }
Endnote
%0 Conference Paper %T Missing Information Impediments to Learnability %A Loizos Michael %B Proceedings of the 24th Annual Conference on Learning Theory %C Proceedings of Machine Learning Research %D 2011 %E Sham M. Kakade %E Ulrike von Luxburg %F pmlr-v19-michael11a %I PMLR %P 825--828 %U https://proceedings.mlr.press/v19/michael11a.html %V 19 %X To what extent is learnability impeded when information is missing in learning instances? We present relevant known results and concrete open problems, in the context of a natural extension of the PAC learning model that accounts for arbitrarily missing information.
RIS
TY - CPAPER TI - Missing Information Impediments to Learnability AU - Loizos Michael BT - Proceedings of the 24th Annual Conference on Learning Theory DA - 2011/12/21 ED - Sham M. Kakade ED - Ulrike von Luxburg ID - pmlr-v19-michael11a PB - PMLR DP - Proceedings of Machine Learning Research VL - 19 SP - 825 EP - 828 L1 - http://proceedings.mlr.press/v19/michael11a/michael11a.pdf UR - https://proceedings.mlr.press/v19/michael11a.html AB - To what extent is learnability impeded when information is missing in learning instances? We present relevant known results and concrete open problems, in the context of a natural extension of the PAC learning model that accounts for arbitrarily missing information. ER -
APA
Michael, L.. (2011). Missing Information Impediments to Learnability. Proceedings of the 24th Annual Conference on Learning Theory, in Proceedings of Machine Learning Research 19:825-828 Available from https://proceedings.mlr.press/v19/michael11a.html.

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