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A theory of universal learning:
, In:
Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing
,
Bousquet, Olivier
;
Hanneke, Steve
;
Moran, Shay
.. - p. 532-541 , 2021
Link:
https://dl.acm.org/doi/10.1145/3406325.3451087
RT T1
Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing
: T1
A theory of universal learning
UL https://suche.suub.uni-bremen.de/peid=acm-3451087&Exemplar=1&LAN=DE A1 Bousquet, Olivier A1 Hanneke, Steve A1 Moran, Shay A1 van Handel, Ramon A1 Yehudayoff, Amir PB ACM YR 2021 K1 Distribution-Dependent Learning Rates K1 Online Learning K1 Statistical Learning K1 Theory of computation K1 Theory and algorithms for application domains K1 Machine learning theory K1 Sample complexity and generalization bounds SP 532 OP 541 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3406325.3451087 DO https://dl.acm.org/doi/10.1145/3406325.3451087 SF ELIB - SuUB Bremen
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