Constituent 发表于 2025-3-28 15:53:25
http://reply.papertrans.cn/16/1530/152965/152965_41.pnginsecticide 发表于 2025-3-28 19:31:40
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http://reply.papertrans.cn/16/1530/152965/152965_43.png傲慢物 发表于 2025-3-29 05:30:16
Gründung und Errichtung der Kreditinstituteormulas is learnable with membership, equivalence and subset queries. Moreover, it is shown that under some condition the class of orthogonal .-Horn formulas is learnable with membership and equivalence queries.concert 发表于 2025-3-29 10:34:49
http://reply.papertrans.cn/16/1530/152965/152965_45.pngMIR 发表于 2025-3-29 14:35:27
„Bankbetrieb“ und „Bankbetriebslehre“above, we obtain probabilistic hierarchies highly structured without a “gap” between the probabilistic and deterministic learning classes. In the case of exact probabilistic learning, we are able to show the probabilistic hierarchy to be dense for every mentioned monotonicity condition. ConsideringACME 发表于 2025-3-29 18:50:55
Learning unions of tree patterns using queries,time PAC-learnability and the polynomial time predictability of .. when membership queries are available. We also show a lower bound . of the number of queries necessary to learn .. using both types of queries. Further, we show that neither types of queries can be eliminated to achieve efficient leamembrane 发表于 2025-3-29 23:31:36
http://reply.papertrans.cn/16/1530/152965/152965_48.png种类 发表于 2025-3-30 00:29:20
Machine induction without revolutionary paradigm shifts,nference, it is shown that there are classes learnable . the non-revolutionary constraint (respectively, with severe parsimony), up to (i}+1) mind changes, and no anomalies, which classes cannot be learned with no size constraint, an unbounded, finite number of anomalies in the final program, but wi染色体 发表于 2025-3-30 06:32:32
Probabilistic language learning under monotonicity constraints,above, we obtain probabilistic hierarchies highly structured without a “gap” between the probabilistic and deterministic learning classes. In the case of exact probabilistic learning, we are able to show the probabilistic hierarchy to be dense for every mentioned monotonicity condition. Considering