BRISK
发表于 2025-3-21 17:41:36
书目名称Computational Learning Theory影响因子(影响力)<br> http://impactfactor.cn/2024/if/?ISSN=BK0232577<br><br> <br><br>书目名称Computational Learning Theory影响因子(影响力)学科排名<br> http://impactfactor.cn/2024/ifr/?ISSN=BK0232577<br><br> <br><br>书目名称Computational Learning Theory网络公开度<br> http://impactfactor.cn/2024/at/?ISSN=BK0232577<br><br> <br><br>书目名称Computational Learning Theory网络公开度学科排名<br> http://impactfactor.cn/2024/atr/?ISSN=BK0232577<br><br> <br><br>书目名称Computational Learning Theory被引频次<br> http://impactfactor.cn/2024/tc/?ISSN=BK0232577<br><br> <br><br>书目名称Computational Learning Theory被引频次学科排名<br> http://impactfactor.cn/2024/tcr/?ISSN=BK0232577<br><br> <br><br>书目名称Computational Learning Theory年度引用<br> http://impactfactor.cn/2024/ii/?ISSN=BK0232577<br><br> <br><br>书目名称Computational Learning Theory年度引用学科排名<br> http://impactfactor.cn/2024/iir/?ISSN=BK0232577<br><br> <br><br>书目名称Computational Learning Theory读者反馈<br> http://impactfactor.cn/2024/5y/?ISSN=BK0232577<br><br> <br><br>书目名称Computational Learning Theory读者反馈学科排名<br> http://impactfactor.cn/2024/5yr/?ISSN=BK0232577<br><br> <br><br>
转折点
发表于 2025-3-21 21:29:20
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破译密码
发表于 2025-3-22 03:45:13
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PANEL
发表于 2025-3-22 08:36:15
https://doi.org/10.1007/978-3-322-87794-9hted average of the experts’ predictions. We show that for a large class of loss functions, even with the simplified prediction rule the additional loss of the algorithm over the loss of the best expert is at most . ln ., where . is the number of experts and . a constant that depends on the loss fun
cleaver
发表于 2025-3-22 11:46:19
https://doi.org/10.1007/978-3-658-00686-0operly between hyperrobust Ex-learning and hyperrobust BC-learning. Furthermore, the bounded totally reliably BC-learnable classes are characterized in terms of infinite branches of certain enumerable families of bounded recursive trees. A class of infinite branches of a further family of trees sepa
giggle
发表于 2025-3-22 15:06:41
https://doi.org/10.1007/978-3-658-00686-0lds a uniformly decidable family of languages and has effective bounded finite thickness, then for each natural number . > 0, the class of languages defined by formal systems of length ≤ .:.The above sufficient conditions are employed to give an ordinal mind change bound for learnability of minimal
giggle
发表于 2025-3-22 19:05:35
Open Theoretical Questions in Reinforcement Learning in a given state and ending upon arrival in a terminal state, terminating the series above. In other cases the interaction is continual, without interruption, and the sum may have an infinite number of terms (in which case we usually assume γ < 1). Infinite horizon cases with γ = 1 are also possibl
新鲜
发表于 2025-3-22 21:59:07
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手榴弹
发表于 2025-3-23 04:02:53
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宠爱
发表于 2025-3-23 09:25:01
Averaging Expert Predictionshted average of the experts’ predictions. We show that for a large class of loss functions, even with the simplified prediction rule the additional loss of the algorithm over the loss of the best expert is at most . ln ., where . is the number of experts and . a constant that depends on the loss fun