cerebral
发表于 2025-3-21 19:24:02
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不能妥协
发表于 2025-3-21 22:22:20
Radial Basis Function Neural Networks Have Superlinear VC Dimension,rons. As the main result we show that every reasonably sized standard network of radial basis function (RBF) neurons has VC dimension Ω( log .), where . is the number of parameters and . the number of nodes. This significantly improves the previously known linear bound. We also derive superlin
transient-pain
发表于 2025-3-22 01:04:14
Tracking a Small Set of Experts by Mixing Past Posteriors,ves predictions from a large set of . experts. Its goal is to predict almost as well as the best sequence of such experts chosen off-line by partitioning the training sequence into .+1 sections and then choosing the best expert for each section. We build on methods developed by Herbster and Warmuth
MODE
发表于 2025-3-22 05:44:45
Potential-Based Algorithms in Online Prediction and Game Theory,e and Warmuth’s Weighted Majority), for playing iterated games (including Freund and Schapire’s Hedge and MW, as well as the Λ-strategies of Hart and Mas-Colell), and for boosting (including AdaBoost) are special cases of a general decision strategy based on the notion of potential. By analyzing thi
Bricklayer
发表于 2025-3-22 11:45:29
A Sequential Approximation Bound for Some Sample-Dependent Convex Optimization Problems with Applicons. This analysis is closely related to the regret bound framework in online learning. However we apply it to batch learning algorithms instead of online stochastic gradient decent methods. Applications of this analysis in some classification and regression problems will be illustrated.
前奏曲
发表于 2025-3-22 16:11:13
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前奏曲
发表于 2025-3-22 19:14:55
Ultraconservative Online Algorithms for Multiclass Problems,pe vector per class. Given an input instance, a multiclass hypothesis computes a similarity-score between each prototype and the input instance and then sets the predicted label to be the index of the prototype achieving the highest similarity. To design and analyze the learning algorithms in this p
visual-cortex
发表于 2025-3-22 21:23:31
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indemnify
发表于 2025-3-23 03:05:27
Adaptive Strategies and Regret Minimization in Arbitrarily Varying Markov Environments,is problem is captured by a two-person stochastic game model involving the reward maximizing agent and a second player, which is free to use an arbitrary (non-stationary and unpredictable) control strategy. While the minimax value of the associated zero-sum game provides a guaranteed performance lev
我就不公正
发表于 2025-3-23 08:53:17
,Robust Learning — Rich and Poor,d classes T(.) where T is any general recursive operator, are learnable in the sense .. It was already shown before, see , that for . (learning in the limit) robust learning is rich in that there are classes being both not contained in any recursively enumerable class of recursive functions a