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Titlebook: Machine Learning and Knowledge Discovery in Databases, Part III; European Conference, Dimitrios Gunopulos,Thomas Hofmann,Michalis Vazirg Co

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樓主: 頌歌
11#
發(fā)表于 2025-3-23 09:50:48 | 只看該作者
Learning First-Order Definite Theories via Object-Based Queriest-order concepts to computers. Prior work has shown that first order Horn theories can be learned using a polynomial number of membership and equivalence queries [6]. However, these query types are sometimes unnatural for humans to answer and only capture a small fraction of the information that a h
12#
發(fā)表于 2025-3-23 17:22:15 | 只看該作者
Fast Support Vector Machines for Structural Kernelsal kernels: (i) we exploit a compact yet exact representation of cutting plane models using directed acyclic graphs to speed up both training and classification, (ii) we provide a parallel implementation, which makes the training scale almost linearly with the number of CPUs, and (iii) we propose an
13#
發(fā)表于 2025-3-23 19:42:27 | 只看該作者
14#
發(fā)表于 2025-3-24 00:56:14 | 只看該作者
Compact Coding for Hyperplane Classifiers in Heterogeneous Environmentuce the high cost of inquiring the labeled information for the target task. However, how to avoid . which happens due to different distributions of tasks in heterogeneous environment is still a open problem. In order to handle this kind of issue, we propose a Compact Coding method for Hyperplane Cla
15#
發(fā)表于 2025-3-24 06:11:24 | 只看該作者
Multi-label Ensemble Learningting the label correlations to improve the accuracy of the learner by building an individual multi-label learner or a combined learner based upon a group of single-label learners. However, the generalization ability of such individual learner can be weak. It is well known that ensemble learning can
16#
發(fā)表于 2025-3-24 06:51:08 | 只看該作者
Rule-Based Active Sampling for Learning to Rankng these labeled training sets is usually very costly as it requires human annotators to assess the relevance or order the elements in the training set. Recently, active learning alternatives have been proposed to reduce the labeling effort by selectively sampling an unlabeled set. In this paper we
17#
發(fā)表于 2025-3-24 12:53:39 | 只看該作者
18#
發(fā)表于 2025-3-24 15:45:28 | 只看該作者
19#
發(fā)表于 2025-3-24 19:28:50 | 只看該作者
20#
發(fā)表于 2025-3-25 02:38:40 | 只看該作者
Matthew Robards,Peter Sunehag,Scott Sanner,Bhaskara Marthi wesentlichen Anteil daran haben Schulleistungsstudien wie z.?B. PISA, in denen Finnland regelm??ig überdurchschnittlich gut abschneidet. Dabei scheint es Finnland zu gelingen, mit moderaten Ausgaben für das Bildungssystem einen überdurchschnittlichen Erfolg in Bezug auf die Bildungsqualit?t und Cha
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