作者: engender 時間: 2025-3-21 22:25
Karl Fr. Hagenmüller,Gerhard Diepenhe concepts are not cyclical and hence can be expressed using a directed acyclic graph (not known to the learner). We investigate this learning problem in various popular theoretical models: mistake bound model, exact learningmo del and probably approximately correct (PAC) model.作者: cauda-equina 時間: 2025-3-22 03:14 作者: Juvenile 時間: 2025-3-22 05:26
Learning Intermediate Conceptshe concepts are not cyclical and hence can be expressed using a directed acyclic graph (not known to the learner). We investigate this learning problem in various popular theoretical models: mistake bound model, exact learningmo del and probably approximately correct (PAC) model.作者: Pruritus 時間: 2025-3-22 12:23 作者: 積習(xí)難改 時間: 2025-3-22 16:18
0302-9743 2001), which was held in Washington DC, USA, during November 25–28, 2001. The main objective of the conference is to provide an inter-disciplinary forum for the discussion of theoretical foundations of machine learning, as well as their relevance to practical applications. The conference was co-loc作者: Insubordinate 時間: 2025-3-22 20:43 作者: Ornithologist 時間: 2025-3-22 21:15 作者: ARY 時間: 2025-3-23 04:18 作者: 小隔間 時間: 2025-3-23 09:09
Das Auslandsdienstleistungsgesch?ftorks under certain conditions. We give a much simpler analysis of the algorithm and simplify the conditions. From this simplification, we can provide a simpler algorithm, for which no prior knowledge on the quality of weak hypotheses is necessary.作者: 勉勵 時間: 2025-3-23 12:24 作者: Enteropathic 時間: 2025-3-23 17:19
The Discovery Science Project in Japan) develop new methods for knowledge discovery, (2) install network environments for knowledge discovery, and (3) establish Discovery Science as a new area of Computer Science / Artificial Intelligence Study.作者: 是剝皮 時間: 2025-3-23 21:01 作者: dilute 時間: 2025-3-23 22:39 作者: Decrepit 時間: 2025-3-24 02:33
A Simpler Analysis of the Multi-way Branching Decision Tree Boosting Algorithmorks under certain conditions. We give a much simpler analysis of the algorithm and simplify the conditions. From this simplification, we can provide a simpler algorithm, for which no prior knowledge on the quality of weak hypotheses is necessary.作者: 適宜 時間: 2025-3-24 07:04
A Random Sampling Technique for Training Support Vector Machinesg hyperplane classifiers. Through this research, we are aiming (I) to design efficient and theoretically guaranteed support vector machine training algorithms, and (II) to develop systematic and efficient methods for finding “outliers”, i.e., examples having an inherent error.作者: lambaste 時間: 2025-3-24 12:46 作者: 遺留之物 時間: 2025-3-24 17:00
Geld- und Kapitalanlagem?glichkeitenbstraction, and though they are not denoting or compositional, they do support planning. Deictic representations of objects and prototype representations of words enable a program to learn the denotational meanings of words. Finally, we discuss two algorithms designed to find the macroscopic structure of episodes in a domain-independent way.作者: 鐵塔等 時間: 2025-3-24 22:43
Editors’ Introductionessful algorithms within each such model. To complete the picture we also seek impossibility results showing that certain things are not learnable within a particular model, irrespective of the particular learning algorithms or methods being employed.作者: compel 時間: 2025-3-25 01:53
Robot Baby 2001bstraction, and though they are not denoting or compositional, they do support planning. Deictic representations of objects and prototype representations of words enable a program to learn the denotational meanings of words. Finally, we discuss two algorithms designed to find the macroscopic structure of episodes in a domain-independent way.作者: 使增至最大 時間: 2025-3-25 05:54 作者: 含糊 時間: 2025-3-25 11:27 作者: Medicaid 時間: 2025-3-25 13:13 作者: CREST 時間: 2025-3-25 18:33 作者: Generic-Drug 時間: 2025-3-25 23:28 作者: 易碎 時間: 2025-3-26 00:56 作者: Metamorphosis 時間: 2025-3-26 04:52
Algorithmic Learning Theory978-3-540-45583-7Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 挑剔小責(zé) 時間: 2025-3-26 09:59
Karl Fr. Hagenmüller,Gerhard Diepenonding predictive complexity w.r.t. the Bernoulli distribution are related through the Legendre transformation. It is shown that if two loss functions specify the same complexity then they are equivalent in a strong sense.作者: Confound 時間: 2025-3-26 14:24
Der limitationale Faktor: Eigenmittel statistics. The main thrust is an attempt to model learning phenomena in precise ways and study the mathematical properties of these scenarios. In this way one hopes to get a better understanding of the learning scenarios and what is possible or as we call it learnable in each. Of course this goes 作者: 剝皮 時間: 2025-3-26 17:08
Aufsichtsrechtliche Rahmenbedingungenfic Research on Priority Area from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan. This project mainly aimed to (1) develop new methods for knowledge discovery, (2) install network environments for knowledge discovery, and (3) establish Discovery Science as a new 作者: LIMN 時間: 2025-3-26 23:06
Das Konto als Basis der Kunde-Bank-Beziehungies. We then sketch general results on the number of queries needed to learn a class of concepts, focusing on the various notions of combinatorial dimension that have been employed, including the teaching dimension, the exclusion dimension, the extended teaching dimension, the fingerprint dimension,作者: Serenity 時間: 2025-3-27 02:57
Geld- und Kapitalanlagem?glichkeiten. We discuss several kinds of meaning that representations might have, and focus on a functional notion of meaning as appropriate for programs to learn. Specifically, a representation is meaningful if it incorporates an indicator of external conditions and if the indicator relation informs action. W作者: 本能 時間: 2025-3-27 07:58 作者: insurrection 時間: 2025-3-27 13:24
Derivative Finanzdienstleistungenearchers believe in the importance of giving users an overview and insight into the data distributions, while data mining researchers believe that statistical algorithms and machine learning can be relied on to find the interesting patterns. This paper discusses two issues that influence design of d作者: 憤世嫉俗者 時間: 2025-3-27 16:42 作者: 虛弱的神經(jīng) 時間: 2025-3-27 20:22
Das Auslandsdienstleistungsgesch?ftof Mansour and McAllester constructs a multiway branching decision tree using a set of multi-class hypotheses. Mansour and McAllester proved that it works under certain conditions. We give a much simpler analysis of the algorithm and simplify the conditions. From this simplification, we can provide 作者: Soliloquy 時間: 2025-3-28 00:07 作者: avenge 時間: 2025-3-28 05:33
Karl Fr. Hagenmüller,Gerhard Diepen more sophisticated algorithm for classification in discrete attribute spaces. Classification in discrete attribute spaces is reduced to the problem of learning Boolean functions from examples of its input/output behavior. Since any Boolean function can be written in Disjunctive Normal Form (DNF), i作者: Adrenal-Glands 時間: 2025-3-28 09:43
Karl Fr. Hagenmüller,Gerhard Diepenues for training support vector machines (more precisely, primal-form maximal-margin classifiers) that solve two-group classification problems by using hyperplane classifiers. Through this research, we are aiming (I) to design efficient and theoretically guaranteed support vector machine training al作者: 流眼淚 時間: 2025-3-28 10:57
Karl Fr. Hagenmüller,Gerhard Diepenitive learning situations, where “natural” constraints are imposed on the outcomes of classifiers so that a valid sentence, image or any other domain representation is produced. We formalize these learning situations, after a model suggested in [.] and study generalization abilities of learning algo作者: 重力 時間: 2025-3-28 16:42
Karl Fr. Hagenmüller,Gerhard Diepenn some situations, although the target concept may be quite complex when expressed as a function of the attribute values of the instance, it may have a simple relationship with some intermediate (yet to be learned) concepts. In such cases, it may be advantageous to learn both these intermediate conc作者: 參考書目 時間: 2025-3-28 19:34
Karl Fr. Hagenmüller,Gerhard Diepench bag contains all likely configurations for the molecule. While there has been a significant amount of theoretical and empirical research directed towards this problem, most research performed under the multiple-instance model is for concept learning. However, binding affinity between molecules an作者: 共同確定為確 時間: 2025-3-29 01:19 作者: 高腳酒杯 時間: 2025-3-29 05:22
Karl Fr. Hagenmüller,Gerhard Diependel is such that the learner requests sequences of positive andnegativ e data andthe relations between the various formalizations in dependence on the number of switches between positive and negative data is investigated. In particular it is shown that there is a proper hierarchy of the notions of l作者: TEN 時間: 2025-3-29 07:19 作者: brother 時間: 2025-3-29 15:27
https://doi.org/10.1007/978-3-322-83519-2this paper we study classes of languages where the unions of up to a fixed number (. say) of languages from the class are identifiable. We distinguish between two different scenarios: in one scenario,the learner need only to name the language which results from the union; in the other, the learner m作者: 不可救藥 時間: 2025-3-29 16:31 作者: 拍翅 時間: 2025-3-29 20:22
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/152966.jpg作者: Hormones 時間: 2025-3-29 23:57
https://doi.org/10.1007/3-540-45583-3Algorithmic Learning; Computational Learning; Concept Learning; Discovery Science; Inductive Inference; L作者: 壓艙物 時間: 2025-3-30 04:47
978-3-540-42875-6Springer-Verlag Berlin Heidelberg 2001作者: Scintillations 時間: 2025-3-30 10:28
Loss Functions, Complexities, and the Legendre Transformationonding predictive complexity w.r.t. the Bernoulli distribution are related through the Legendre transformation. It is shown that if two loss functions specify the same complexity then they are equivalent in a strong sense.作者: defendant 時間: 2025-3-30 14:02
Editors’ Introduction statistics. The main thrust is an attempt to model learning phenomena in precise ways and study the mathematical properties of these scenarios. In this way one hopes to get a better understanding of the learning scenarios and what is possible or as we call it learnable in each. Of course this goes 作者: 消散 時間: 2025-3-30 16:37 作者: 勉強 時間: 2025-3-30 21:38 作者: Gyrate 時間: 2025-3-31 01:23
Robot Baby 2001. We discuss several kinds of meaning that representations might have, and focus on a functional notion of meaning as appropriate for programs to learn. Specifically, a representation is meaningful if it incorporates an indicator of external conditions and if the indicator relation informs action. W作者: Myocarditis 時間: 2025-3-31 06:08
Discovering Mechanisms: A Computational Philosophy of Science Perspectiveuation and revision. Because mechanisms are often what is discovered in biology, a newc haracterization of mechanism aids in their discovery. A computational system for discovering mechanisms is sketched, consisting of a simulator, a library of mechanism schemas and components, and a discoverer for 作者: engrossed 時間: 2025-3-31 09:22
Inventing Discovery Tools: Combining Information Visualization with Data Miningearchers believe in the importance of giving users an overview and insight into the data distributions, while data mining researchers believe that statistical algorithms and machine learning can be relied on to find the interesting patterns. This paper discusses two issues that influence design of d作者: 偶然 時間: 2025-3-31 15:25 作者: 宴會 時間: 2025-3-31 18:14 作者: Hemiparesis 時間: 2025-4-1 00:59 作者: 無情 時間: 2025-4-1 05:32 作者: 觀點 時間: 2025-4-1 09:20
A Random Sampling Technique for Training Support Vector Machinesues for training support vector machines (more precisely, primal-form maximal-margin classifiers) that solve two-group classification problems by using hyperplane classifiers. Through this research, we are aiming (I) to design efficient and theoretically guaranteed support vector machine training al作者: fabricate 時間: 2025-4-1 13:25
Learning Coherent Conceptsitive learning situations, where “natural” constraints are imposed on the outcomes of classifiers so that a valid sentence, image or any other domain representation is produced. We formalize these learning situations, after a model suggested in [.] and study generalization abilities of learning algo作者: 溺愛 時間: 2025-4-1 16:51
Learning Intermediate Conceptsn some situations, although the target concept may be quite complex when expressed as a function of the attribute values of the instance, it may have a simple relationship with some intermediate (yet to be learned) concepts. In such cases, it may be advantageous to learn both these intermediate conc作者: 雪白 時間: 2025-4-1 21:00
