標(biāo)題: Titlebook: Machine Learning and Knowledge Discovery in Databases; European Conference, Walter Daelemans,Bart Goethals,Katharina Morik Conference proce [打印本頁] 作者: Fibromyalgia 時(shí)間: 2025-3-21 19:06
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書目名稱Machine Learning and Knowledge Discovery in Databases影響因子(影響力)學(xué)科排名
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書目名稱Machine Learning and Knowledge Discovery in Databases網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Machine Learning and Knowledge Discovery in Databases被引頻次
書目名稱Machine Learning and Knowledge Discovery in Databases被引頻次學(xué)科排名
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書目名稱Machine Learning and Knowledge Discovery in Databases讀者反饋
書目名稱Machine Learning and Knowledge Discovery in Databases讀者反饋學(xué)科排名
作者: 橫截,橫斷 時(shí)間: 2025-3-21 23:41
From Microscopy Images to Models of Cellular Processesaginable just a few years ago. However, as the analysis of these images is done mostly by hand, there is a severe bottleneck in transforming these images into useful quantitative data that can be used to evaluate mathematical models..One of the inherent challenges involved in automating this transfo作者: rods366 時(shí)間: 2025-3-22 02:25 作者: 內(nèi)部 時(shí)間: 2025-3-22 08:35
Learning Language from Its Perceptual Contexte to acquire language like a child by being exposed to linguistic input in the context of a relevant but ambiguous perceptual environment. As a step in this direction, we present a system that learns to sportscast simulated robot soccer games by example. The training data consists of textual human c作者: 適宜 時(shí)間: 2025-3-22 10:29
The Role of Hierarchies in Exploratory Data Miningold: first, the size of the space raises computational challenges, and second, it can introduce data sparsity issues even in the presence of very large datasets. In this talk, well consider how the use of hierarchies (e.g., taxonomies, or the OLAP multidimensional model) can help mitigate the proble作者: mastoid-bone 時(shí)間: 2025-3-22 13:15
Rollout Sampling Approximate Policy Iterationuggests an approximate policy iteration algorithm for learning a good policy represented as a classifier, without explicit value function representation. At each iteration, a new policy is produced using training data obtained through rollouts of the previous policy on a simulator. These rollouts ai作者: 無意 時(shí)間: 2025-3-22 19:43 作者: Benign 時(shí)間: 2025-3-22 23:19
Large Margin vs. Large Volume in Transductive Learningted uniformly at random from the full sample and the labels of the training points are revealed. The goal is to predict the labels of the remaining unlabeled points as accurately as possible. The full sample partitions the transductive hypothesis space into a finite number of .. All hypotheses in th作者: harpsichord 時(shí)間: 2025-3-23 03:10
Incremental Exemplar Learning Schemes for Classification on Embedded Deviceson-monitoring data streams). Memory-based classifiers are an excellent choice in such cases, however, an embedded device is unlikely to be able to hold a large training dataset in memory (which could potentially keep increasing in size as new training data with new concepts arrive). A viable option 作者: 出汗 時(shí)間: 2025-3-23 08:25
A Collaborative Filtering Framework Based on Both Local User Similarity and Global User Similarityer, we introduce the concept of local user similarity and global user similarity, based on surprisal-based vector similarity and the application of the concept of maximin distance in graph theory. Surprisal-based vector similarity expresses the relationship between any two users based on the quantit作者: Endemic 時(shí)間: 2025-3-23 09:54
A Critical Analysis of Variants of the AUCinstances, the metric considers the number of correctly ordered pairs of instances with different class label. Thus, its value only depends on the ordering of the scores but not on the “margin” between them. Consequently, it can happen that a small change in scores leads to a considerable change in 作者: 老人病學(xué) 時(shí)間: 2025-3-23 14:31
Improving Maximum Margin Matrix Factorizationour recent paper [2], we proposed to extend the general MMMF framework to allow for structured (ranking) losses in addition to the squared error loss..In this paper, we introduce a novel algorithm to compute the ordinal regression ranking loss which is significantly faster than the state of the art.作者: 調(diào)情 時(shí)間: 2025-3-23 20:04
Finding Reliable Subgraphs from Large Probabilistic Graphsconcepts (“search terms”), and wishes to obtain other concepts and relationships that connect the search concepts. An application example is in analysis of biological information, conveniently represented as a graph of biological concepts and their relations. A search engine we envision would allow 作者: 熱情贊揚(yáng) 時(shí)間: 2025-3-23 22:25 作者: 冷漠 時(shí)間: 2025-3-24 03:06 作者: 不易燃 時(shí)間: 2025-3-24 10:13
SkyGraph: An Algorithm for Important Subgraph Discovery in Relational Graphsoarray data in bioinformatics, (ii) pattern discovery in social networks, (iii) analysis of transportation networks, (iv) community discovery in Web data. Existing pattern discovery approaches operate by using simple constraints on the mined patterns. For example, given a database of graphs, a typic作者: MUTED 時(shí)間: 2025-3-24 14:23 作者: 單色 時(shí)間: 2025-3-24 15:30 作者: ANIM 時(shí)間: 2025-3-24 21:43
Two Heads Better Than One: Pattern Discovery in Time-Evolving Multi-aspect Data associated type (e.g., temperature, humidity, etc) as well as location. Time-stamp, type and location are the three aspects, which can be modeled using a tensor (high-order array). However, the time aspect is special, with a natural ordering, and with successive time-ticks having usually correlated作者: irritation 時(shí)間: 2025-3-25 00:34
ffentlichkeit eines Landes wie Lenin. Tag für Tag preisen sowjetische Ver?ffentlichungen - Redner, Zeitungen, Zeitschriften, Rund- funk - Lenin als Vorbild in jeder Hinsicht. Jede wichtige Ma?nahme der kommunistischen Partciführung auf dem Gebiete der Au?enpolitik, Wirt- schaftspolitik, im organisat作者: 懶惰民族 時(shí)間: 2025-3-25 06:13 作者: 孵卵器 時(shí)間: 2025-3-25 07:33
Christos Dimitrakakis,Michail G. Lagoudakisraktische Ergebnisse, gestützt auf theoretische Erw?gungen, .Das Buch enth?lt neue Berechnungsgrundlagen und eine praxisorientierte systematische Sicht für die Gestaltung und Bemessung der Lenksysteme an Nutzfahrzeugen. Im Mittelpunkt stehen vor allem Off-Road-, Bau-, Bergbau-, Landwirtschafts-, For作者: Respond 時(shí)間: 2025-3-25 14:26 作者: anachronistic 時(shí)間: 2025-3-25 17:54 作者: jettison 時(shí)間: 2025-3-25 23:59 作者: Cubicle 時(shí)間: 2025-3-26 03:38 作者: 溫順 時(shí)間: 2025-3-26 06:00
Stijn Vanderlooy,Eyke Hüllermeierraktische Ergebnisse, gestützt auf theoretische Erw?gungen, .Das Buch enth?lt neue Berechnungsgrundlagen und eine praxisorientierte systematische Sicht für die Gestaltung und Bemessung der Lenksysteme an Nutzfahrzeugen. Im Mittelpunkt stehen vor allem Off-Road-, Bau-, Bergbau-, Landwirtschafts-, For作者: 夾克怕包裹 時(shí)間: 2025-3-26 09:39 作者: aspect 時(shí)間: 2025-3-26 13:42 作者: 可行 時(shí)間: 2025-3-26 18:44 作者: Admonish 時(shí)間: 2025-3-26 21:06 作者: obtuse 時(shí)間: 2025-3-27 04:35
Jimeng Sun,Charalampos E. Tsourakakis,Evan Hoke,Christos Faloutsos,Tina Eliassi-Radund Torsionsstab des Lenkgetriebes so miteinander gekoppelt, dass die am Lenkrad eingeleitete Drehbewegung quasi verlustfrei und ohne Spiel übertragen wird. Ebenso werden die vom Lenkgetriebe ausgehenden Drehmomente an das Lenkrad übertragen. Somit werden durch die Koppelglieder Lenks?ule und Lenkzw作者: 來就得意 時(shí)間: 2025-3-27 07:42 作者: inventory 時(shí)間: 2025-3-27 12:42 作者: parasite 時(shí)間: 2025-3-27 17:42
From Microscopy Images to Models of Cellular Processese believe, will allow the rapid integration of computer vision methods with confocal microscopy and open the way to the development of quantitative spatial models of cellular processes..For more information, see http://seed.ucsd.edu/?yfreund/NewHomePage/ Applications/Biomedical Imaging.html作者: 半球 時(shí)間: 2025-3-27 20:02
Learning Language from Its Perceptual Contextcommentate novel games. The system is evaluated based on its ability to parse sentences into correct meanings and generate accurate descriptions of game events. Human evaluation was also conducted on the overall quality of the generated sportscasts and compared to human-generated commentaries.作者: 態(tài)學(xué) 時(shí)間: 2025-3-28 01:07 作者: Magnitude 時(shí)間: 2025-3-28 02:22
Mining Conjunctive Sequential Patternsconjunctions of sequences as the pattern type, we can easily form association rules between sequences. We believe that building a theoretical framework and an efficient approach for sequence association rules extraction problem is the first step toward the generalization of association rules to all complex and ordered patterns.作者: 食道 時(shí)間: 2025-3-28 08:02
Data Clustering: 50 Years Beyond K-meansls. The absence of category information distinguishes cluster analysis (unsupervised learning) from discriminant analysis (supervised learning). The objective of cluster analysis is to simply find a convenient and valid organization of the data, not to establish rules for separating future data into categories.作者: acheon 時(shí)間: 2025-3-28 13:22
Adequate Condensed Representations of Patternstingness of patterns is evaluated by various many other user-defined measures (e.g., confidence, lift, minimum). To the best of our knowledge, these measures have received very little attention. The Galois closure is appropriate to frequency based measures but unfortunately not to other measures.作者: Communal 時(shí)間: 2025-3-28 17:40
Conference proceedings 2008in Antwerp, Belgium, in September 2008. The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Jo作者: Indent 時(shí)間: 2025-3-28 20:28 作者: gonioscopy 時(shí)間: 2025-3-29 02:56 作者: flavonoids 時(shí)間: 2025-3-29 03:17
Machine Learning and Knowledge Discovery in Databases978-3-540-87479-9Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 確保 時(shí)間: 2025-3-29 08:26 作者: insolence 時(shí)間: 2025-3-29 14:52 作者: debacle 時(shí)間: 2025-3-29 19:27
The Role of Hierarchies in Exploratory Data Miningold: first, the size of the space raises computational challenges, and second, it can introduce data sparsity issues even in the presence of very large datasets. In this talk, well consider how the use of hierarchies (e.g., taxonomies, or the OLAP multidimensional model) can help mitigate the problem.作者: 詩集 時(shí)間: 2025-3-29 23:30
The Boolean Column and Column-Row Matrix Decompositionsata matrix. Different decomposition formulations have been proposed for this task, many of which assume a certain property of the input data (e.g., nonnegativity) and aim at preserving that property in the decomposition.作者: deface 時(shí)間: 2025-3-30 01:26 作者: 解開 時(shí)間: 2025-3-30 04:21 作者: 要控制 時(shí)間: 2025-3-30 08:29
Machine Learning and Knowledge Discovery in DatabasesEuropean Conference,作者: 表主動(dòng) 時(shí)間: 2025-3-30 13:47 作者: 射手座 時(shí)間: 2025-3-30 16:39
Rollout Sampling Approximate Policy Iterationg the setting as akin to a bandit problem over the states from which rollouts are performed. Our contribution is two-fold: (a) we suitably adapt existing bandit techniques for rollout management, and (b) we suggest a more appropriate statistical test for identifying states with dominating actions ea作者: 上坡 時(shí)間: 2025-3-30 21:57 作者: Inkling 時(shí)間: 2025-3-31 03:10
Incremental Exemplar Learning Schemes for Classification on Embedded Devicesar sets of any user-defined size) and (3) robust (such that the exemplar sets generalize for other classifiers as well). Our proposed methods are as follows:.We show that our schemes efficiently incorporate new training datasets while maintaining high-quality exemplar sets of any user-defined size. 作者: 詞根詞綴法 時(shí)間: 2025-3-31 05:52
A Collaborative Filtering Framework Based on Both Local User Similarity and Global User Similaritycan be connected through their locally similar neighbors. A weighted user graph is first constructed by using local similarity of any two users as the weight of the edge connecting them. Then the global similarity can be calculated as the maximin distance of any two nodes in the graph. Based on both作者: Conducive 時(shí)間: 2025-3-31 11:53 作者: Presbyopia 時(shí)間: 2025-3-31 16:45 作者: 名次后綴 時(shí)間: 2025-3-31 20:45 作者: bourgeois 時(shí)間: 2025-3-31 21:59
Two Heads Better Than One: Pattern Discovery in Time-Evolving Multi-aspect Datarthermore, 2-heads has several other advantages as well: (a) it can be computed incrementally in a streaming fashion, (b) it has a provable error guarantee and, (c) it achieves significant compression ratio against competitors. Finally, we show experiments on real datasets, and we illustrate how 2-h作者: Banister 時(shí)間: 2025-4-1 03:25 作者: 費(fèi)解 時(shí)間: 2025-4-1 08:19 作者: 慷慨不好 時(shí)間: 2025-4-1 11:57
Ran El-Yaniv,Dmitry Pechyony,Vladimir Vapnikndung nur über eine bescheidene Bibliographie verfügen. Die praktischen Ergebnisse, gestützt auf theoretische Erw?gungen, werden in Gestalt von innovativen mechanischen oder mechatronischen technischen L?sungen dargestellt..978-3-540-26461-3Series ISSN 2512-5281 Series E-ISSN 2512-529X 作者: 輕而薄 時(shí)間: 2025-4-1 16:33
Ankur Jain,Daniel Nikovskindung nur über eine bescheidene Bibliographie verfügen. Die praktischen Ergebnisse, gestützt auf theoretische Erw?gungen, werden in Gestalt von innovativen mechanischen oder mechatronischen technischen L?sungen dargestellt..978-3-540-26461-3Series ISSN 2512-5281 Series E-ISSN 2512-529X
