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Results 1 - 10
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419
From Data Mining to Knowledge Discovery in Databases.
- AI Magazine,
, 1996
"... ■ Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. What is all the excitement about? This article provides an overview of this emerging field, clarifying how data mining and knowledge discovery in database ..."
Abstract
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Cited by 538 (0 self)
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predictive model for estimating the value of future cases). At the core of the process is the application of specific data-mining methods for pattern discovery and extraction. 1 This article begins by discussing the historical context of KDD and data mining and their intersection with other related fields. A
Hierarchical Bayesian Inference in the Visual Cortex
, 2002
"... this paper, we propose a Bayesian theory of hierarchical cortical computation based both on (a) the mathematical and computational ideas of computer vision and pattern the- ory and on (b) recent neurophysiological experimental evidence. We ,2 have proposed that Grenander's pattern theory 3 coul ..."
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Cited by 300 (2 self)
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of Zhu and colleagues 7, 8 might be the most successful recent application of this proposal in solving real and difficult computer vision problems using generafive models, though its connection to the visual cortex has not been explored. Here, we bring in a powerful and widely applicable paradigm from
Behavioral theories and the neurophysiology of reward,
- Annu. Rev. Psychol.
, 2006
"... ■ Abstract The functions of rewards are based primarily on their effects on behavior and are less directly governed by the physics and chemistry of input events as in sensory systems. Therefore, the investigation of neural mechanisms underlying reward functions requires behavioral theories that can ..."
Abstract
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Cited by 187 (0 self)
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(Amador et al. 2000, Apicella et al. 1991 Contiguity Procedures involving Pavlovian conditioning provide simple paradigms for learning and allow the experimenter to test the basic requirements of contiguity, contingency, and prediction error. Contiguity can be tested by presenting a reward 1.5-2.0 seconds
Algorithms, Experimentation
"... We present in this paper results on inferring a signed network (a “web of trust”) from interactions on user-generated content inWiki-pedia. From a collection of articles in the politics domain and their revision history, we investigate mechanisms by which rela-tionships between Wikipedia contributor ..."
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of link signs. We assess connections to social theories such as structural balance and status, which have already been considered in online communities. We also evaluate on this network the accu-racy of a learned predictor for edge signs. Equipped with learning techniques that have been applied in recent
Issues in Evaluation of Stream Learning Algorithms
"... Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that continuously evolve over time, run in resource-aware environments, detect and react to changes in the environment generati ..."
Abstract
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Cited by 47 (7 self)
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Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that continuously evolve over time, run in resource-aware environments, detect and react to changes in the environment
Learn to Predict “Affecting Changes ” in Software Engineering
"... This paper explores a new possible application of machine learning algorithms: change impact analysis. Two versions of a java project were analyzed and their differences were decomposed into a unique set of atomic changes. The execution behavior of a test may have been affected by the applied change ..."
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This paper explores a new possible application of machine learning algorithms: change impact analysis. Two versions of a java project were analyzed and their differences were decomposed into a unique set of atomic changes. The execution behavior of a test may have been affected by the applied
Materials for an exploratory theory of the network society.
- The British Journal of Sociology
, 2000
"... ABSTRACT This article aims at proposing some elements for a grounded theor y of the network society. The network society is the social structure characteristic of the Information Age, as tentatively identi ed by empirical, cross-cultural investigation. It permeates most societies in the world, in v ..."
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Cited by 122 (0 self)
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in technical relationships, which are socially conditioned, so in itself it is not an independent, non-human dimension. In principle, because it is the application of knowledge to obtain a product of some kind, it could be assigned primarily to the process of production, in which we could then distinguish
The BKZ Simulation Algorithm
"... Hiermit versichere ich, die vorliegende Bachelor-Thesis ohne Hilfe Dritter nur mit den angegebenen Quellen und Hilfsmitteln angefertigt zu haben. Alle Stellen, die aus Quellen entnommen wurden, sind als solche kenntlich gemacht. Diese Arbeit hat in gleicher oder ähnlicher Form noch keiner Prüfungsbe ..."
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. The BKZ simulation algorithm by Chen and Nguyen predicts the Gram-Schmidt norms of a lattice basis after a given time of rounds of BKZ reduction. Given the cost of the enumeration subroutine used in BKZ reduction, the simulation algorithm can also be used to estimate the running time of BKZ reduction
Machine Learning Application for Stock Market Price Prediction
"... ABSTRACT The development of a vibrant application for analyzing and predicting stock market prices is a basic tool aimed at increasing the rate of investors' interest in stock markets. This paper explains the development and implementation of a stock price prediction application using machine ..."
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learning algorithm and object oriented approach of software system development. The algorithm was used in training a set of market data collected for the period of one thousand, two hundred and three days. The implementation was done with Java programming language and Neuroph software. From the experiments
A Unifying Framework for Detecting Outliers and Change Points from Non-Stationary Time Series Data
- In Proc. of the Eighth ACM SIGKDD, ACM
, 2002
"... We m'e concerned vith the issues of outlier detection and change point detection from a data stream. In the area of data mining, there have been increased interest in these issues since the former is related to fraud detection, rare event discovery, etc., vhile the latter is related to event/tr ..."
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Cited by 74 (3 self)
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stream are detected by applying this scoring method into a time series of moving averaged losses for prediction using the learned model. Specifically ve develop an efficient algorithms for on-line discounting learning of auto-regression models from time series data, and demonstrate the validity of our
Results 1 - 10
of
419
