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12,097
Xmeans: Extending Kmeans with Efficient Estimation of the Number of Clusters
 In Proceedings of the 17th International Conf. on Machine Learning
, 2000
"... Despite its popularity for general clustering, Kmeans suffers three major shortcomings; it scales poorly computationally, the number of clusters K has to be supplied by the user, and the search is prone to local minima. We propose solutions for the first two problems, and a partial remedy for the t ..."
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Cited by 418 (5 self)
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and their parameters. Experiments show this technique reveals the true number of classes in the underlying distribution, and that it is much faster than repeatedly using accelerated Kmeans for different values of K.
Autograph: Toward automated, distributed worm signature detection
 In Proceedings of the 13th Usenix Security Symposium
, 2004
"... Today’s Internet intrusion detection systems (IDSes) monitor edge networks ’ DMZs to identify and/or filter malicious flows. While an IDS helps protect the hosts on its local edge network from compromise and denial of service, it cannot alone effectively intervene to halt and reverse the spreading o ..."
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Cited by 362 (3 self)
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by analyzing the prevalence of portions of flow payloads, and thus uses no knowledge of protocol semantics above the TCP level. It is designed to produce signatures that exhibit high sensitivity (high true positives) and high specificity (low false positives); our evaluation of the system on real DMZ traces
Strictly Proper Scoring Rules, Prediction, and Estimation
, 2007
"... Scoring rules assess the quality of probabilistic forecasts, by assigning a numerical score based on the predictive distribution and on the event or value that materializes. A scoring rule is proper if the forecaster maximizes the expected score for an observation drawn from the distribution F if he ..."
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Cited by 373 (28 self)
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scores. The continuous ranked probability score applies to probabilistic forecasts that take the form of predictive cumulative distribution functions. It generalizes the absolute error and forms a special case of a new and very general type of score, the energy score. Like many other scoring rules
Model selection and accounting for model uncertainty in graphical models using Occam's window
, 1993
"... We consider the problem of model selection and accounting for model uncertainty in highdimensional contingency tables, motivated by expert system applications. The approach most used currently is a stepwise strategy guided by tests based on approximate asymptotic Pvalues leading to the selection o ..."
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Cited by 370 (47 self)
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Bayesian formalism which averages the posterior distributions of the quantity of interest under each of the models, weighted by their posterior model probabilities. Furthermore, this approach is optimal in the sense of maximising predictive ability. However, this has not been used in practice because
A family of algorithms for approximate Bayesian inference
, 2001
"... One of the major obstacles to using Bayesian methods for pattern recognition has been its computational expense. This thesis presents an approximation technique that can perform Bayesian inference faster and more accurately than previously possible. This method, "Expectation Propagation," ..."
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Cited by 366 (11 self)
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," unifies and generalizes two previous techniques: assumeddensity filtering, an extension of the Kalman filter, and loopy belief propagation, an extension of belief propagation in Bayesian networks. The unification shows how both of these algorithms can be viewed as approximating the true posterior
Binary operations
 Journal of Formalized Mathematics
, 1989
"... Summary. In this paper we define binary and unary operations on domains. We also define the following predicates concerning the operations:... is commutative,... is associative,... is the unity of..., and... is distributive wrt.... A number of schemes useful in justifying the existence of the operat ..."
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Cited by 363 (6 self)
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Summary. In this paper we define binary and unary operations on domains. We also define the following predicates concerning the operations:... is commutative,... is associative,... is the unity of..., and... is distributive wrt.... A number of schemes useful in justifying the existence
Posterior Predictive Assessment of Model Fitness Via Realized Discrepancies
 Statistica Sinica
, 1996
"... Abstract: This paper considers Bayesian counterparts of the classical tests for goodness of fit and their use in judging the fit of a single Bayesian model to the observed data. We focus on posterior predictive assessment, in a framework that also includes conditioning on auxiliary statistics. The B ..."
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Cited by 348 (39 self)
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. The Bayesian formulation facilitates the construction and calculation of a meaningful reference distribution not only for any (classical) statistic, but also for any parameterdependent “statistic ” or discrepancy. The latter allows us to propose the realized discrepancy assessment of model fitness, which
The positive false discovery rate: A Bayesian interpretation and the qvalue
 Annals of Statistics
, 2003
"... Multiple hypothesis testing is concerned with controlling the rate of false positives when testing several hypotheses simultaneously. One multiple hypothesis testing error measure is the false discovery rate (FDR), which is loosely defined to be the expected proportion of false positives among all s ..."
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Cited by 337 (8 self)
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and disadvantages of the pFDR and investigate its statistical properties. When assuming the test statistics follow a mixture distribution, we show that the pFDR can be written as a Bayesian posterior probability and can be connected to classification theory. These properties remain asymptotically true under fairly
Advanced and Authenticated Marking Schemes for IP Traceback
 IN: PROCEEDINGS OF IEEE INFOCOM CONFERENCE
, 2000
"... Defending against distributed denialofservice attacks is one of the hardest security problems on the Internet today. One difficulty to thwart these attacks is to trace the sourec of the attacks because they often use incorrect, or spoofed IP source addresses to disguide the true origin. In this pa ..."
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Cited by 316 (7 self)
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Defending against distributed denialofservice attacks is one of the hardest security problems on the Internet today. One difficulty to thwart these attacks is to trace the sourec of the attacks because they often use incorrect, or spoofed IP source addresses to disguide the true origin
Tractable inference for complex stochastic processes
 In Proc. UAI
, 1998
"... The monitoring and control of any dynamic system depends crucially on the ability to reason about its current status and its future trajectory. In the case of a stochastic system, these tasks typically involve the use of a belief state—a probability distribution over the state of the process at a gi ..."
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Cited by 302 (14 self)
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The monitoring and control of any dynamic system depends crucially on the ability to reason about its current status and its future trajectory. In the case of a stochastic system, these tasks typically involve the use of a belief state—a probability distribution over the state of the process at a
Results 11  20
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12,097