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Data Mining in Soft Computing Framework: A Survey
White Paper Neural networks are non-parametric, robust, and exhibit good learning and generalization capabilities in data-rich environments. A categorization has been provided based on the different soft computing tools and their... [01 Oct 2008]
HIDE: A Hierarchical Network Intrusion Detection System Using Statistical Preprocessing and Neural Network Classification
White Paper Five different types of neural network classifiers are tested those are Perceptron, BackPropagation (BP), Perceptron-BackOropagation-hybrid (PBH), Fuzzy ARTMAP, and Radial-based Function. This paper... [03 Jun 2008]
HIDE: A Hierarchical Network Intrusion Detection System Using Statistical Preprocessing and Neural Network Classification
Five different types of neural network classifiers are tested those are Perceptron, BackPropagation (BP), Perceptron-BackOropagation-hybrid (PBH), Fuzzy ARTMAP, and Radial-based Function. This paper... [03 Jun 2008]
Learning to Rank With Nonsmooth Cost Functions
White Paper The paper describes LambdaRank using neural network models, although the idea applies to any differentiable function class. The quality measures used in information retrieval are particularly difficult... [08 Aug 2007]
Learning to Rank With Nonsmooth Cost Functions
White Paper The paper describes LambdaRank using neural network models, although the idea applies to any differentiable function class. The quality measures used in information retrieval are particularly difficult... [19 Jul 2007]
Poisson-Networks: A Model for Structured Point Processes
White Paper Modelling structured multivariate point process data has wide ranging applications like understanding neural activity, developing faster file access systems and learning dependencies among servers in large networks. [24 May 2007]
AA in £10m network outsourcing deal with C&W
News The AA.com website replaced its static FAQ section with neural network technology from Transversal to handle questions from its 8.2 million website visitors each month. The technology dynamically updates the FAQ... [28 Jun 2006]
Mapping Boolean Functions with Neural Networks having Binary Weights and Zero Thresholds
White Paper In this paper, the ability of a Binary Neural Network comprising only neurons with zero thresholds and binary weights to map given samples of a Boolean function is studied. These criteria provide... [25 Feb 2004]
A Two Layer Paradigm Capable of Forming Arbitrary Decision Regions in Input Space
White Paper Based on these, a new 2-layer neural paradigm based on increasing the dimensionality of the output of the first layer is proposed and is shown to be capable of forming any arbitrary decision region in input space. [25 Feb 2004]
Approximating and Simulating the Stochastic Growth Model: Parameterized Expectations, Neural Networks, and the Genetic Algorithm
White Paper We use this search procedure in combination with either polynomial or neural network specifications for the expectation function. We distinguish between polynomial and neural network... [25 Feb 2004]
