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Elements of artificial neural networks
TLDR
History of neural networks supervised learning - single-layer networks supervisedlearning - multilayer networks I unsupervised learning associative models optimization methods a little math data. Expand
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An efficient k-means clustering algorithm
In this paper, we present a novel algorithm for performing k-means clustering. It organizes all the patterns in a k-d tree structure such that one can find all the patterns which are closest to aExpand
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Efficient classification for multiclass problems using modular neural networks
TLDR
The rate of convergence of net output error is very low when training feedforward neural networks for multiclass problems using the backpropagation algorithm. Expand
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Forecasting the behavior of multivariate time series using neural networks
TLDR
This paper presents a neural network approach to multivariate time-series analysis. Expand
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An improved algorithm for neural network classification of imbalanced training sets
TLDR
The backpropagation algorithm converges very slowly for two-class problems in which most of the exemplars belong to one dominant class. Expand
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Conditional Anomaly Detection
TLDR
This paper describes a general purpose method called conditional anomaly detection for taking such differences among attributes into account, and proposes three different expectation-maximization algorithms for learning the model that is used in conditional anomaly Detection. Expand
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An Efficient Algorithm for the Incremental Updation of Association Rules in Large Databases
TLDR
We propose an incremental updating technique based on negative borders, for the maintenance of association rules when new transaction data is added to or deleted from a transaction database. Expand
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Dynamic cache reconfiguration and partitioning for energy optimization in real-time multi-core systems
TLDR
In this paper, we present a novel energy optimization technique which employs both dynamic reconfiguration of private caches and partitioning of the shared cache for multicore systems with real-time tasks. Expand
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Applications and performance analysis of a compile-time optimization approach for list scheduling algorithms on distributed memory multiprocessors
TLDR
The authors discuss applications of BTDH (bottom-up top-down duplication heuristic) to list scheduling algorithms (LSAs). Expand
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Statistical change detection for multi-dimensional data
TLDR
We propose a statistical test called the density test for detecting change of distribution in multi-dimensional data sets. Expand
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