One of the difficulties of Data Envelopment Analysis(DEA) is the problem of deciency discriminationamong efficient Decision Making Units(DMUs) and hence, yielding large number of DMUs as efficientones. The main purpose of this paper is to overcome this inability. One of the methods for rankingefficient DMUs is minimizing the Coefficient of Variation (CV) for inputs-outputs weights. In this pape...

We have developed a hierarchical performance bounding methodology that attempts to explain the performance of loop-dominated scientific applications on particular systems. The Kendall Square Research KSR1 is used as a running example. We model the throughput of key hardware units that are common bottlenecks in concurrent machines. The four units currently used are: memory port, floating-point, ...

In this work, we improve the performance of a dialogue engine, Say Something Smart, using online learning. Given a request by a user, this engine selects an answer from a corpus of movie subtitles, weighting the quality of each candidate answer according to several criteria and selecting the one that is chosen by the most representative criteria. We contribute with an online approach, using seq...

Fundamental self-organizing artificial neural networks, both static (with predefined number of neurons) and incremental, are presented and goals of competitive learning are enumerated. A novel incremental self-organizing ANN Cooling Growing Grid (CGG) is proposed, which combines the advantages of static and incremental approaches and overcomes their main drawbacks. The estimation of growth dire...

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We examined the coding of sound-source location by ensembles of neurons in the auditory cortex. Broadband noise bursts were presented from loudspeakers throughout 360 degrees in the horizontal plane. Sound levels varied from 20 to 40 dB above neural thresholds. We recorded temporal spike patterns simultaneously at 16 recording sites in area A2 of alpha-chloralose-anesthetized cats. Spike patter...

This paper introduces a class of higher-order networks called pi-sigma networks (PSNs). PSNs are feedforward networks with a single \hidden" layer of linear summing units, and with product units in the output layer. A PSN uses these product units to indirectly incorporate the capabilities of higher-order networks while greatly reducing network complexity. PSNs have only one layer of adjustable ...