are represented as pseudo-document vectors formed from weighted combinations of terms, and documents with supra-threshold cosine values are re-turned. initial tests find this completely automatic method for retrieval to be promising.

A distributed algorithm is presented that constructs he minimum-weight spanning tree in a connected undirected graph with distinct edge weights. A processor exists at each node of the graph, knowing initially only the weights of the adjacent edges. The processors obey the same algorithm

at a time, provided the top two layers form an undirected associative memory. The fast, greedy algorithm is used to initialize a slower learning procedure that fine-tunes the weights using a contrastive version of the wake-sleep algorithm. After fine-tuning, a network with three hidden layers forms a

splice site consenses, codon bias, exon/intron length preferences, and open reading frame analysis all in one scoring system. How should all those parameters be set? How should different kinds of information be weighted? A second issue is being able to interpret results probabilistically. Finding a best

to the correct marginals. However, on the QMR network, the loopy be liefs oscillated and had no obvious relation ship to the correct posteriors. We present some initial investigations into the cause of these oscillations, and show that some sim ple methods of preventing them lead to the wrong results

Atmospheric CO2 concentrations, have been successfully retrieved from spectral measurements made in the near infrared (NIR) by the SCIAMACHY instrument, using a new retrieval algorithm called Full

This paper presents a rapid initial weight computation method for adaptive array antennas. The proposed method estimates a correlation matrix using not only samples received with the desired signal but also those received from other sources. The proposed method reduces the number of known symbols

the optimization, by initializing weights in a region near a good local minimum, giving rise to internal distributed representations that are high-level abstractions of the input, bringing better generalization.

), the algorithm has two integral parts: a low-resolution initial estimate of the real signal and the iteration process that refines the initial estimate to the final localized energy solution. The iterations are based on weighted norm minimization of the dependent variable with the weights being a function

this loss, some saying that it is natural and may continue, others that it is harmful and should be stopped. At the same time some say that the average loss 'on the third day post-partum ' is 3-8 % of the birth weight (Kotz and Kaufman, 1939), others that it averages 4 5 % over the first few days