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Disjoint Access Parallelism (DAP) stipulates that operations involving disjoint sets of memory words must be able to progress independently, without interfering with each other. In this work we argue towards revising the two decade old wisdom saying that D ...
Recent advances in associative memory design through structured pattern sets and graph-based inference al- gorithms have allowed reliable learning and recall of an exponential number of patterns. Although these designs correct external errors in recall, th ...
How to attenuate traumatic memories has long been the focus of intensive research efforts, as traumatic memories are extremely persistent and heavily impinge on the quality of life. Despite the fact that traumatic memories are often not readily amenable to ...
Traumatic events generate some of the most enduring forms of memories. Despite the elevated lifetime prevalence of anxiety disorders, effective strategies to attenuate long-term traumatic memories are scarce. The most efficacious treatments to diminish rec ...
Disjoint Access Parallelism (DAP) stipulates that operations involving disjoint sets of memory words must be able to progress independently, without interfering with each other. In this work we argue towards revising the two decade old wisdom saying that D ...
A recent PVLDB paper reports on experimental analyses of ten spatial join techniques in main memory. We build on this comprehensive study to raise awareness of the fact that empirical running time performance findings in main-memory settings are results of ...
Recent brain imaging research has highlighted a new global system of areas termed the Default Mode network (DM), which appears to specialize in intrinsically oriented functions. However, it is still unresolved to what extent this system contains functional ...
Reward mediates the acquisition and long-term retention of procedural skills in humans. Yet, learning under rewarded conditions is highly variable across individuals and the mechanisms that determine interindividual variability in rewarded learning are not ...
We propose a novel architecture to design a neural associative memory that is capable of learning a large number of patterns and recalling them later in presence of noise. It is based on dividing the neurons into local clusters and parallel plains, an arch ...
We consider the problem of neural association for a network of nonbinary neurons. Here, the task is to first memorize a set of patterns using a network of neurons whose states assume values from a finite number of integer levels. Later, the same network sh ...
