Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
The paper studies machine learning problems where each example is described using a set of Boolean features and where hypotheses are represented by linear threshold elements. One ...
In this study, we apply a novel synthesis technique for implementing robust digital computation in nanoscale lattices with random interconnects: percolation theory on random graph...
For any Boolean functionf letL(f) be its formulasizecomplexityin the basis f^ 1g. For every n and every k n=2, we describe a probabilistic distribution on formulas in the basis f^...
Abstract— The growing popularity of look-up table (LUT)based field programmable gate arrays (FPGA’s) has renewed the interest in functional or Roth–Karp decomposition techni...