We consider the existence of a linear weak learner for boosting algorithms. A weak learner for binary classification problems is required to achieve a weighted empirical error on t...
d Abstract] György Elekes Eötvös University Micha Sharir Tel Aviv University and New York University We first describe a reduction from the problem of lower-bounding the numbe...
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
In previous work [Zlotkin and Rosenschein, 1989a], we have developed a negotiation protocol and offered some negotiation strategies that are in equilibrium. This negotiation proce...
Multi-dimensional spatial data are obtained when a number of data acquisition devices are deployed at different locations to measure a certain set of attributes of the study subje...