In an election held in a noisy environment, agents may unintentionally perturb the outcome by communicating faulty preferences. We investigate this setting by introducing a theore...
Ariel D. Procaccia, Jeffrey S. Rosenschein, Gal A....
This paper presents the design and analysis of parallel approximation algorithms for facility-location problems, including NC and RNC algorithms for (metric) facility location, k-...
Sensing affect raises critical privacy concerns, which are examined here using ethical theory, and with a study that illuminates the connection between ethical theory and privacy....
Multi–comparand associative processors are efficient in parallel processing of complex search problems that arise from many application areas including computational geometry, ...
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...