The well-studied task of learning a linear function with errors is a seemingly hard problem and the basis for several cryptographic schemes. Here we demonstrate additional applicat...
Benny Applebaum, David Cash, Chris Peikert, Amit S...
We prove space hierarchy and separation results for randomized and other semantic models of computation with advice where a machine is only required to behave appropriately when g...
A new kernel function between two labeled graphs is presented. Feature vectors are defined as the counts of label paths produced by random walks on graphs. The kernel computation ...
We investigate how stack filter function classes like weighted order statistics can be applied to classification problems. This leads to a new design criteria for linear classifie...
Reid B. Porter, Damian Eads, Don R. Hush, James Th...
When similarity queries over multimedia databases are processed by splitting the overall query condition into a set of sub-queries, the problem of how to efficiently and effectiv...
Ilaria Bartolini, Paolo Ciaccia, Vincent Oria, M. ...