We consider the sparse Fourier transform problem: given a complex vector x of length n, and a parameter k, estimate the k largest (in magnitude) coefficients of the Fourier transf...
Haitham Hassanieh, Piotr Indyk, Dina Katabi, Eric ...
We develop, analyze, and evaluate a novel, supervised, specific-to-general learner for a simple temporal logic and use the resulting algorithm to learn visual event definitions fr...
Robotic sensor networks are more powerful than sensor networks because the sensors can be moved by the robots to adjust their sensing coverage. In robotic sensor networks, an impor...
In real-life temporal scenarios, uncertainty and preferences are often essential, coexisting aspects. We present a formalism where temporal constraints with both preferences and un...
Francesca Rossi, Kristen Brent Venable, Neil Yorke...
We present a new efficient approach for solving the multicommodity flow problem as a sequence of subproblems, each on a very sparse but connected network. We show that each subpro...