— We introduce the Oracular Partially Observable Markov Decision Process (OPOMDP), a type of POMDP in which the world produces no observations; instead there is an “oracle,” ...
The advent of sensor networks presents untapped opportunities for synthesis. We examine the problem of synthesis of behavioral specifications into networks of programmable sensor ...
Ryan Mannion, Harry Hsieh, Susan Cotterell, Frank ...
The capability of multi-objective evolutionary algorithms (MOEAs) to handle premature convergence is critically important when applied to real-world problems. Their highly multi-mo...
Jianjun Hu, Kisung Seo, Zhun Fan, Ronald C. Rosenb...
Since the C language imposes little restriction on the use of function pointers, the task of call graph construction for a C program is far more di cult than what the algorithms d...
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a linear combination of the input variables while constraining the number of nonze...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...