Power minimization under variability is formulated as a rigorous statistical robust optimization program with a guarantee of power and timing yields. Both power and timing metrics...
We consider the problem of unsupervised learning from a matrix of data vectors where in each row the observed values are randomly permuted in an unknown fashion. Such problems ari...
Tiling, a key transformation for optimizing programs, has been widely studied in literature. Parameterized tiled code is important for auto-tuning systems since they often execute...
Muthu Manikandan Baskaran, Albert Hartono, Sanket ...
We describe a semantic type soundness result, formalized in the Coq proof assistant, for a compiler from a simple imperative language with heap-allocated data into an idealized as...
This paper presents a kernel density estimation method by means of real-coded crossovers. Estimation of density algorithms (EDAs) are evolutionary optimization techniques, which d...