Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
The fastest known algorithms for factoring large numbers share a core sieving technique. The sieving cores find numbers that are completely factored over a prime base set raised t...
We present a novel application of structured classification: identifying function entry points (FEPs, the starting byte of each function) in program binaries. Such identification ...
Nathan E. Rosenblum, Xiaojin Zhu, Barton P. Miller...
It is known that if a 2-universal hash function H is applied to elements of a block source (X1, . . . , XT ), where each item Xi has enough min-entropy conditioned on the previous...
Accurate and less invasive personalized predictive medicine can spare many breast cancer patients from receiving complex surgical biopsies, unnecessary adjuvant treatments and its...
Umer Khan, Hyunjung Shin, Jongpill Choi, Minkoo Ki...