Optimizing programs at run-time provides opportunities to apply aggressive optimizations to programs based on information that was not available at compile time. At run time, prog...
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
Inspired by syndrome source coding using linear error-correcting codes, we explore a new form of measurement matrix for compressed sensing. The proposed matrix is constructed in t...
—We take a systematic approach to developing a symmetric cryptography library in Javascript. We study various strategies for optimizing the code for the Javascript interpreter, a...
We present a modular approach to implement adaptive decisions with existing scientific codes. Using a sophisticated system software tool based on the function call interception t...
Pilsung Kang 0002, Yang Cao, Naren Ramakrishnan, C...