Quantum Shannon theory is loosely defined as a collection of coding theorems, such as classical and quantum source compression, noisy channel coding theorems, entanglement distilla...
Igor Devetak, Aram Wettroth Harrow, Andreas J. Win...
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Genome-wide microarray designs containing millions to hundreds of millions of probes are available for a variety of mammals, including mouse and human. These genome tiling arrays ...
In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. These representa...
Convergent scheduling is a general framework for instruction scheduling and cluster assignment for parallel, clustered architectures. A convergent scheduler is composed of many ind...
Walter Lee, Diego Puppin, Shane Swenson, Saman P. ...