Multiomics data integration with machine learning has become the standard approach for combining genomic, transcriptomic, proteomic, and metabolomic measurements collected from the same biological ...

Abstract: Recovering structured models (e.g., sparse or group-sparse vectors, low-rank matrices) given a few linear observations have been well-studied recently. In various applications in signal ...

Sparse matrices, which are common in scientific applications, are matrices in which most elements are zero. To save space and running time it is critical to only store the nonzero elements. A standard ...

Michelle Obama's fashion diplomacy shines at new the Obama Presidential Center. Bobbi Brown chats about bringing Jones Road to the West Coast. Dataland in DTLA rivals Walt Disney's "Fantasia." And the ...

Abstract: An efficient and training-sample-reducing space-time adaptive processing (STAP) algorithm based on sparse representation for ground clutter suppression in airborne radar is proposed in this ...

KokkosKernels implements local computational kernels for linear algebra and graph operations, using the Kokkos shared-memory parallel programming model. "Local" means not using MPI, or running within ...

Artificial intelligence is hijacking our brains. Discover how the digital shortcuts we use impact our decision-making, and ...

Discover how heterogeneous compute templates optimize fast token generation and lower total cost of ownership for enterprise ...

In his decades-long career in tech journalism, Dennis has written about nearly every type of hardware and software. He was a founding editor of Ziff Davis’ Computer Select in the 1990s, senior ...

Imagine standing in the emptiest place the universe has to offer, a stretch of cosmic ocean so vast that light takes tens of ...

Environmental sustainability in tertiary sports remains an emergent yet under-resourced domain, particularly in sub-Saharan ...