AMD and Intel have now published a full technical specification for ACE — AI Compute Extensions — the most significant overhaul to x86 AI compute in the architecture's history, co-authored by eight ...
The easiest way to start with tabmat is to use the convenience constructor tabmat.from_pandas. TL;DR: We provide matrix classes for efficiently building statistical algorithms with data that is ...
Abstract: The simultaneous orthogonal matching pursuit (SOMP) algorithm and its variants are the main recovery algorithms based on sub-Nyquist sampling (SNS) in Wideband spectrum sensing (WBSS). In ...
Abstract: In this paper, authentication for mobile radio frequency identification (RFID) systems with low-cost tags is investigated. To this end, an adaptive modulus (AM) encryption algorithm is first ...
Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on an implementation of the technique that emphasizes simplicity and ease-of-modification over robustness and ...
NonnegMFPy ----- NonnegMFPy is developed and maintained by Guangtun Ben Zhu, It is designed to solve nonnegative matrix factorization (NMF) given a dataset with heteroscedastic uncertainties and ...
Current motor imagery-based brain-computer interface (BCI) systems require a long calibration time at the beginning of each session before they can be used with adequate levels of classification ...
The Locally Competitive Algorithm (LCA) is a biologically plausible computational architecture for sparse coding, where a signal is represented as a linear combination of elements from an ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results