Abstract: Due to its strong representation learning ability and its facilitation of joint learning for representation and hash codes, deep learning-to-hash has achieved promising results and is ...

@article{roffe_decoding_2020, title={Decoding across the quantum low-density parity-check code landscape}, volume={2}, ISSN={2643-1564}, url={http://dx.doi.org/10. ...

You can check an interactive Google chart with few benchmark cases for all similarity algorithms in this library through StringsSimilarity function here However, if you want or need more details, you ...

Neuroscience (also known as neurobiology) is a science that studies the structure, function, development, pharmacology and pathology of the nervous system. In recent years, C. Cotardo has introduced ...

Numerous microarchitectural optimizations unlocked tremendous processing power for deep neural networks that in turn fueled the AI revolution. With the exhaustion of such optimizations, the growth of ...

Deep holes are very important in the decoding of generalized RS codes, and deep holes of RS codes have been widely studied, but there are few works on constructing general linear codes based on deep ...

Abstract: In this paper, we investigate an artificial-intelligence (AI) driven approach to design error correction codes (ECC). Classic error-correction code design ...

Code concatenation that uses two or more short component codes is a significant method for designing powerful codes. Concatenated classical codes are not only asymptotically good in theory, but also ...

New Yorker writers reflect on the year’s highs and lows. New York novels are as various as the city they describe. But “Want,” a subtly glorious new entry in the genre by Lynn Steger Strong, is set in ...