Abstract: Conventional soft clustering algorithms perform well on linearly distributed features, but their performance degrades on nonlinearly distributed features in high-dimensional space. In this ...
While the creation of this new entity marks a big step toward avoiding a U.S. ban, as well as easing trade and tech-related tensions between Washington and Beijing, there is still uncertainty ...
Abstract: Most clustering algorithms require setting one or more parameters, which rely on prior knowledge or are constantly adjusted based on external indicators. To address the issues of requiring ...
Landlords could no longer rely on rent-pricing software to quietly track each other's moves and push rents higher using confidential data, under a settlement between RealPage Inc. and federal ...
WASHINGTON — The U.S. Army announced updates to its Direct Commissioning Program, DCP, aimed at attracting top-tier professionals with specialized skills directly into its officer corps. The program ...
In structural health monitoring (SHM), uncertainties from environmental noise and modeling errors affect damage detection accuracy. This paper introduces a new concept: the Fast Fourier Transform ...
Graduate School of Economics, The University of Osaka, Osaka, Japan. Stock returns exhibit nonlinear dynamics and volatility clustering. It is well known that we cannot forecast the movements of stock ...
Cryptography secures communication in banking, messaging, and blockchain. Good algorithms (AES, RSA, ECC, SHA-2/3, ChaCha20) are secure, efficient, and widely trusted. Bad algorithms (DES, MD5, SHA-1, ...
There's a familiar TV discourse taking shape online right now, the kind that I suspect will look awfully familiar to you if you remember the way Game of Thrones crashed and burned in its eighth and ...
Collateral Damage for the Coal Industry? Sue-Pervised Retirement Lawfare Is the Climate Warriors’ Best Friend Why Canada Engaged China Ahead of the USMCA Review We Need a Private-Sector Overhaul of ...
Researchers have developed a new AI algorithm, called Torque Clustering, that significantly improves how AI systems independently learn and uncover patterns in data, without human guidance.
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