Abstract: Anomaly detection needs to learn one-class classifiers from normal instances in observation or feature spaces. In the Neyman–Pearson criterion, the design of one-class classifiers boils down ...
The quest for true randomness has roots in cryptography and is a rabbit hole that gets surprisingly deep with alarmingly ...
Abstract: In a large hospital system, a network of hospitals relies on electronic health records (EHRs) to make informed decisions regarding their patients in various clinical domains. Consequently, ...
Ligand-based drug design combines AI and QSAR modeling to prioritize drug candidates, minimizing preclinical failures and ...
The "lazy influencer" is finished. Social media hierarchies stayed frozen for a decade. If a content creator hit a million ...
Personalized algorithms may quietly sabotage how people learn, nudging them into narrow tunnels of information even when they start with zero prior knowledge. In the study, participants using ...
JHU mathematician Emily Riehl explains how a surprising amount of math goes into determining who ends up in the U.S. House of ...
Graph processes and random structures form a vibrant subfield of graph theory concerned with the probabilistic evolution of networks and the emergence of complex connectivity patterns. At its core ...
Random graph theory provides a probabilistic framework for modelling and analysing networks in which connections between entities are assigned according to specified random processes. From its origins ...
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