Abstract: We consider the binary classification problem of static and dynamic mixed data in this paper. Different from mixed categorical and numerical data, the dynamic variables in the new type of ...

SINGAPORE: The announcement on Monday (Apr 13) that the medical grading system for national servicemen will be changed beginning in October next year caught the attention of many in Singapore.

CLAP (Contrastive Language-Assembly Pre-training) is a framework that learns binary code representations through natural language supervision. By aligning binary code with natural language ...

The bias problem in classification tasks and the different strategies used for bias mitigation. How these strategies are grouped into categories and a brief introduction of the most representative ...

Decision by high court’s conservative majority is Trump administration’s latest win on emergency docket The supreme court on Thursday allowed Donald Trump’s administration to enforce a policy blocking ...

President Donald Trump’s administration asked the Supreme Court on Friday to let it enforce a passport policy for transgender and nonbinary people that requires male or female sex designations based ...

NeuralClassifier is designed for quick implementation of neural models for hierarchical multi-label classification task, which is more challenging and common in real-world scenarios. A salient feature ...

Section 1. Purpose. Across the country, ideologues who deny the biological reality of sex have increasingly used legal and other socially coercive means to permit men to self-identify as women and ...

In binary systems, each digit is referred to as a bit (short for binary digit). Each bit can either be 0 or 1, representing no electrical charge (off) or an electrical charge (on). Bits are grouped in ...

In veterinary medicine, attempts to apply artificial intelligence (AI) to ultrasonography have rarely been reported, and few studies have investigated the value of AI in ultrasonographic diagnosis.

Abstract: For the problem of binary linear classification and feature selection, we propose algorithmic approaches to classifier design based on the generalized approximate message passing (GAMP) ...