IEEE

Stacking Binary Neural Networks for Efficient Edge-Based Waste Classification

Abstract: Waste classification poses significant challenges owing to rapid societal development and increasing waste generation. Although deep neural networks have demonstrated remarkable results in ...
Bloomberg L.P.

Bloomberg’s AI Researchers Publish 7 Papers at EMNLP 2025

At the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025) in Suzhou, China this week (November 4-9, 2025), researchers from Bloomberg’s AI Engineering group and its BLAW ...
Scientific Research Publishing

Performance of Different Machine Learning Algorithms for Credit Risk Classification ()

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...
GitHub

[QUESTION] Determine whether distillation is appropriate for task

Thank you for the awesome library. I am trying to determine whether a specific task would be a good fit for distillation. I am working on training a distilled binary classification model to determine ...
Phys.org

Why our organs cannot simply be classified as male or female

Biological sex is usually described in simple binary terms: male or female. This works well for germ cells (sperm versus eggs), but for other body organs it is of little help. A new study by the Max ...
marktechpost

From Pretraining to Post-Training: Why Language Models Hallucinate and How Evaluation Methods Reinforce the Problem

Large language models (LLMs) very often generate “hallucinations”—confident yet incorrect outputs that appear plausible. Despite improvements in training methods and architectures, hallucinations ...
Scientific Research Publishing

Multi-Task Deep Learning for Predicting Depression Severity and Treatment Response Using Synthetic Neuroimaging: A Fully Controlled Simulation Framework ()

Major Depressive Disorder (MDD) remains a complex and debilitating psychiatric condition characterized by heterogeneous symptom profiles and substantial variability in treatment response. Despite ...