Abstract: An automated, robust, noncontact sleep posture recognition technique is proposed in this letter, which uses optimizable (Bayesian hyperparameter tuning) machine learning (ML) classifiers ...
Abstract: Software testing is a crucial activity during software development and fault prediction models assist practitioners herein by providing an upfront identification of faulty software code by ...
Many scientific problems entail labeling data items with one of a given, finite set of classes based on features of the data items. For example, oncologists classify tumors as different known cancer ...
Buy-in-Bulk Active Learning. Liu Yang and Jaime Carbonell. Advances in Neural Information Processing Systems 26 (NIPS), 2013. Liu Yang, Avrim Blum and Jaime Carbonell. Learnability of DNF with ...
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Machine learning models in this domain often operate in low-data regimes, with training set sizes as low as 20 and a median dataset size of around 600 records—conditions that hinder model ...
This limitation motivates the Bayesian framework developed in the present study. Hybrid approaches that combine statistical ranking methods with machine learning have also gained traction. Groll et al ...
Certification of Machine Learning Models via Directional Sharpness Gefei Tan, Adria Gascon, Sarah Meiklejohn, Mariana Raykova Speculative Decoding at Temperature Zero: A Scoped Safety-Invariance ...
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