6 citations · 9 across the 3 of their papers we have counts for
4 papers · 1 filter
Looking back to lower-level information in few-shot learning
Zhongjie Yu, Sebastian Raschka
Humans are capable of learning new concepts from small numbers of examples. In contrast, supervised deep learning models usually lack the ability to extract reliable predictive rul…
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence
Sebastian Raschka, Joshua Patterson, Corey Nolet
Smarter applications are making better use of the insights gleaned from data, having an impact on every industry and research discipline. At the core of this revolution lies the to…
Rank consistent ordinal regression for neural networks with application to age estimation
Wenzhi Cao, Vahid Mirjalili, Sebastian Raschka
In many real-world prediction tasks, class labels include information about the relative ordering between labels, which is not captured by commonly-used loss functions such as mult…
Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning
Sebastian Raschka
The correct use of model evaluation, model selection, and algorithm selection techniques is vital in academic machine learning research as well as in many industrial settings. This…