219 citations · 261 across the 15 of their papers we have counts for
15 papers
Hierarchical Channel Stacking: A Structured Decision Framework for AI-Generated Image Detection
Saifullah Shoaib, Akash Borigi, Rupendra Lekkala +5
Many synthetic-image detectors produce accurate predictions but offer limited insight into how those decisions are formed. This paper introduces Hierarchical Channel Stacking (HCS)…
Extreme AutoML: Analysis of Classification, Regression, and NLP Performance
Edward Ratner, Elliot Farmer, Brandon Warner +2
Utilizing machine learning techniques has always required choosing hyperparameters. This is true whether one uses a classical technique such as a KNN or very modern neural networks…
Mislabel Detection of Finnish Publication Ranks
Anton Akusok, Mirka Saarela, Tommi Kärkkäinen +2
The paper proposes to analyze a data set of Finnish ranks of academic publication channels with Extreme Learning Machine (ELM). The purpose is to introduce and test recently propos…
Per-sample Prediction Intervals for Extreme Learning Machines
Anton Akusok, Yoan Miche, Kaj-Mikael Björk +1
Prediction intervals in supervised Machine Learning bound the region where the true outputs of new samples may fall. They are necessary in the task of separating reliable predictio…
Extreme Learning Tree
Anton Akusok, Emil Eirola, Kaj-Mikael Björk +1
The paper proposes a new variant of a decision tree, called an Extreme Learning Tree. It consists of an extremely random tree with non-linear data transformation, and a linear obse…
Spiking Networks for Improved Cognitive Abilities of Edge Computing Devices
Anton Akusok, Kaj-Mikael Björk, Leonardo Espinosa Leal +3
This concept paper highlights a recently opened opportunity for large scale analytical algorithms to be trained directly on edge devices. Such approach is a response to the arising…