Search Results for author:
Found 5 papers, 2 papers with code
Deep Learning in Target Space
Experimental results show the speed of using target space, and examples of improved generalisation, for fully-connected networks and convolutional networks, and the ability to recall and process long time sequences and perform natural-language processing with recurrent networks.
Effect of data leakage in brain MRI classification using 2D convolutional neural networks
In this study, we quantitatively assessed the effect of a data leakage caused by 3D MRI data splitting based on a 2D slice-level using three 2D CNN models to classify patients with Alzheimer’s disease (AD) and Parkinson’s disease (PD).
A simple yet efficient algorithm for multiple kernel learning under elastic-net constraints
This papers introduces an algorithm for the solution of multiple kernel learning (MKL) problems with elastic-net constraints on the kernel weights.
Domain Adaptation for Deep Reinforcement Learning in Visually Distinct Games
Many deep reinforcement learning approaches use graphical state representations, this means visually distinct games that share the same underlying structure cannot effectively share knowledge.
A Real-Time Automated Point-Process Method for the Detection and Correction of Erroneous and Ectopic Heartbeats
Our automated algorithm represents an improvement over previous procedures, with best specificity for the detection of correct beats, as well as highest sensitivity to missed and extra beats, artificially misplaced beats, and for real arrhythmic events.
