Labels in a haystack: Approaches beyond supervised learning in biomedical applications
Open Access
Abstract
No abstract availableKeywords
This publication has 61 references indexed in Scilit:
- Low Data Drug Discovery with One-Shot LearningACS Central Science, 2017
- Continuous Distributed Representation of Biological Sequences for Deep Proteomics and GenomicsPLOS ONE, 2015
- iDrug-Target: predicting the interactions between drug compounds and target proteins in cellular networking via benchmark dataset optimization approachJournal of Biomolecular Structure and Dynamics, 2015
- Semi-Supervised Learning (Chapelle, O. et al., Eds.; 2006) [Book reviews]IEEE Transactions on Neural Networks, 2009
- Feature Selection for Genomic Signal Processing: Unsupervised, Supervised, and Self-Supervised ScenariosJournal of Signal Processing Systems, 2008
- One-shot learning of object categoriesIEEE Transactions on Pattern Analysis and Machine Intelligence, 2006
- Semi-supervised protein classification using cluster kernelsBioinformatics, 2005
- Multi-Relational Learning, Text Mining, and Semi-Supervised Learning for Functional GenomicsMachine Learning, 2004
- Active Learning with Support Vector Machine Applied to Gene Expression Data for Cancer ClassificationJournal of Chemical Information and Computer Sciences, 2004
- Solving the multiple instance problem with axis-parallel rectanglesArtificial Intelligence, 1997