Detecting Particles in Cryo-EM Micrographs using Learned Features Satya P. Mallick1 Yuanxin Zhu2

First Page		Document Content
Artificial intelligence Ensemble learning Learning Machine learning Statistical classification Cascading classifiers AdaBoost Boosting Face recognition Classifier Supervised learning Linear discriminant analysis		Detecting Particles in Cryo-EM Micrographs using Learned Features Satya P. Mallick1 Yuanxin Zhu2 Add to Reading List Source URL: vision.ucsd.edu Download Document from Source Website File Size: 478,17 KB Share Document on Facebook

	Estimating the strength of unlabeled information during semi-supervised learning Brenden M. Lake () Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology James L. McClelland (m DocID: 1xVKT - View Document
	Natural Language to Structured Query Generation via Meta-Learning Po-Sen Huang 1 Chenglong Wang 2 Rishabh Singh 3 * Wen-tau Yih 4 Xiaodong He 5 * 1. Introduction Conventional supervised training is a pervasive paradigm DocID: 1xUL3 - View Document
	MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Semi-Supervised Transfer Learning Using Marginal Predictors Deshmukh, A.; Laftchiev, E. DocID: 1vqKH - View Document
	Weakly-Supervised Grammar-Informed Bayesian CCG Parser Learning Dan Garrette Chris Dyer Jason Baldridge DocID: 1vlce - View Document
	Online Semi-Supervised Learning on Quantized Graphs Michal Valko Branislav Kveton Computer Science Department Intel Labs DocID: 1vkLD - View Document