Clayton Scott
Clayton Scott
Professor of Electrical Engineering and Computer Science, University of Michigan
כתובת אימייל מאומתת בדומיין - דף הבית
צוטט על ידי
צוטט על ידי
Robust kernel density estimation
JS Kim, CD Scott
The Journal of Machine Learning Research 13 (1), 2529-2565, 2012
Semi-supervised novelty detection
G Blanchard, G Lee, C Scott
The Journal of Machine Learning Research 11, 2973-3009, 2010
A Neyman-Pearson approach to statistical learning
C Scott, R Nowak
IEEE Transactions on Information Theory 51 (11), 3806-3819, 2005
Learning minimum volume sets
CD Scott, RD Nowak
The Journal of Machine Learning Research 7, 665-704, 2006
Classification with asymmetric label noise: Consistency and maximal denoising
C Scott, G Blanchard, G Handy
Conference on learning theory, 489-511, 2013
Minimax-optimal classification with dyadic decision trees
C Scott, RD Nowak
IEEE transactions on information theory 52 (4), 1335-1353, 2006
Generalizing from several related classification tasks to a new unlabeled sample
G Blanchard, G Lee, C Scott
Advances in neural information processing systems 24, 2178-2186, 2011
EM algorithms for multivariate Gaussian mixture models with truncated and censored data
G Lee, C Scott
Computational Statistics & Data Analysis 56 (9), 2816-2829, 2012
Mean values of Dedekind sums
JB Conrey, E Fransen, R Klein, C Scott
arXiv preprint math/9410212, 1994
Robust contour matching via the order-preserving assignment problem
C Scott, R Nowak
IEEE Transactions on Image Processing 15 (7), 1831-1838, 2006
Mixture proportion estimation via kernel embeddings of distributions
H Ramaswamy, C Scott, A Tewari
International conference on machine learning, 2052-2060, 2016
A rate of convergence for mixture proportion estimation, with application to learning from noisy labels
C Scott
Artificial Intelligence and Statistics, 838-846, 2015
Distributed spatial anomaly detection
P Chhabra, C Scott, ED Kolaczyk, M Crovella
IEEE INFOCOM 2008-The 27th Conference on Computer Communications, 1705-1713, 2008
Performance measures for Neyman–Pearson classification
C Scott
IEEE Transactions on Information Theory 53 (8), 2852-2863, 2007
Tuning support vector machines for minimax and Neyman-Pearson classification
MA Davenport, RG Baraniuk, CD Scott
IEEE transactions on pattern analysis and machine intelligence 32 (10), 1888 …, 2010
Adaptive hausdorff estimation of density level sets
A Singh, C Scott, R Nowak
The Annals of Statistics 37 (5B), 2760-2782, 2009
Calibrated asymmetric surrogate losses
C Scott
Electronic Journal of Statistics 6, 958-992, 2012
Novelty detection: Unlabeled data definitely help
C Scott, G Blanchard
Artificial intelligence and statistics, 464-471, 2009
Controlling false alarms with support vector machines
MA Davenport, RG Baraniuk, CD Scott
2006 IEEE International Conference on Acoustics Speech and Signal Processing …, 2006
The value of defibrillator electrograms for recognition of clinical ventricular tachycardias and for pace mapping of post-infarction ventricular tachycardia
K Yoshida, TY Liu, C Scott, A Hero, M Yokokawa, S Gupta, E Good, ...
Journal of the American College of Cardiology 56 (12), 969-979, 2010
המערכת אינה יכולה לבצע את הפעולה כעת. נסה שוב מאוחר יותר.
מאמרים 1–20