Don R. Hush

Publication Activity (10 Years)

Years Active: 1984-2021
Publications (10 Years): 3

Top Topics

Computer Science And Engineering

Educational Environment

Tutoring System

Top Venues

Comput. Sci. Eng.

Publications

Ahmad Slim, Don R. Hush, Tushar Ojha, Georges El-Howayek, Chaouki T. Abdallah, Terry Babbitt
Maximizing University Enrollment Using Institutional-Based Aid Scholarship. ICMLA (2021)
Ahmad Slim, Don R. Hush, Tushar Ojha, Chaouki T. Abdallah, Gregory L. Heileman, Georges El-Howayek
An Automated Framework to Recommend A Suitable Academic Program, Course and Instructor. BigDataService (2019)
Ahmad Slim, Don R. Hush, Tushar Ojha, Terry Babbitt
Predicting Student Enrollment based on Student and College Characteristics. EDM (2018)
Reid B. Porter, James Theiler, Don R. Hush
Interactive Machine Learning in Data Exploitation. Comput. Sci. Eng. 15 (5) (2013)
G. Beate Zimmer, Don R. Hush, Reid B. Porter
Ordered Hypothesis Machines. J. Math. Imaging Vis. 43 (2) (2012)
Don R. Hush, Norma H. Pawley, Kary L. Myers, Bob Nemzek
A comparison of methods for estimating broadband noise in the frequency domain. ACSCC (2011)
Reid B. Porter, Don R. Hush, G. Beate Zimmer
Error minimizing algorithms for nearest neighbor classifiers. Image Processing: Algorithms and Systems (2011)
Ingo Steinwart, Don R. Hush, Clint Scovel
Training SVMs Without Offset. J. Mach. Learn. Res. 12 (2011)
Reid B. Porter, Christy Ruggiero, Don R. Hush, Neal R. Harvey, Patrick Kelly, Wayne Scoggins, Lav Tandon
Interactive image quantification tools in nuclear material forensics. Image Processing: Machine Vision Applications (2011)
Maria A. Zuluaga, Don R. Hush, Edgar J. F. Delgado Leyton, Marcela Hernández Hoyos, Maciej Orkisz
Learning from Only Positive and Unlabeled Data to Detect Lesions in Vascular CT Images. MICCAI (3) (2011)
Reid B. Porter, Andrew M. Fraser, Don R. Hush
Wide-Area Motion Imagery. IEEE Signal Process. Mag. 27 (5) (2010)
Clint Scovel, Don R. Hush, Ingo Steinwart, James Theiler
Radial kernels and their reproducing kernel Hilbert spaces. J. Complex. 26 (6) (2010)
James Theiler, Don R. Hush
Statistics for characterizing data on the periphery. IGARSS (2010)
Don R. Hush, Reid B. Porter
Algorithms for optimal dyadic decision trees. Mach. Learn. 80 (1) (2010)
Ingo Steinwart, Don R. Hush, Clint Scovel
Learning from dependent observations. J. Multivar. Anal. 100 (1) (2009)
Ingo Steinwart, Don R. Hush, Clint Scovel
Optimal Rates for Regularized Least Squares Regression. COLT (2009)
Reid B. Porter, G. Beate Zimmer, Don R. Hush
Stack Filter Classifiers. ISMM (2009)
Nikolas List, Don R. Hush, Clint Scovel, Ingo Steinwart
Gaps in Support Vector Optimization. COLT (2007)
Don R. Hush, Clint Scovel, Ingo Steinwart
Stability of Unstable Learning Algorithms. Mach. Learn. 67 (3) (2007)
Ingo Steinwart, Don R. Hush, Clint Scovel
An Oracle Inequality for Clipped Regularized Risk Minimizers. NIPS (2006)
Ingo Steinwart, Don R. Hush, Clint Scovel
An Explicit Description of the Reproducing Kernel Hilbert Spaces of Gaussian RBF Kernels. IEEE Trans. Inf. Theory 52 (10) (2006)
Don R. Hush, Patrick Kelly, Clint Scovel, Ingo Steinwart
QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines. J. Mach. Learn. Res. 7 (2006)
Ingo Steinwart, Don R. Hush, Clint Scovel
Function Classes That Approximate the Bayes Risk. COLT (2006)
Ingo Steinwart, Don R. Hush, Clint Scovel
A Classification Framework for Anomaly Detection. J. Mach. Learn. Res. 6 (2005)
Don R. Hush, Clint Scovel
Fat-Shattering of Affine Functions. Comb. Probab. Comput. 13 (3) (2004)
Ingo Steinwart, Don R. Hush, Clint Scovel
Density Level Detection is Classification. NIPS (2004)
Adam Cannon, Don R. Hush
Multiple instance learning using simple classifiers. ICMLA (2004)
Mike Cannon, Mike Fugate, Don R. Hush, Clint Scovel
Selecting a restoration technique to minimize OCR error. IEEE Trans. Neural Networks 14 (3) (2003)
Don R. Hush, Clint Scovel
Polynomial-Time Decomposition Algorithms for Support Vector Machines. Mach. Learn. 51 (1) (2003)
Reid B. Porter, Damian Eads, Don R. Hush, James Theiler
Weighted Order Statistic Classifiers with Large Rank-Order Margin. ICML (2003)
Adam Cannon, J. Mark Ettinger, Don R. Hush, Clint Scovel
Machine Learning with Data Dependent Hypothesis Classes. J. Mach. Learn. Res. 2 (2002)
Don R. Hush, Clint Scovel
On the VC Dimension of Bounded Margin Classifiers. Mach. Learn. 45 (1) (2001)
Kenneth R. Muske, James W. Howse, Don R. Hush
Product property monitoring for a batch polymerization reaction system. ACC (2001)
Don R. Hush
Training a Sigmoidal Node Is Hard. Neural Comput. 11 (5) (1999)
Don R. Hush, Bill G. Horne
Efficient algorithms for function approximation with piecewise linear sigmoidal networks. IEEE Trans. Neural Networks 9 (6) (1998)
Tim Draelos, Don R. Hush
A Constructive Neural Network Algorithm for Function Approximation Using Locally Fit Sigmoids. Int. J. Artif. Intell. Tools 7 (2) (1998)
Don R. Hush, Fernando Lozano, Bill G. Horne
Function Approximation with the Sweeping Hinge Algorithm. NIPS (1997)
Chaouki T. Abdallah, Dalton Soares Arantes, Gregory L. Heileman, Don R. Hush, Ramiro Jordan, Roberto de Alencar Lotufo, Neeraj Magotra, L. Howard Pollard, Edl Schamiloglu, Robert Whitman
Interactive DSP course development/teaching environment. ICASSP (1997)
Bill G. Horne, Don R. Hush
Bounds on the complexity of recurrent neural network implementations of finite state machines. Neural Networks 9 (2) (1996)
Tim Draelos, Don R. Hush
A constructive neural network algorithm for function approximation. ICNN (1996)
Mary M. Moya, Don R. Hush
Network constraints and multi-objective optimization for one-class classification. Neural Networks 9 (3) (1996)
Patrick M. Kelly, T. Michael Cannon, Don R. Hush
Query by Image Example: The Comparison Algorithm for Navigating Digital Image Databases (CANDID) Approach. Storage and Retrieval for Image and Video Databases (SPIE) (1995)
Bill G. Horne, Don R. Hush
On the node complexity of neural networks. Neural Networks 7 (9) (1994)
Bill G. Horne, Don R. Hush
Bounds on the Complexity of Recurrent Neural Network Implementations of Finite State Machines. NIPS (1993)
Don R. Hush, Bill G. Horne
Progress in supervised neural networks. IEEE Signal Process. Mag. 10 (1) (1993)
Don R. Hush, Bill G. Horne, John M. Salas
Error surfaces for multilayer perceptrons. IEEE Trans. Syst. Man Cybern. 22 (5) (1992)
Daechul Park, Don R. Hush
Statistical analysis of a change detector based on image modeling of difference picture. ICASSP (1990)
Bill G. Horne, Don R. Hush
Estimating a posteriori probability with P-type nodes. IJCNN (1990)
Don R. Hush, John M. Salas
Improving the learning rate of back-propagation with the gradient reuse algorithm. ICNN (1988)
Gregory W. Donohoe, Don R. Hush, Nasir Ahmed
Change detection for target detection and classification in video sequences. ICASSP (1988)
Delores M. Etter, Don R. Hush
A new technique for adaptive frequency estimation and tracking. IEEE Trans. Acoust. Speech Signal Process. 35 (4) (1987)
Don R. Hush, Nasir Ahmed, Ruth David, Samuel D. Stearns
An adaptive IIR structure for sinusoidal enhancement, frequency estimation, and detection. IEEE Trans. Acoust. Speech Signal Process. 34 (6) (1986)
Don R. Hush, Nasir Ahmed
Detection and identification of sinusoids in broadband noise via a parallel recursive ALE. ICASSP (1985)
Nasir Ahmed, Don R. Hush, G. R. Elliott, R. Fogler
Detection of multiple sinusoids using an adaptive cascaded structure. ICASSP (1984)