Don R. Hush - RankMe

57 papers A* 4B 2C 5Misc 5Journal 29Unranked 12

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Characterizing Extra Credit Accumulation by Undergraduate Students. IEEE Access Tushar Ojha, Don R. Hush
2025	J	`jnl`	Finding Interpretable Data Pockets in Tabular Data. Stat. Comput. Tushar Ojha, Don R. Hush
2021	C	`conf`	Maximizing University Enrollment Using Institutional-Based Aid Scholarship. ICMLA Ahmad Slim, Don R. Hush, Tushar Ojha, Georges El-Howayek, Chaouki T. Abdallah, Terry Babbitt
2019	—	`conf`	An Automated Framework to Recommend A Suitable Academic Program, Course and Instructor. BigDataService Ahmad Slim, Don R. Hush, Tushar Ojha, Chaouki T. Abdallah, Gregory L. Heileman, Georges El-Howayek
2018	B	`conf`	Predicting Student Enrollment based on Student and College Characteristics. EDM Ahmad Slim, Don R. Hush, Tushar Ojha, Terry Babbitt
2013	J	`jnl`	Interactive Machine Learning in Data Exploitation. Comput. Sci. Eng. Reid B. Porter, James Theiler, Don R. Hush
2012	J	`jnl`	Ordered Hypothesis Machines. J. Math. Imaging Vis. G. Beate Zimmer, Don R. Hush, Reid B. Porter
2011	—	`conf`	A comparison of methods for estimating broadband noise in the frequency domain. ACSCC Don R. Hush, Norma H. Pawley, Kary L. Myers, Bob Nemzek
2011	—	`conf`	Error minimizing algorithms for nearest neighbor classifiers. Image Processing: Algorithms and Systems Reid B. Porter, Don R. Hush, G. Beate Zimmer
2011	—	`conf`	Interactive image quantification tools in nuclear material forensics. Image Processing: Machine Vision Applications Reid B. Porter, Christy Ruggiero, Don R. Hush, Neal R. Harvey, Patrick Kelly, Wayne Scoggins, Lav Tandon
2011	—	`conf`	Learning from Only Positive and Unlabeled Data to Detect Lesions in Vascular CT Images. MICCAI (3) Maria A. Zuluaga, Don R. Hush, Edgar J. F. Delgado Leyton, Marcela Hernández Hoyos, Maciej Orkisz
2011	J	`jnl`	Training SVMs Without Offset. J. Mach. Learn. Res. Ingo Steinwart, Don R. Hush, Clint Scovel
2010	J	`jnl`	Algorithms for optimal dyadic decision trees. Mach. Learn. Don R. Hush, Reid B. Porter
2010	J	`jnl`	Radial kernels and their reproducing kernel Hilbert spaces. J. Complex. Clint Scovel, Don R. Hush, Ingo Steinwart, James Theiler
2010	C	`conf`	Statistics for characterizing data on the periphery. IGARSS James Theiler, Don R. Hush
2010	J	`jnl`	Wide-Area Motion Imagery. IEEE Signal Process. Mag. Reid B. Porter, Andrew M. Fraser, Don R. Hush
2009	J	`jnl`	Learning from dependent observations. J. Multivar. Anal. Ingo Steinwart, Don R. Hush, Clint Scovel
2009	A*	`conf`	Optimal Rates for Regularized Least Squares Regression. COLT Ingo Steinwart, Don R. Hush, Clint Scovel
2009	C	`conf`	Stack Filter Classifiers. ISMM Reid B. Porter, G. Beate Zimmer, Don R. Hush
2007	A*	`conf`	Gaps in Support Vector Optimization. COLT Nikolas List, Don R. Hush, Clint Scovel, Ingo Steinwart
2007	J	`jnl`	Stability of Unstable Learning Algorithms. Mach. Learn. Don R. Hush, Clint Scovel, Ingo Steinwart
2006	J	`jnl`	An Explicit Description of the Reproducing Kernel Hilbert Spaces of Gaussian RBF Kernels. IEEE Trans. Inf. Theory Ingo Steinwart, Don R. Hush, Clint Scovel
2006	—	`conf`	An Oracle Inequality for Clipped Regularized Risk Minimizers. NIPS Ingo Steinwart, Don R. Hush, Clint Scovel
2006	A*	`conf`	Function Classes That Approximate the Bayes Risk. COLT Ingo Steinwart, Don R. Hush, Clint Scovel
2006	J	`jnl`	QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines. J. Mach. Learn. Res. Don R. Hush, Patrick Kelly, Clint Scovel, Ingo Steinwart
2005	J	`jnl`	A Classification Framework for Anomaly Detection. J. Mach. Learn. Res. Ingo Steinwart, Don R. Hush, Clint Scovel
2004	—	`conf`	Density Level Detection is Classification. NIPS Ingo Steinwart, Don R. Hush, Clint Scovel
2004	J	`jnl`	Fat-Shattering of Affine Functions. Comb. Probab. Comput. Don R. Hush, Clint Scovel
2004	C	`conf`	Multiple instance learning using simple classifiers. ICMLA Adam Cannon, Don R. Hush
2003	J	`jnl`	Polynomial-Time Decomposition Algorithms for Support Vector Machines. Mach. Learn. Don R. Hush, Clint Scovel
2003	J	`jnl`	Selecting a restoration technique to minimize OCR error. IEEE Trans. Neural Networks Mike Cannon, Mike Fugate, Don R. Hush, Clint Scovel
2003	A*	`conf`	Weighted Order Statistic Classifiers with Large Rank-Order Margin. ICML Reid B. Porter, Damian Eads, Don R. Hush, James Theiler
2002	J	`jnl`	Machine Learning with Data Dependent Hypothesis Classes. J. Mach. Learn. Res. Adam Cannon, J. Mark Ettinger, Don R. Hush, Clint Scovel
2001	J	`jnl`	On the VC Dimension of Bounded Margin Classifiers. Mach. Learn. Don R. Hush, Clint Scovel
2001	C	`conf`	Product property monitoring for a batch polymerization reaction system. ACC Kenneth R. Muske, James W. Howse, Don R. Hush
1999	J	`jnl`	Training a Sigmoidal Node Is Hard. Neural Comput. Don R. Hush
1998	J	`jnl`	A Constructive Neural Network Algorithm for Function Approximation Using Locally Fit Sigmoids. Int. J. Artif. Intell. Tools Tim Draelos, Don R. Hush
1998	J	`jnl`	Efficient algorithms for function approximation with piecewise linear sigmoidal networks. IEEE Trans. Neural Networks Don R. Hush, Bill G. Horne
1998	J	`jnl`	Nonlinear Signal-Processing Methods. IEEE Signal Process. Mag. Don R. Hush
1997	—	`conf`	Function Approximation with the Sweeping Hinge Algorithm. NIPS Don R. Hush, Fernando Lozano, Bill G. Horne
1997	Misc	`conf`	Interactive DSP course development/teaching environment. ICASSP 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
1996	—	`conf`	A constructive neural network algorithm for function approximation. ICNN Tim Draelos, Don R. Hush
1996	J	`jnl`	Bounds on the complexity of recurrent neural network implementations of finite state machines. Neural Networks Bill G. Horne, Don R. Hush
1996	J	`jnl`	Network constraints and multi-objective optimization for one-class classification. Neural Networks Mary M. Moya, Don R. Hush
1995	—	`conf`	Query by Image Example: The Comparison Algorithm for Navigating Digital Image Databases (CANDID) Approach. Storage and Retrieval for Image and Video Databases (SPIE) Patrick M. Kelly, T. Michael Cannon, Don R. Hush
1994	J	`jnl`	On the node complexity of neural networks. Neural Networks Bill G. Horne, Don R. Hush
1993	—	`conf`	Bounds on the Complexity of Recurrent Neural Network Implementations of Finite State Machines. NIPS Bill G. Horne, Don R. Hush
1993	J	`jnl`	Progress in supervised neural networks. IEEE Signal Process. Mag. Don R. Hush, Bill G. Horne
1992	J	`jnl`	Error surfaces for multilayer perceptrons. IEEE Trans. Syst. Man Cybern. Don R. Hush, Bill G. Horne, John M. Salas
1990	B	`conf`	Estimating a posteriori probability with P-type nodes. IJCNN Bill G. Horne, Don R. Hush
1990	Misc	`conf`	Statistical analysis of a change detector based on image modeling of difference picture. ICASSP Daechul Park, Don R. Hush
1988	Misc	`conf`	Change detection for target detection and classification in video sequences. ICASSP Gregory W. Donohoe, Don R. Hush, Nasir Ahmed
1988	—	`conf`	Improving the learning rate of back-propagation with the gradient reuse algorithm. ICNN Don R. Hush, John M. Salas
1987	J	`jnl`	A new technique for adaptive frequency estimation and tracking. IEEE Trans. Acoust. Speech Signal Process. Delores M. Etter, Don R. Hush
1986	J	`jnl`	An adaptive IIR structure for sinusoidal enhancement, frequency estimation, and detection. IEEE Trans. Acoust. Speech Signal Process. Don R. Hush, Nasir Ahmed, Ruth David, Samuel D. Stearns
1985	Misc	`conf`	Detection and identification of sinusoids in broadband noise via a parallel recursive ALE. ICASSP Don R. Hush, Nasir Ahmed
1984	Misc	`conf`	Detection of multiple sinusoids using an adaptive cascaded structure. ICASSP Nasir Ahmed, Don R. Hush, G. R. Elliott, R. Joseph Fogler