Bill G. Horne

William G. Horne

Hewlett-Packard Laboratories, Princeton, NJ, USA

	2011
c16		Sandeep Bhatt, William G. Horne, Prasad Rao: On Computing Enterprise IT Risk Metrics. SEC 2011: 271-280
	2009
c15		Brian Thompson, Stuart Haber, William G. Horne, Tomas Sander, Danfeng Yao: Privacy-Preserving Computation and Verification of Aggregate Queries on Outsourced Databases. Privacy Enhancing Technologies 2009: 185-201
	2008
c14		Stuart Haber, Yasuo Hatano, Yoshinori Honda, William G. Horne, Kunihiko Miyazaki, Tomas Sander, Satoru Tezoku, Danfeng Yao: Efficient signature schemes supporting redaction, pseudonymization, and data deidentification. ASIACCS 2008: 353-362
c13		Alina Ene, William G. Horne, Nikola Milosavljevic, Prasad Rao, Robert Schreiber, Robert Endre Tarjan: Fast exact and heuristic methods for role minimization problems. SACMAT 2008: 1-10
	2003
c12		Stuart Haber, Bill G. Horne, Joe Pato, Tomas Sander, Robert Endre Tarjan: If Piracy Is the Problem, Is DRM the Answer? Digital Rights Management 2003: 224-233
	2001
j14		Peter Tiño, Bill G. Horne, C. Lee Giles: Attractive Periodic Sets in Discrete-Time Recurrent Networks (with Emphasis on Fixed-Point Stability and Bifurcations in Two-Neuron Networks). Neural Computation 13(6): 1379-1414 (2001)
c11		Bill G. Horne, Lesley R. Matheson, Casey Sheehan, Robert Endre Tarjan: Dynamic Self-Checking Techniques for Improved Tamper Resistance. Digital Rights Management Workshop 2001: 141-159
c10		Bill G. Horne, Benny Pinkas, Tomas Sander: Escrow services and incentives in peer-to-peer networks. ACM Conference on Electronic Commerce 2001: 85-94
	2000
j13		Frank L. Lewis, Bill G. Horne, Chaouki T. Abdallah: Computational complexity of determining resource loops in re-entrant flow lines. IEEE Transactions on Systems, Man, and Cybernetics, Part A 30(2): 222-229 (2000)
	1998
j12		Tsungnan Lin, Bill G. Horne, C. Lee Giles: How embedded memory in recurrent neural network architectures helps learning long-term temporal dependencies. Neural Networks 11(5): 861-868 (1998)
j11		Don R. Hush, Bill G. Horne: Efficient algorithms for function approximation with piecewise linear sigmoidal networks. IEEE Transactions on Neural Networks 9(6): 1129-1141 (1998)
	1997
j10		Daniel S. Clouse, C. Lee Giles, Bill G. Horne, Garrison W. Cottrell: Time-delay neural networks: representation and induction of finite-state machines. IEEE Trans. Neural Netw. Learning Syst. 8(5): 1065-1070 (1997)
j9		Hava T. Siegelmann, Bill G. Horne, C. Lee Giles: Computational capabilities of recurrent NARX neural networks. IEEE Transactions on Systems, Man, and Cybernetics, Part B 27(2): 208-215 (1997)
j8		Tsung-Nan Lin, C. Lee Giles, Bill G. Horne, Sun-Yuan Kung: A delay damage model selection algorithm for NARX neural networks. IEEE Transactions on Signal Processing 45(11): 2719-2730 (1997)
c9		M. F. Sakr, Steven P. Levitan, Donald M. Chiarulli, Bill G. Horne, C. Lee Giles: Predicting Multiprocessor Memory Access Patterns with Learning Models. ICML 1997: 305-312
c8		Don R. Hush, Fernando Lozano, Bill G. Horne: Function Approximation with the Sweeping Hinge Algorithm. NIPS 1997
	1996
j7		Bill G. Horne, Don R. Hush: Bounds on the complexity of recurrent neural network implementations of finite state machines. Neural Networks 9(2): 243-252 (1996)
j6		Tsungnan Lin, Bill G. Horne, Peter Tino, C. Lee Giles: Learning long-term dependencies in NARX recurrent neural networks. IEEE Trans. Neural Netw. Learning Syst. 7(6): 1329-1338 (1996)
j5		Kam-Chuen Jim, C. Lee Giles, Bill G. Horne: An analysis of noise in recurrent neural networks: convergence and generalization. IEEE Trans. Neural Netw. Learning Syst. 7(6): 1424-1438 (1996)
c7		Daniel S. Clouse, C. Lee Giles, Bill G. Horne, Garrison W. Cottrell: Representation and Induction of Finite State Machines using Time-Delay Neural Networks. NIPS 1996: 403-409
	1995
j4		C. Lee Giles, Bill G. Horne, Tsungnan Lin: Learning a class of large finite state machines with a recurrent neural network. Neural Networks 8(9): 1359-1365 (1995)
c6		Tsungnan Lin, Bill G. Horne, Peter Tiño, C. Lee Giles: Learning long-term dependencies is not as difficult with NARX networks. NIPS 1995: 577-583
c5		Bill G. Horne, Hava T. Siegelmann, C. Lee Giles: What NARX Networks Can Compute. SOFSEM 1995: 95-102
	1994
j3		Bill G. Horne, Don R. Hush: On the node complexity of neural networks. Neural Networks 7(9): 1413-1426 (1994)
c4		Laurens R. Leerink, C. Lee Giles, Bill G. Horne, Marwan A. Jabri: Learning with Product Units. NIPS 1994: 537-544
c3		Kam-Chuen Jim, Bill G. Horne, C. Lee Giles: Effects of Noise on Convergence and Generalization in Recurrent Networks. NIPS 1994: 649-656
c2		Bill G. Horne, C. Lee Giles: An experimental comparison of recurrent neural networks. NIPS 1994: 697-704
	1993
c1		Bill G. Horne, Don R. Hush: Bounds on the Complexity of Recurrent Neural Network Implementations of Finite State Machines. NIPS 1993: 359-366
	1992
j2		Don R. Hush, Bill G. Horne, John M. Salas: Error surfaces for multilayer perceptrons. IEEE Transactions on Systems, Man, and Cybernetics 22(5): 1152-1161 (1992)
	1990
j1		Bill G. Horne, Mohammad Jamshidi, Nader Vadiee: Neural networks in robotics: A survey. Journal of Intelligent and Robotic Systems 3(1): 51-66 (1990)

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