Bill G. Horne - researchr alias

researchr

You are not signed in
Sign in
Sign up

Viewing Publication 1 - 34 from 34

2016

Trust Me. Trust Me NotBill G. Horne. ieeesp, 14(3):3-5, 2016. [doi]

2015

Umbrellas and OctopusesBill G. Horne. ieeesp, 13(1):3-5, 2015. [doi]

2014

Humans in the LoopBill G. Horne. ieeesp, 12(1):3-4, 2014. [doi]

On Computer Security Incident Response TeamsBill G. Horne. ieeesp, 12(5):13-15, 2014. [doi]

2013

Guest Editorial: Special issue on privacy and trust management in cloud and distributed systemsSen-ching Samson Cheung, Yan Sun, Karl Aberer, Jayant R. Haritsa, Bill G. Horne, Kai Hwang. tifs, 8(6):835-837, 2013. [doi]

2003

If Piracy Is the Problem, Is DRM the Answer?Stuart Haber, Bill G. Horne, Joe Pato, Tomas Sander, Robert Endre Tarjan. drm 2003: 224-233 [doi]

2001

Dynamic Self-Checking Techniques for Improved Tamper ResistanceBill G. Horne, Lesley R. Matheson, Casey Sheehan, Robert Endre Tarjan. ccs 2002: 141-159 [doi]

Escrow services and incentives in peer-to-peer networksBill G. Horne, Benny Pinkas, Tomas Sander. sigecom 2001: 85-94 [doi]

Attractive Periodic Sets in Discrete-Time Recurrent Networks (with Emphasis on Fixed-Point Stability and Bifurcations in Two-Neuron Networks)Peter Tiño, Bill G. Horne, C. Lee Giles. neco, 13(6):1379-1414, 2001.

2000

Computational complexity of determining resource loops in re-entrant flow linesFrank L. Lewis, Bill G. Horne, Chaouki T. Abdallah. tsmc, 30(2):222-229, 2000.

1999

Alternative discrete-time operators: an algorithm for optimal selection of parametersAndrew D. Back, Bill G. Horne, Ah Chung Tsoi, C. Lee Giles. tsp, 47(9):2612-2615, 1999. [doi]

1998

Efficient algorithms for function approximation with piecewise linear sigmoidal networksDon R. Hush, Bill G. Horne. tnn, 9(6):1129-1141, 1998. [doi]

How embedded memory in recurrent neural network architectures helps learning long-term temporal dependenciesTsungnan Lin, Bill G. Horne, C. Lee Giles. NN, 11(5):861-868, 1998. [doi]

1997

1996

1995

Learning a class of large finite state machines with a recurrent neural networkC. Lee Giles, Bill G. Horne, Tsungnan Lin. NN, 8(9):1359-1365, 1995. [doi]

What NARX Networks Can ComputeBill G. Horne, Hava T. Siegelmann, C. Lee Giles. sofsem 1995: 95-102

Learning long-term dependencies is not as difficult with NARX networksTsungnan Lin, Bill G. Horne, Peter Tiño, C. Lee Giles. nips 1996: 577-583 [doi]

1994

1993

Bounds on the Complexity of Recurrent Neural Network Implementations of Finite State MachinesBill G. Horne, Don R. Hush. nips 1994: 359-366 [doi]

Progress in supervised neural networksDon R. Hush, Bill G. Horne. spm, 10(1):8-39, 1993. [doi]

1992

Error surfaces for multilayer perceptronsDon R. Hush, Bill G. Horne, John M. Salas. tsmc, 22(5):1152-1161, 1992. [doi]

1990

Estimating a posteriori probability with P-type nodesBill G. Horne, Don R. Hush. ijcnn 1990: 691-696 [doi]

All Publications

Filter by Year
OR AND NOT 1

Filter by Type
OR AND NOT 1

Filter by Tag
OR AND NOT 1

Filter by Venue
OR AND NOT 1

Filter by Author

[+]
OR AND NOT 1

Filter by Top Terms

[+]
OR AND NOT 1

Researchr

Publications by 'Bill G. Horne'

Viewing Publication 1 - 34 from 34

2016

2015

2014

2013

2003

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1990

All Publications

Filter by YearOR AND NOT 1

Filter by TypeOR AND NOT 1

Filter by TagOR AND NOT 1

Filter by VenueOR AND NOT 1

Filter by Author [+]OR AND NOT 1

Filter by Top Terms [+]OR AND NOT 1

Researchr

Publications by 'Bill G. Horne'

Viewing Publication 1 - 34 from 34

2016

2015

2014

2013

2003

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1990

Filter by Year
OR AND NOT 1

Filter by Type
OR AND NOT 1

Filter by Tag
OR AND NOT 1

Filter by Venue
OR AND NOT 1

Filter by Author

[+]
OR AND NOT 1

Filter by Top Terms

[+]
OR AND NOT 1