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ORCIDThomas R. Hancock
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1990 – 1999
- 1998
[j9]Long-Ji Lin, Thomas R. Hancock, J. Stephen Judd:
A robust landmark-based system for vehicle location using low-bandwidth vision. Robotics Auton. Syst. 25(1-2): 19-32 (1998)- 1996
- [j8]Thomas R. Hancock, Tao Jiang, Ming Li, John Tromp:
Lower Bounds on Learning Decision Lists and Trees. Inf. Comput. 126(2): 114-122 (1996) - [j7]Nader H. Bshouty, Sally A. Goldman, Thomas R. Hancock, Sleiman Matar:
Asking Questions to Minimize Errors. J. Comput. Syst. Sci. 52(2): 268-286 (1996) - [j6]Thomas R. Hancock:
Guest Editor's Introduction. Mach. Learn. 25(2-3): 115-116 (1996) - [j5]Mostefa Golea, Mario Marchand
, Thomas R. Hancock:
On learning ?-perceptron networks on the uniform distribution. Neural Networks 9(1): 67-82 (1996) - 1995
- [j4]Nader H. Bshouty, Thomas R. Hancock, Lisa Hellerstein:
Learning Boolean Read-Once Formulas over Generalized Bases. J. Comput. Syst. Sci. 50(3): 521-542 (1995) - [j3]Nader H. Bshouty, Thomas R. Hancock, Lisa Hellerstein:
Learning Arithmetic Read-Once Formulas. SIAM J. Comput. 24(4): 706-735 (1995) - [c10]Thomas R. Hancock, Tao Jiang, Ming Li, John Tromp:
Lower Bounds on Learning Decision Lists and Trees (Extended Abstract). STACS 1995: 527-538 - 1994
- [j2]Nader H. Bshouty, Thomas R. Hancock, Lisa Hellerstein, Marek Karpinski:
An Algorithm to Learn Read-Once Threshold Formulas, and Transformations Between Learning Models. Comput. Complex. 4: 37-61 (1994) - [j1]Thomas R. Hancock, Mostefa Golea, Mario Marchand:
Learning Nonoverlapping Perceptron Networks from Examples and Membership Queries. Mach. Learn. 16(3): 161-183 (1994) - 1993
- [c9]Nader H. Bshouty, Sally A. Goldman, Thomas R. Hancock, Sleiman Matar:
Asking Questions to Minimize Errors. COLT 1993: 41-50 - [c8]Thomas R. Hancock:
Learning kµ Decision Trees on the Uniform Distribution. COLT 1993: 352-360 - 1992
- [c7]Nader H. Bshouty, Thomas R. Hancock, Lisa Hellerstein:
Learning Boolean Read-Once Formulas with Arbitrary Symmetric and Constant Fan-in Gates. COLT 1992: 1-15 - [c6]Mostefa Golea, Mario Marchand, Thomas R. Hancock:
On Learning µ-Perceptron Networks with Binary Weights. NIPS 1992: 591-598 - [c5]Nader H. Bshouty, Thomas R. Hancock, Lisa Hellerstein:
Learning Arithmetic Read-Once Formulas. STOC 1992: 370-381 - 1991
- [c4]Thomas R. Hancock, Yishay Mansour:
Learning Monotone kµ DNF Formulas on Product Distributions. COLT 1991: 179-183 - [c3]Thomas R. Hancock:
Learning 2µ DNF Formulas and kµ Decision Trees. COLT 1991: 199-209 - [c2]Thomas R. Hancock, Lisa Hellerstein:
Learning Read-Once Formulas over Fields and Extended Bases. COLT 1991: 326-336 - 1990
- [c1]Thomas R. Hancock:
Identifying µ-Formula Decision Trees with Queries. COLT 1990: 23-37
Coauthor Index
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