2009 |
22 | EE | Leen-Kiat Soh,
Ashok Samal,
Stephen D. Scott,
Stephen Ramsay,
Etsuko Moriyama,
George Meyer,
Brian Moore,
William G. Thomas,
Duane F. Shell:
Renaissance computing: an initiative for promoting student participation in computing.
SIGCSE 2009: 59-63 |
2008 |
21 | EE | Chris Bourke,
Kun Deng,
Stephen D. Scott,
Robert E. Schapire,
N. V. Vinodchandran:
On reoptimizing multi-class classifiers.
Machine Learning 71(2-3): 219-242 (2008) |
20 | EE | Qingping Tao,
Stephen D. Scott:
Improved MCMC sampling methods for estimating weighted sums in Winnow with application to DNF learning.
Machine Learning 73(2): 107-132 (2008) |
2007 |
19 | EE | Kun Deng,
Chris Bourke,
Stephen D. Scott,
Julie Sunderman,
Yaling Zheng:
Bandit-Based Algorithms for Budgeted Learning.
ICDM 2007: 463-468 |
2006 |
18 | EE | Matt Culver,
Kun Deng,
Stephen D. Scott:
Active Learning to Maximize Area Under the ROC Curve.
ICDM 2006: 149-158 |
2005 |
17 | EE | Thomas Takeo Osugi,
Kun Deng,
Stephen D. Scott:
Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning.
ICDM 2005: 330-337 |
16 | EE | Chang Wang,
Stephen D. Scott:
New kernels for protein structural motif discovery and function classification.
ICML 2005: 940-947 |
2004 |
15 | | Qingping Tao,
Stephen D. Scott:
A Faster Algorithm for Generalized Multiple-Instance Learning.
FLAIRS Conference 2004 |
14 | EE | Qingping Tao,
Stephen D. Scott,
N. V. Vinodchandran,
Thomas Takeo Osugi:
SVM-based generalized multiple-instance learning via approximate box counting.
ICML 2004 |
13 | EE | Qingping Tao,
Stephen D. Scott,
N. V. Vinodchandran,
Thomas Takeo Osugi,
Brandon Mueller:
An Extended Kernel for Generalized Multiple-Instance Learning.
ICTAI 2004: 272-277 |
12 | | Chang Wang,
Stephen D. Scott,
Qingping Tao,
Dmitri E. Fomenko,
Vadim N. Gladyshev:
New Techniques for Generation and Analysis of Evolutionary Trees.
METMBS 2004: 283-292 |
2003 |
11 | | Sally A. Goldman,
Stephen D. Scott:
Multiple-Instance Learning of Real-Valued Geometric Patterns.
Ann. Math. Artif. Intell. 39(3): 259-290 (2003) |
10 | EE | Sally A. Goldman,
Stephen Kwek,
Stephen D. Scott:
Learning from examples with unspecified attribute values.
Inf. Comput. 180(2): 82-100 (2003) |
2001 |
9 | EE | Daniel R. Dooly,
Sally A. Goldman,
Stephen D. Scott:
On-line analysis of the TCP acknowledgment delay problem.
J. ACM 48(2): 243-273 (2001) |
8 | | Sally A. Goldman,
Stephen Kwek,
Stephen D. Scott:
Agnostic Learning of Geometric Patterns.
J. Comput. Syst. Sci. 62(1): 123-151 (2001) |
1999 |
7 | | Sally A. Goldman,
Stephen D. Scott:
A Theoretical and Empirical Study of a Noise-Tolerant Algorithm to Learn Geometric Patterns.
Machine Learning 37(1): 5-49 (1999) |
1998 |
6 | EE | Daniel R. Dooly,
Sally A. Goldman,
Stephen D. Scott:
TCP Dynamic Acknowledgment Delay: Theory and Practice (Extended Abstract).
STOC 1998: 389-398 |
1997 |
5 | EE | Sally A. Goldman,
Stephen Kwek,
Stephen D. Scott:
Learning from Examples with Unspecified Attribute Values (Extended Abstract).
COLT 1997: 231-242 |
4 | EE | Sally A. Goldman,
Stephen Kwek,
Stephen D. Scott:
Agnostic Learning of Geometric Patterns (Extended Abstract).
COLT 1997: 325-333 |
1996 |
3 | | Sally A. Goldman,
Stephen D. Scott:
A Theoretical and Empirical Study of a Noise-Tolerant Algorithm to Learn Geormetric Patterns.
ICML 1996: 191-199 |
2 | | Paul W. Goldberg,
Sally A. Goldman,
Stephen D. Scott:
PAC Learning of One-Dimensional Patterns.
Machine Learning 25(1): 51-70 (1996) |
1995 |
1 | EE | Stephen D. Scott,
Ashok Samal,
Sharad C. Seth:
HGA: A Hardware-Based Genetic Algorithm.
FPGA 1995: 53-59 |