Stephen D. Scott

According to our database1, Stephen D. Scott authored at least 34 papers between 1995 and 2016.

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Bibliography

2016
Constrained Group Testing to Predict Binding Response of Candidate Compounds.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Learning Hierarchically Decomposable Concepts with Active Over-Labeling.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Computing triangle and open-wedge heavy-hitters in large networks.
Proceedings of the 2016 IEEE International Conference on Big Data, 2016

2014
Yeast pheromone pathway modeling using Petri nets.
BMC Bioinformatics, 2014

2013
New algorithms for budgeted learning.
Machine Learning, 2013

Selecting the Appropriate Consistency Algorithm for CSPs Using Machine Learning Classifiers.
Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

2010
Active Learning from Multiple Noisy Labelers with Varied Costs.
Proceedings of the ICDM 2010, 2010

2009
Renaissance computing: an initiative for promoting student participation in computing.
Proceedings of the 40th SIGCSE Technical Symposium on Computer Science Education, 2009

2008
Kernels for Generalized Multiple-Instance Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2008

Improved MCMC sampling methods for estimating weighted sums in Winnow with application to DNF learning.
Machine Learning, 2008

On reoptimizing multi-class classifiers.
Machine Learning, 2008

2007
Bandit-Based Algorithms for Budgeted Learning.
Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007

2006
Active Learning to Maximize Area Under the ROC Curve.
Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006), 2006

2005
New kernels for protein structural motif discovery and function classification.
Proceedings of the Machine Learning, 2005

Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning.
Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 2005

2004
New Techniques for Generation and Analysis of Evolutionary Trees.
Proceedings of the International Conference on Mathematics and Engineering Techniques in Medicine and Biological Scienes, 2004

An Extended Kernel for Generalized Multiple-Instance Learning.
Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2004), 2004

Agnostic learning of general geometric patterns and multi-instance learning in Rd.
Proceedings of the 2004 International Conference on Machine Learning and Applications, 2004

LASSO: a learning architecture for semantic web ontologies.
Proceedings of the 2004 International Conference on Machine Learning and Applications, 2004

EMPRR: a high-dimensional EM-based peicewise regression algorithm.
Proceedings of the 2004 International Conference on Machine Learning and Applications, 2004

SVM-based generalized multiple-instance learning via approximate box counting.
Proceedings of the Machine Learning, 2004

A Faster Algorithm for Generalized Multiple-Instance Learning.
Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference, 2004

2003
Learning from examples with unspecified attribute values.
Inf. Comput., 2003

Multiple-Instance Learning of Real-Valued Geometric Patterns.
Ann. Math. Artif. Intell., 2003

A novel fiber delay line buffering architecture for optical packet switching.
Proceedings of the Global Telecommunications Conference, 2003

2001
Agnostic Learning of Geometric Patterns.
J. Comput. Syst. Sci., 2001

On-line analysis of the TCP acknowledgment delay problem.
J. ACM, 2001

1999
A Theoretical and Empirical Study of a Noise-Tolerant Algorithm to Learn Geometric Patterns.
Machine Learning, 1999

1998
TCP Dynamic Acknowledgment Delay: Theory and Practice (Extended Abstract).
Proceedings of the Thirtieth Annual ACM Symposium on the Theory of Computing, 1998

1997
Agnostic Learning of Geometric Patterns (Extended Abstract).
Proceedings of the Tenth Annual Conference on Computational Learning Theory, 1997

Learning from Examples with Unspecified Attribute Values (Extended Abstract).
Proceedings of the Tenth Annual Conference on Computational Learning Theory, 1997

1996
PAC Learning of One-Dimensional Patterns.
Machine Learning, 1996

A Theoretical and Empirical Study of a Noise-Tolerant Algorithm to Learn Geormetric Patterns.
Proceedings of the Machine Learning, 1996

1995
HGA: A Hardware-Based Genetic Algorithm.
Proceedings of the Third International ACM Symposium on Field-Programmable Gate Arrays, 1995


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