Communications of the ACM
A qualitative physics based on confluences
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Matrix multiplication via arithmetic progressions
Journal of Symbolic Computation - Special issue on computational algebraic complexity
Algorithms for finding patterns in strings
Handbook of theoretical computer science (vol. A)
Efficient 2-dimensional approximate matching of non-rectangular figures
SODA '91 Proceedings of the second annual ACM-SIAM symposium on Discrete algorithms
On the complexity of inferring functional dependencies
Discrete Applied Mathematics - Special issue on combinatorial problems in databases
An introduction to computational learning theory
An introduction to computational learning theory
Randomized algorithms
Fast rectangular matrix multiplications and improving parallel matrix computations
PASCO '97 Proceedings of the second international symposium on Parallel symbolic computation
Identifying gene regulatory networks from experimental data
RECOMB '99 Proceedings of the third annual international conference on Computational molecular biology
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Approximating Minimum Keys and Optimal Substructure Screens
COCOON '96 Proceedings of the Second Annual International Conference on Computing and Combinatorics
Efficient randomized pattern-matching algorithms
IBM Journal of Research and Development - Mathematics and computing
DS '00 Proceedings of the Third International Conference on Discovery Science
Asymptotical lower limits on required number of examples for learning boolean networks
ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
Multi-objective model optimization for inferring gene regulatory networks
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
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Due to the recent progress of the DNA microarray technology, a large number of gene expression profile data are being produced. How to analyze gene expression data is an important topic in computational molecular biology Several studies have been done using the Boolean network as a model of a genetic network This paper proposes efficient algorithms for identifying Boolean networks of bounded indegree and related biological networks, where identification of a Boolean network can be formalized as a problem of identifying many Boolean functions simultaneously. For the identification of a Boolean network, an O(mnD+1) time naive algorithm and a simple O(mnD) time algorithm are known, where n denotes the number of nodes, m denotes the number of examples, and D denotes the maximum indegree. This paper presents an improved O(mw-2nD + mnD+w-3) time Monte-Carlo type randomized algorithm, where w is the exponent of matrix multiplication (currently, w