Theory of computation: formal languages, automata, and complexity
Theory of computation: formal languages, automata, and complexity
Generalized Queries on Probabilistic Context-Free Grammars
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mining the stock market (extended abstract): which measure is best?
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
Machine Learning
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Inducing Probabilistic Grammars by Bayesian Model Merging
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
The Penn-Lehman Automated Trading Project
IEEE Intelligent Systems
Knowledge discovery in time series databases
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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A variety of interesting domains, such as financial markets, weather systems, herding phenomena, etc., are characterized by highly complex time series datasets which defy simple description and prediction. The generation of input data for simulators operating in these domains is challenging because process description usually involves high-dimensional joint distributions that are either too complex or simply unavailable. In such applications, a standard approach is to drive simulators with (historical) trace-data, along with facilities for real-time interaction and synchronization. But, limited input data, or conversely, abundant but low-fidelity random data, limits the usefulness and quality of the results. With a view to generating high-fidelity, random input for such applications, we propose a methodology which uses the original data, as a template, to generate candidate datasets, to finally accept only those datasets which resemble the template, based upon parameterized features. We demonstrate the methodology with some early experimental results.