Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Spectral Techniques and Fault Detection
Spectral Techniques and Fault Detection
Spectral Techniques in Digital Logic
Spectral Techniques in Digital Logic
Finite Orthogonal Series in Design of Digital Devices
Finite Orthogonal Series in Design of Digital Devices
Learning decision trees using the Fourier spectrum
STOC '91 Proceedings of the twenty-third annual ACM symposium on Theory of computing
Constant depth circuits, Fourier transform, and learnability
Journal of the ACM (JACM)
Lower bounds for noisy Boolean decision trees
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Spectral Analysis of Boolean Functions as a Graph Eigenvalue Problem
IEEE Transactions on Computers
Circuit and decision tree complexity of some number theoretic problems
Information and Computation
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
Data Mining and Knowledge Discovery
Theoretical Computer Science
On the average sensitivity of testing square-free numbers
COCOON'99 Proceedings of the 5th annual international conference on Computing and combinatorics
Geometric implications of the naive Bayes assumption
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
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A universal lower-bound technique for the size and other implementation characteristics of an arbitrary Boolean function as a decision tree and as a two-level AND/OR circuit is derived. The technique is based on the power spectrum coefficients of the n dimensional Fourier transform of the function. The bounds vary from constant to exponential and are tight in many cases. Several examples are presented.