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Nobel, Andrew - Department of Statistics and Operations Research, University of North Carolina at Chapel Hill
Mining Approximate Frequent Itemsets from Noisy Data Jinze Liu, 1
Hypothesis Testing for Families of Ergodic Processes Andrew B. Nobel
A Note on Uniform Laws of Averages for Dependent Processes Andrew Nobel
Estimating a Function from Ergodic Samples with Additive Noise
On Optimal Sequential Prediction for General Processes Andrew B. Nobel
A Counterexample Concerning Uniform Ergodic Theorems for a Class of Functions
Consistency of Data-driven Histogram Methods for Density Estimation and Classification
Histogram Regression Estimation Using Data-dependent Andrew Nobel
Recursive Partitioning to Reduce Distortion Andrew B. Nobel
Limits to Classification and Regression Estimation from Ergodic Processes
Regression Estimation from an Individual Stable Sequence Gusztav Morvai, Sanjeev R. Kulkarni, Andrew B. Nobel
Analysis of a complexity based pruning scheme for classification trees
Adaptive Model Selection Using Empirical Complexities
INDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 42, NO. 1, JANUARY 1996 191 Termination and Continuity of Greedy Growing
Finitary Reconstruction of a Measure Preserving Tranformation
Density Estimation from an Individual Numerical Sequence Andrew B. Nobel, Gusztav Morvai, and Sanjeev Kulkarni
Vanishing Distortion and Shrinking Cells Andrew B. Nobel
On Density Estimation from Ergodic Processes Terrence M. Adams and Andrew B. Nobel
Some Stochastic Properties of Memoryless Individual Sequences
