
Innovation Representation of Stochastic Processes with Application to Causal Inference
Typically, realworld stochastic processes are not easy to analyze. In t...
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An InformationTheoretic Framework for Nonlinear Canonical Correlation Analysis
Canonical Correlation Analysis (CCA) is a linear representation learning...
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Lossless (and Lossy) Compression of Random Forests
Ensemble methods are among the stateoftheart predictive modeling appr...
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Bregman Divergence Bounds and the Universality of the Logarithmic Loss
A loss function measures the discrepancy between the true values and the...
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Linear Independent Component Analysis over Finite Fields: Algorithms and Bounds
Independent Component Analysis (ICA) is a statistical tool that decompos...
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MSc Dissertation: Exclusive Row Biclustering for Gene Expression Using a Combinatorial Auction Approach
The availability of large microarray data has led to a growing interest ...
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Generalized Independent Components Analysis Over Finite Alphabets
Independent component analysis (ICA) is a statistical method for transfo...
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PhD Dissertation: Generalized Independent Components Analysis Over Finite Alphabets
Independent component analysis (ICA) is a statistical method for transfo...
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Outperforming GoodTuring: Preliminary Report
Estimating a large alphabet probability distribution from a limited numb...
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On the Universality of the Logistic Loss Function
A loss function measures the discrepancy between the true values (observ...
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Optimal Procedures for Multiple Testing Problems
Multiple testing problems are a staple of modern statistical analysis. T...
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Gaussian Lower Bound for the Information Bottleneck Limit
The Information Bottleneck (IB) is a conceptual method for extracting th...
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CrossValidated Variable Selection in TreeBased Methods Improves Predictive Performance
Recursive partitioning approaches producing treelike models are a long ...
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Amichai Painsky
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