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11/06/2022
Confidence Intervals for Unobserved Events
Consider a finite sample from an unknown distribution over a countable a...
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09/12/2021
Feature Importance in Gradient Boosting Trees with Cross-Validation Feature Selection
Gradient Boosting Machines (GBM) are among the go-to algorithms on tabul...
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12/21/2020
Neural Joint Entropy Estimation
Estimating the entropy of a discrete random variable is a fundamental pr...
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11/25/2018
Innovation Representation of Stochastic Processes with Application to Causal Inference
Typically, real-world stochastic processes are not easy to analyze. In t...
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10/31/2018
An Information-Theoretic Framework for Non-linear Canonical Correlation Analysis
Canonical Correlation Analysis (CCA) is a linear representation learning...
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10/26/2018
Lossless (and Lossy) Compression of Random Forests
Ensemble methods are among the state-of-the-art predictive modeling appr...
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10/14/2018
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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09/16/2018
Linear Independent Component Analysis over Finite Fields: Algorithms and Bounds
Independent Component Analysis (ICA) is a statistical tool that decompos...
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09/13/2018
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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09/13/2018
Generalized Independent Components Analysis Over Finite Alphabets
Independent component analysis (ICA) is a statistical method for transfo...
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09/13/2018
PhD Dissertation: Generalized Independent Components Analysis Over Finite Alphabets
Independent component analysis (ICA) is a statistical method for transfo...
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07/06/2018
Outperforming Good-Turing: Preliminary Report
Estimating a large alphabet probability distribution from a limited numb...
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05/10/2018
On the Universality of the Logistic Loss Function
A loss function measures the discrepancy between the true values (observ...
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04/26/2018
Optimal Procedures for Multiple Testing Problems
Multiple testing problems are a staple of modern statistical analysis. T...
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11/07/2017
Gaussian Lower Bound for the Information Bottleneck Limit
The Information Bottleneck (IB) is a conceptual method for extracting th...
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12/10/2015