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An Elementary Derivation of the Numerical Integration Bounds in Beginning Calculus

The American mathematical monthly, 2017-06, Vol.124 (6), p.558-561

Jones, Lee K.

2017

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Statistical Learning from Single-Molecule Experiments: Support Vector Machines and Expectation–Maximization Approaches to Understanding Protein Unfolding Data

The journal of physical chemistry. B, 2021-06, Vol.125 (22), p.5794-5808

2021

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A Simple Lemma on Greedy Approximation in Hilbert Space and Convergence Rates for Projection Pursuit Regression and Neural Network Training

The Annals of statistics, 1992-03, Vol.20 (1), p.608-613

Jones, Lee K.

1992

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Modeling origin-destination uncertainty using network sensor and survey data and new approaches to robust control

Transportation research. Part C, Emerging technologies, 2018-09, Vol.94, p.121-132

2018

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Confident predictability: identifying reliable gene expression patterns for individualized tumor classification using a local minimax kernel algorithm

BMC medical genomics, 2011-01, Vol.4 (1), p.10-10, Article 10

2011

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Remarks on queue inference from departure data alone and the importance of the queue inference engine

Operations research letters, 2012-11, Vol.40 (6), p.503-505

Jones, Lee K.

2012

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Local Minimax Learning of Functions With Best Finite Sample Estimation Error Bounds: Applications to Ridge and Lasso Regression, Boosting, Tree Learning, Kernel Machines, and Inverse Problems

IEEE transactions on information theory, 2009-12, Vol.55 (12), p.5700-5727

Jones, L.K.

2009

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Robust controls for traffic networks: The near-Bayes near-Minimax strategy

Transportation research. Part C, Emerging technologies, 2013-02, Vol.27, p.205-218

2013

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Modeling Origin-Destination Uncertainty Using Network Sensor and Survey Data and New Approaches to Robust Control

Transportation research procedia (Online), 2017, Vol.23, p.887-900

2017

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Inferring Balking Behavior From Transactional Data

Operations research, 1999-09, Vol.47 (5), p.778-784

Jones, Lee K

1999

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The computational intractability of training sigmoidal neural networks

IEEE transactions on information theory, 1997-01, Vol.43 (1), p.167-173

Jones, L.K.

1997

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On a Conjecture of Huber Concerning the Convergence of Projection Pursuit Regression

The Annals of statistics, 1987-06, Vol.15 (2), p.880-882

Jones, Lee K.

1987

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Good weights and hyperbolic kernels for neural networks, projection pursuit, and pattern classification: Fourier strategies for extracting information from high-dimensional data

IEEE transactions on information theory, 1994-03, Vol.40 (2), p.439-454

Jones, L.K.

1994

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Approximation-Theoretic Derivation of Logarithmic Entropy Principles for Inverse Problems and Unique Extension of the Maximum Entropy Method to Incorporate Prior Knowledge

SIAM journal on applied mathematics, 1989-04, Vol.49 (2), p.650-661

Jones, Lee K.

1989

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Uniformly Generating Origin Destination Tables

Information Theory, Combinatorics, and Search Theory, p.209-216

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Constructive approximations for neural networks by sigmoidal functions

Proceedings of the IEEE, 1990-10, Vol.78 (10), p.1586-1589

Jones, L.K.

1990

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Efficient Computation of Probabilities of Events Described by Order Statistics and Applications to Queue Inference

INFORMS journal on computing, 1995-02, Vol.7 (1), p.89-100

1995

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On the range of an unbounded partly atomic vector-valued measure

Pacific journal of mathematics, 1992-06, Vol.154 (2), p.245-251

1992

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Information Theory, Combinatorics, and Search Theory: In Memory of Rudolf Ahlswede

2013, 2013

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A Combinatorial Approach for Classification of Patterns with Missing Information and Random Orientation

IEEE transactions on pattern analysis and machine intelligence, 1986-07, Vol.PAMI-8 (4), p.482-490

1986

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On Markov chain Monte Carlo Algorithms for Computing Conditional Expectations Based on Sufficient Statistics

Journal of computational and graphical statistics, 2002-09, Vol.11 (3), p.660-677

2002

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A generalization of the method of correlated sampling for numerical integration

SIAM journal on scientific and statistical computing, 1986-07, Vol.7 (3), p.1037-1040

1986

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Unimodular eigenvalues and weak mixing

Journal of functional analysis, 1980, Vol.35 (1), p.42-48

1980

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Ergodic Theorems of Weak Mixing Type

Proceedings of the American Mathematical Society, 1976, Vol.57 (1), p.50-52

1976

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General entropy criteria for inverse problems, with applications to data compression, pattern classification, and cluster analysis

IEEE transactions on information theory, 1990-01, Vol.36 (1), p.23-30

1990

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An Elementary Derivation of the Numerical Integration Bounds in Beginning Calculus

Statistical Learning from Single-Molecule Experiments: Support Vector Machines and Expectation–Maximization Approaches to Understanding Protein Unfolding Data

A Simple Lemma on Greedy Approximation in Hilbert Space and Convergence Rates for Projection Pursuit Regression and Neural Network Training

Modeling origin-destination uncertainty using network sensor and survey data and new approaches to robust control

Confident predictability: identifying reliable gene expression patterns for individualized tumor classification using a local minimax kernel algorithm

Remarks on queue inference from departure data alone and the importance of the queue inference engine

Local Minimax Learning of Functions With Best Finite Sample Estimation Error Bounds: Applications to Ridge and Lasso Regression, Boosting, Tree Learning, Kernel Machines, and Inverse Problems

Robust controls for traffic networks: The near-Bayes near-Minimax strategy

Modeling Origin-Destination Uncertainty Using Network Sensor and Survey Data and New Approaches to Robust Control

Inferring Balking Behavior From Transactional Data

The computational intractability of training sigmoidal neural networks

On a Conjecture of Huber Concerning the Convergence of Projection Pursuit Regression

Good weights and hyperbolic kernels for neural networks, projection pursuit, and pattern classification: Fourier strategies for extracting information from high-dimensional data

Approximation-Theoretic Derivation of Logarithmic Entropy Principles for Inverse Problems and Unique Extension of the Maximum Entropy Method to Incorporate Prior Knowledge

Uniformly Generating Origin Destination Tables

Constructive approximations for neural networks by sigmoidal functions

Efficient Computation of Probabilities of Events Described by Order Statistics and Applications to Queue Inference

On the range of an unbounded partly atomic vector-valued measure

Information Theory, Combinatorics, and Search Theory: In Memory of Rudolf Ahlswede

A Combinatorial Approach for Classification of Patterns with Missing Information and Random Orientation

On Markov chain Monte Carlo Algorithms for Computing Conditional Expectations Based on Sufficient Statistics

A generalization of the method of correlated sampling for numerical integration

Unimodular eigenvalues and weak mixing

Ergodic Theorems of Weak Mixing Type

General entropy criteria for inverse problems, with applications to data compression, pattern classification, and cluster analysis

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