A bound on the financial value of information. - Andrew R. Barron; Thomas M. Cover (IEEE Trans. Inf. Theory, 1988)

Information-theoretic asymptotics of Bayes methods. - Bertrand S. Clarke; Andrew R. Barron (IEEE Trans. Inf. Theory, 1990)

Minimum complexity density estimation. - Andrew R. Barron; Thomas M. Cover (IEEE Trans. Inf. Theory, 1991)

Correction to 'Minimum Complexity Density Estimation'. - Andrew R. Barron; Thomas M. Cover (IEEE Trans. Inf. Theory, 1991)

Distribution estimation consistent in total variation and in two types of information divergence. - Andrew R. Barron; László Györfi; Edward C. van der Meulen (IEEE Trans. Inf. Theory, 1992)

Universal approximation bounds for superpositions of a sigmoidal function. - Andrew R. Barron (IEEE Trans. Inf. Theory, 1993)

Approximation and Estimation Bounds for Artificial Neural Networks. - Andrew R. Barron (Mach. Learn., 1994)

Information Theory in Probability, Statistics, Learning, and Neural Nets (Abstract). - Andrew R. Barron (COLT, 1997)

Minimax redundancy for the class of memoryless sources. - Qun Xie; Andrew R. Barron (IEEE Trans. Inf. Theory, 1997)

The Minimum Description Length Principle in Coding and Modeling. - Andrew R. Barron; Jorma Rissanen; Bin Yu 001 (IEEE Trans. Inf. Theory, 1998)

An Asymptotic Property of Model Selection Criteria. - Yuhong Yang 002; Andrew R. Barron (IEEE Trans. Inf. Theory, 1998)

Estimation with two hidden layer neural nets. - Gerald H. L. Cheang; Andrew R. Barron (IJCNN, 1999)

Mixture Density Estimation. - Jonathan Q. Li; Andrew R. Barron (NIPS, 1999)

Asymptotic minimax regret for data compression, gambling, and prediction. - Qun Xie; Andrew R. Barron (IEEE Trans. Inf. Theory, 2000)

Penalized least squares, model selection, convex hull classes and neural nets. - Gerald H. L. Cheang; Andrew R. Barron (ESANN, 2001)

Exact minimax strategies for predictive density estimation, data compression, and model selection. - Feng Liang; Andrew R. Barron (IEEE Trans. Inf. Theory, 2004)

Combining least-squares regressions: an upper-bound on mean-squared error. - Gilbert Leung; Andrew R. Barron (ISIT, 2005)

The Monotonicity of Information in the Central Limit Theorem and Entropy Power Inequalities. - Mokshay Madiman; Andrew R. Barron (ISIT, 2006)

Information Theory and Mixing Least-Squares Regressions. - Gilbert Leung; Andrew R. Barron (IEEE Trans. Inf. Theory, 2006)

Generalized Entropy Power Inequalities and Monotonicity Properties of Information. - Mokshay M. Madiman; Andrew R. Barron (IEEE Trans. Inf. Theory, 2007)

MDL, penalized likelihood, and statistical risk. - Andrew R. Barron; Cong Huang; Jonathan Q. Li; Xi Luo (ITW, 2008)

A model for pricing data bundles based on minimax risks for estimation of a location parameter. - Mokshay M. Madiman; Andrew R. Barron; Abram Kagan; Tinghui Yu (ITW, 2009)

In Silico Drug Screening Approach for the Design of Magic Bullets: A Successful Example with Anti-HIV Fullerene Derivatized Amino Acids. - Serdar Durdagi; Claudiu T. Supuran; T. Amanda Strom; Nadjmeh Doostdar; Mananjali K. Kumar; Andrew R. Barron; Thomas M. Mavromoustakos; Manthos G. Papadopoulos (J. Chem. Inf. Model., 2009)

Least squares superposition codes of moderate dictionary size, reliable at rates up to capacity. - Andrew R. Barron; Antony Joseph (ISIT, 2010)

Toward fast reliable communication at rates near capacity with Gaussian noise. - Andrew R. Barron; Antony Joseph (ISIT, 2010)

Polar coding schemes for the AWGN channel. - Emmanuel Abbe; Andrew R. Barron (ISIT, 2011)

Analysis of fast sparse superposition codes. - Andrew R. Barron; Antony Joseph (ISIT, 2011)

High-rate sparse superposition codes with iteratively optimal estimates. - Andrew R. Barron; Sanghee Cho (ISIT, 2012)

Fast Sparse Superposition Codes have Exponentially Small Error Probability for R < C - Antony Joseph; Andrew R. Barron (CoRR, 2012)

Introduction to the Issue on Signal Processing Methods in Finance and Electronic Trading. - Ali N. Akansu; Sanjeev R. Kulkarni; Marco Avellaneda; Andrew R. Barron (IEEE J. Sel. Top. Signal Process., 2012)

Least Squares Superposition Codes of Moderate Dictionary Size Are Reliable at Rates up to Capacity. - Antony Joseph; Andrew R. Barron (IEEE Trans. Inf. Theory, 2012)

Asymptotically minimax regret by Bayes mixtures for non-exponential families. - Jun'ichi Takeuchi; Andrew R. Barron (ITW, 2013)

Properties of Jeffreys Mixture for Markov Sources. - Jun'ichi Takeuchi; Tsutomu Kawabata; Andrew R. Barron (IEEE Trans. Inf. Theory, 2013)

Bayesian properties of normalized maximum likelihood and its fast computation. - Andrew R. Barron; Teemu Roos; Kazuho Watanabe (ISIT, 2014)

Information theoretic validity of penalized likelihood. - Sabyasachi Chatterjee; Andrew R. Barron (ISIT, 2014)

Asymptotically minimax regret for models with hidden variables. - Jun'ichi Takeuchi; Andrew R. Barron (ISIT, 2014)

Compression and predictive distributions for large alphabet i.i.d and Markov models. - Xiao Yang 003; Andrew R. Barron (ISIT, 2014)

Stochastic Complexity for tree models. - Jun'ichi Takeuchi; Andrew R. Barron (ITW, 2014)

Large Alphabet Compression and Predictive Distributions through Poissonization and Tilting. - Xiao Yang 003; Andrew R. Barron (CoRR, 2014)

Fast Sparse Superposition Codes Have Near Exponential Error Probability for $R<{ cal C}$. - Antony Joseph; Andrew R. Barron (IEEE Trans. Inf. Theory, 2014)

Minimax lower bounds for ridge combinations including neural nets. - Jason M. Klusowski; Andrew R. Barron (ISIT, 2017)

Minimax Compression and Large Alphabet Approximation Through Poissonization and Tilting. - Xiao Yang 003; Andrew R. Barron (IEEE Trans. Inf. Theory, 2017)

Approximation and Estimation for High-Dimensional Deep Learning Networks. - Andrew R. Barron; Jason M. Klusowski (CoRR, 2018)

Approximation by Combinations of ReLU and Squared ReLU Ridge Functions With ℓ1 and ℓ0 Controls. - Jason M. Klusowski; Andrew R. Barron (IEEE Trans. Inf. Theory, 2018)

Improved MDL Estimators Using Local Exponential Family Bundles Applied to Mixture Families. - Kohei Miyamoto; Andrew R. Barron; Jun'ichi Takeuchi (ISIT, 2019)

Complexity, Statistical Risk, and Metric Entropy of Deep Nets Using Total Path Variation. - Andrew R. Barron; Jason M. Klusowski (CoRR, 2019)

Sparse Regression Codes. - Ramji Venkataramanan; Sekhar Tatikonda; Andrew R. Barron (Found. Trends Commun. Inf. Theory, 2019)

Proposal of a Score Based Approach to Sampling Using Monte Carlo Estimation of Score and Oracle Access to Target Density. - Curtis McDonald; Andrew R. Barron (CoRR, 2022)

Improved MDL Estimators Using Fiber Bundle of Local Exponential Families for Non-exponential Families. - Kohei Miyamoto; Andrew R. Barron; Jun'ichi Takeuchi (CoRR, 2023)

Log-Concave Coupling for Sampling Neural Net Posteriors. - Curtis McDonald; Andrew R. Barron (ISIT, 2024)

Asymptotically Minimax Regret by Bayes Mixtures. - Jun'ichi Takeuchi; Andrew R. Barron (CoRR, 2024)