Andrew R. Barron

发表

Toward fast reliable communication at rates near capacity with Gaussian noise

Andrew R. Barron, Antony Joseph, A. Barron, 2010, 2010 IEEE International Symposium on Information Theory.

Stochastic Complexity for tree models

Andrew R. Barron, Jun'ichi Takeuchi, A. Barron, 2014, 2014 IEEE Information Theory Workshop (ITW 2014).

Minimax redundancy for the class of memoryless sources

Andrew R. Barron, Qun Xie, A. Barron, 1997, IEEE Trans. Inf. Theory.

Penalized least squares, model selection, convex hull classes and neural nets

Andrew R. Barron, Gerald H. L. Cheang, 2001, ESANN.

A model for pricing data bundles based on minimax risks for estimation of a location parameter

Mokshay M. Madiman, Andrew R. Barron, Abram Kagan, 2009, 2009 IEEE Information Theory Workshop on Networking and Information Theory.

The Monotonicity of Information in the Central Limit Theorem and Entropy Power Inequalities

Mokshay Madiman, Andrew R. Barron, 2006, 2006 IEEE International Symposium on Information Theory.

Minimum complexity density estimation

Andrew R. Barron, Thomas M. Cover, T. Cover, 1991, IEEE Trans. Inf. Theory.

Approximation and estimation bounds for artificial neural networks

Andrew R. Barron, A. Barron, 2004, Machine Learning.

Mixture Density Estimation

Andrew R. Barron, Jonathan Q. Li, A. Barron, 1999, NIPS.

Minimax lower bounds for ridge combinations including neural nets

Andrew R. Barron, Jason M. Klusowski, A. Barron, 2017, 2017 IEEE International Symposium on Information Theory (ISIT).

Approximation by Combinations of ReLU and Squared ReLU Ridge Functions With $\ell^1$ and $\ell^0$ Controls

Andrew R. Barron, Jason M. Klusowski, A. Barron, 2016, IEEE Transactions on Information Theory.

Asymptotic minimax regret for data compression, gambling, and prediction

Andrew R. Barron, Qun Xie, A. Barron, 1997, IEEE Trans. Inf. Theory.

In Silico Drug Screening Approach for the Design of Magic Bullets: A Successful Example with Anti-HIV Fullerene Derivatized Amino Acids

Serdar Durdagi, Andrew R. Barron, Manthos G. Papadopoulos, 2009, J. Chem. Inf. Model..

A bound on the financial value of information

Andrew R. Barron, Thomas M. Cover, T. Cover, 1988, IEEE Trans. Inf. Theory.

High-rate sparse superposition codes with iteratively optimal estimates

Andrew R. Barron, Sanghee Cho, A. Barron, 2012, 2012 IEEE International Symposium on Information Theory Proceedings.

Information Theory in Probability, Statistics, Learning, and Neural Nets (Abstract)

Andrew R. Barron, 1997, COLT.

The Minimum Description Length Principle in Coding and Modeling

Jorma Rissanen, Bin Yu, Andrew R. Barron, 1998, IEEE Trans. Inf. Theory.

Analysis of fast sparse superposition codes

Andrew R. Barron, Antony Joseph, 2011, 2011 IEEE International Symposium on Information Theory Proceedings.

Correction to 'Minimum Complexity Density Estimation'

Andrew R. Barron, Thomas M. Cover, 1991, IEEE Trans. Inf. Theory.

Asymptotically minimax regret by Bayes mixtures for non-exponential families

Andrew R. Barron, Jun'ichi Takeuchi, A. Barron, 2013, 2013 IEEE Information Theory Workshop (ITW).

Information theoretic validity of penalized likelihood

Andrew R. Barron, Sabyasachi Chatterjee, A. Barron, 2014, 2014 IEEE International Symposium on Information Theory.

Distribution estimation consistent in total variation and in two types of information divergence

László Györfi, Edward C. van der Meulen, Andrew R. Barron, 1992, IEEE Trans. Inf. Theory.

Fast Sparse Superposition Codes have Exponentially Small Error Probability for R < C pdf

Andrew R. Barron, Antony Joseph, A. Barron, 2012, ArXiv.

MDL, penalized likelihood, and statistical risk

Cong Huang, Andrew R. Barron, Xi Luo, 2008, 2008 IEEE Information Theory Workshop.

A teacher''s guide to distance learning

Andrew R. Barron, A. Barron, 1999 .

Information-theoretic asymptotics of Bayes methods

Andrew R. Barron, Bertrand S. Clarke, A. Barron, 1990, IEEE Trans. Inf. Theory.

Approximation and Estimation for High-Dimensional Deep Learning Networks pdf

Andrew R. Barron, Jason M. Klusowski, A. Barron, 2018, ArXiv.

Complexity Regularization with Application to Artificial Neural Networks

Andrew R. Barron, A. Barron, 1991 .

Fast Sparse Superposition Codes Have Near Exponential Error Probability for $R<{\cal C}$

Andrew R. Barron, Antony Joseph, A. Barron, 2014, IEEE Transactions on Information Theory.

An Asymptotic Property of Model Selection Criteria

Yuhong Yang, Andrew R. Barron, Yuhong Yang, 1998, IEEE Trans. Inf. Theory.

Large Alphabet Compression and Predictive Distributions through Poissonization and Tilting pdf

Andrew R. Barron, Xiao Yang, A. Barron, 2014, ArXiv.

Micro‐ and nano‐sensor technology/trends in sensor markets. Sensors: A comprehensive survey, vol. 8

Andrew R. Barron, A. Barron, 1996 .

Sparse Regression Codes

Sekhar Tatikonda, Andrew R. Barron, Ramji Venkataramanan, 2019, Found. Trends Commun. Inf. Theory.

Estimation with two hidden layer neural nets

Andrew R. Barron, Gerald H. L. Cheang, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Asymptotically minimax regret for models with hidden variables

Andrew R. Barron, Jun'ichi Takeuchi, A. Barron, 2014, 2014 IEEE International Symposium on Information Theory.

Least squares superposition codes of moderate dictionary size, reliable at rates up to capacity

Andrew R. Barron, Antony Joseph, A. Barron, 2010, 2010 IEEE International Symposium on Information Theory.

The minimum description length principle in coding and modeling (invited paper)

Jorma Rissanen, Andrew R. Barron, Bin Yu, 2000 .

Properties of Jeffreys Mixture for Markov Sources

Tsutomu Kawabata, Andrew R. Barron, Jun'ichi Takeuchi, 2013, IEEE Transactions on Information Theory.

Compression and predictive distributions for large alphabet i.i.d and Markov models

Andrew R. Barron, Xiao Yang, 2014, 2014 IEEE International Symposium on Information Theory.

Polar coding schemes for the AWGN channel

Emmanuel Abbe, Andrew R. Barron, 2011, 2011 IEEE International Symposium on Information Theory Proceedings.

Information Theory and Mixing Least-Squares Regressions

Andrew R. Barron, Gilbert Leung, A. Barron, 2006, IEEE Transactions on Information Theory.

Complexity, Statistical Risk, and Metric Entropy of Deep Nets Using Total Path Variation pdf

Andrew R. Barron, Jason M. Klusowski, A. Barron, 2019, ArXiv.

Generalized Entropy Power Inequalities and Monotonicity Properties of Information

Mokshay M. Madiman, Andrew R. Barron, A. Barron, 2006, IEEE Transactions on Information Theory.

Universal approximation bounds for superpositions of a sigmoidal function

Andrew R. Barron, A. Barron, 1993, IEEE Trans. Inf. Theory.

Improved MDL Estimators Using Local Exponential Family Bundles Applied to Mixture Families

Andrew R. Barron, Kohei Miyamoto, Jun’ichi Takeuchi, 2019, 2019 IEEE International Symposium on Information Theory (ISIT).

Bayesian properties of normalized maximum likelihood and its fast computation

Kazuho Watanabe, Teemu Roos, Andrew R. Barron, 2014, 2014 IEEE International Symposium on Information Theory.

Minimax Compression and Large Alphabet Approximation Through Poissonization and Tilting

Andrew R. Barron, Xiao Yang, A. Barron, 2017, IEEE Transactions on Information Theory.

Combining least-squares regressions: an upper-bound on mean-squared error

Andrew R. Barron, Gilbert Leung, A. Barron, 2005, Proceedings. International Symposium on Information Theory, 2005. ISIT 2005..

Exact minimax strategies for predictive density estimation, data compression, and model selection

Feng Liang, Andrew R. Barron, A. Barron, 2002, IEEE Transactions on Information Theory.

Jeffreys' prior yields the asymptotic minimax redundancy

Andrew R. Barron, Bertrand Clarke, 1994, Proceedings of 1994 Workshop on Information Theory and Statistics.

[Neural Networks: A Review from Statistical Perspective]: Comment

Andrew R. Barron, 1994 .

MDL Procedures with ` 1 Penalty and their Statistical Risk

Andrew R. Barron, A. Barron, Xi Luo, 2008 .

USING THE METHOD OF NEARBY MEASURES IN SUPERPOSITION CODING WITH A BERNOULLI DICTIONARY

Andrew R. Barron, Cynthia Rush, 2013 .

A Better Approximation for Balls

Andrew R. Barron, Gerald H. L. Cheang, A. Barron, 2000 .