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Journal Articles
- 2019
[j22]Ramji Venkataramanan, Sekhar Tatikonda, Andrew R. Barron:
Sparse Regression Codes. Found. Trends Commun. Inf. Theory 15(1-2): 1-195 (2019)- 2018
- [j21]Jason M. Klusowski
, Andrew R. Barron:
Approximation by Combinations of ReLU and Squared ReLU Ridge Functions With ℓ1 and ℓ0 Controls. IEEE Trans. Inf. Theory 64(12): 7649-7656 (2018) - 2017
- [j20]Xiao Yang, Andrew R. Barron:
Minimax Compression and Large Alphabet Approximation Through Poissonization and Tilting. IEEE Trans. Inf. Theory 63(5): 2866-2884 (2017) - 2014
- [j19]Antony Joseph, Andrew R. Barron:
Fast Sparse Superposition Codes Have Near Exponential Error Probability for $R<{\cal C}$. IEEE Trans. Inf. Theory 60(2): 919-942 (2014) - 2013
- [j18]Jun'ichi Takeuchi, Tsutomu Kawabata, Andrew R. Barron:
Properties of Jeffreys Mixture for Markov Sources. IEEE Trans. Inf. Theory 59(1): 438-457 (2013) - 2012
- [j17]Ali N. Akansu, Sanjeev R. Kulkarni, Marco Avellaneda, Andrew R. Barron:
Introduction to the Issue on Signal Processing Methods in Finance and Electronic Trading. IEEE J. Sel. Top. Signal Process. 6(4): 297 (2012) - [j16]Antony Joseph, Andrew R. Barron:
Least Squares Superposition Codes of Moderate Dictionary Size Are Reliable at Rates up to Capacity. IEEE Trans. Inf. Theory 58(5): 2541-2557 (2012) - 2009
- [j15]Serdar Durdagi, Claudiu T. Supuran, T. Amanda Strom, Nadjmeh Doostdar, Mananjali K. Kumar, Andrew R. Barron, Thomas M. Mavromoustakos, Manthos G. Papadopoulos:
In Silico Drug Screening Approach for the Design of Magic Bullets: A Successful Example with Anti-HIV Fullerene Derivatized Amino Acids. J. Chem. Inf. Model. 49(5): 1139-1143 (2009) - 2007
- [j14]Mokshay M. Madiman, Andrew R. Barron:
Generalized Entropy Power Inequalities and Monotonicity Properties of Information. IEEE Trans. Inf. Theory 53(7): 2317-2329 (2007) - 2006
- [j13]Gilbert Leung, Andrew R. Barron:
Information Theory and Mixing Least-Squares Regressions. IEEE Trans. Inf. Theory 52(8): 3396-3410 (2006) - 2004
- [j12]Feng Liang, Andrew R. Barron:
Exact minimax strategies for predictive density estimation, data compression, and model selection. IEEE Trans. Inf. Theory 50(11): 2708-2726 (2004) - 2000
- [j11]Qun Xie, Andrew R. Barron:
Asymptotic minimax regret for data compression, gambling, and prediction. IEEE Trans. Inf. Theory 46(2): 431-445 (2000) - 1998
- [j10]Yuhong Yang, Andrew R. Barron:
An Asymptotic Property of Model Selection Criteria. IEEE Trans. Inf. Theory 44(1): 95-116 (1998) - [j9]Andrew R. Barron, Jorma Rissanen, Bin Yu:
The Minimum Description Length Principle in Coding and Modeling. IEEE Trans. Inf. Theory 44(6): 2743-2760 (1998) - 1997
- [j8]Qun Xie, Andrew R. Barron:
Minimax redundancy for the class of memoryless sources. IEEE Trans. Inf. Theory 43(2): 646-657 (1997) - 1994
- [j7]Andrew R. Barron:
Approximation and Estimation Bounds for Artificial Neural Networks. Mach. Learn. 14(1): 115-133 (1994) - 1993
- [j6]Andrew R. Barron:
Universal approximation bounds for superpositions of a sigmoidal function. IEEE Trans. Inf. Theory 39(3): 930-945 (1993) - 1992
- [j5]Andrew R. Barron, László Györfi, Edward C. van der Meulen:
Distribution estimation consistent in total variation and in two types of information divergence. IEEE Trans. Inf. Theory 38(5): 1437-1454 (1992) - 1991
- [j4]Andrew R. Barron, Thomas M. Cover:
Minimum complexity density estimation. IEEE Trans. Inf. Theory 37(4): 1034-1054 (1991) - [j3]Andrew R. Barron, Thomas M. Cover:
Correction to 'Minimum Complexity Density Estimation'. IEEE Trans. Inf. Theory 37(6): 1738- (1991) - 1990
- [j2]Bertrand S. Clarke, Andrew R. Barron:
Information-theoretic asymptotics of Bayes methods. IEEE Trans. Inf. Theory 36(3): 453-471 (1990) - 1988
- [j1]Andrew R. Barron, Thomas M. Cover:
A bound on the financial value of information. IEEE Trans. Inf. Theory 34(5): 1097-1100 (1988)
Conference and Workshop Papers
- 2024
- [c23]Curtis McDonald, Andrew R. Barron:
Log-Concave Coupling for Sampling Neural Net Posteriors. ISIT 2024: 2251-2256 - 2019
- [c22]Kohei Miyamoto, Andrew R. Barron, Jun'ichi Takeuchi:
Improved MDL Estimators Using Local Exponential Family Bundles Applied to Mixture Families. ISIT 2019: 1442-1446 - 2017
- [c21]Jason M. Klusowski, Andrew R. Barron:
Minimax lower bounds for ridge combinations including neural nets. ISIT 2017: 1376-1380 - 2014
- [c20]Andrew R. Barron, Teemu Roos, Kazuho Watanabe:
Bayesian properties of normalized maximum likelihood and its fast computation. ISIT 2014: 1667-1671 - [c19]Xiao Yang, Andrew R. Barron:
Compression and predictive distributions for large alphabet i.i.d and Markov models. ISIT 2014: 2504-2508 - [c18]Sabyasachi Chatterjee, Andrew R. Barron:
Information theoretic validity of penalized likelihood. ISIT 2014: 3027-3031 - [c17]Jun'ichi Takeuchi, Andrew R. Barron:
Asymptotically minimax regret for models with hidden variables. ISIT 2014: 3037-3041 - [c16]Jun'ichi Takeuchi, Andrew R. Barron:
Stochastic Complexity for tree models. ITW 2014: 222-226 - 2013
- [c15]Jun'ichi Takeuchi, Andrew R. Barron:
Asymptotically minimax regret by Bayes mixtures for non-exponential families. ITW 2013: 1-5 - 2012
- [c14]Andrew R. Barron, Sanghee Cho:
High-rate sparse superposition codes with iteratively optimal estimates. ISIT 2012: 120-124 - 2011
- [c13]Emmanuel Abbe, Andrew R. Barron:
Polar coding schemes for the AWGN channel. ISIT 2011: 194-198 - [c12]Andrew R. Barron, Antony Joseph:
Analysis of fast sparse superposition codes. ISIT 2011: 1772-1776 - 2010
- [c11]Andrew R. Barron, Antony Joseph:
Least squares superposition codes of moderate dictionary size, reliable at rates up to capacity. ISIT 2010: 275-279 - [c10]Andrew R. Barron, Antony Joseph:
Toward fast reliable communication at rates near capacity with Gaussian noise. ISIT 2010: 315-319 - 2009
- [c9]Mokshay M. Madiman, Andrew R. Barron, Abram Kagan, Tinghui Yu:
A model for pricing data bundles based on minimax risks for estimation of a location parameter. ITW 2009: 106-109 - 2008
- [c8]Andrew R. Barron, Cong Huang, Jonathan Q. Li, Xi Luo:
MDL, penalized likelihood, and statistical risk. ITW 2008: 247-257 - 2006
- [c7]Mokshay Madiman, Andrew R. Barron:
The Monotonicity of Information in the Central Limit Theorem and Entropy Power Inequalities. ISIT 2006: 1021-1025 - 2005
- [c6]Gilbert Leung, Andrew R. Barron:
Combining least-squares regressions: an upper-bound on mean-squared error. ISIT 2005: 1711-1715 - 2001
- [c5]Gerald H. L. Cheang, Andrew R. Barron:
Penalized least squares, model selection, convex hull classes and neural nets. ESANN 2001: 371-376 - 1999
- [c4]Gerald H. L. Cheang, Andrew R. Barron:
Estimation with two hidden layer neural nets. IJCNN 1999: 375-378 - [c3]Jonathan Q. Li, Andrew R. Barron:
Mixture Density Estimation. NIPS 1999: 279-285 - 1997
- [c2]Andrew R. Barron:
Information Theory in Probability, Statistics, Learning, and Neural Nets (Abstract). COLT 1997: 1 - 1991
- [c1]Andrew R. Barron:
Approximation and Estimation Bounds for Artificial Neural Networks. COLT 1991: 243-249
Informal and Other Publications
- 2024
- [i14]Jun'ichi Takeuchi, Andrew R. Barron:
Asymptotically Minimax Regret by Bayes Mixtures. CoRR abs/2406.17929 (2024) - [i13]Curtis McDonald, Andrew R. Barron:
Log-Concave Coupling for Sampling Neural Net Posteriors. CoRR abs/2407.18802 (2024) - 2023
- [i12]Kohei Miyamoto, Andrew R. Barron, Jun'ichi Takeuchi:
Improved MDL Estimators Using Fiber Bundle of Local Exponential Families for Non-exponential Families. CoRR abs/2311.03852 (2023) - 2022
- [i11]Curtis McDonald, Andrew R. Barron:
Proposal of a Score Based Approach to Sampling Using Monte Carlo Estimation of Score and Oracle Access to Target Density. CoRR abs/2212.03325 (2022) - 2019
- [i10]Andrew R. Barron, Jason M. Klusowski:
Complexity, Statistical Risk, and Metric Entropy of Deep Nets Using Total Path Variation. CoRR abs/1902.00800 (2019) - [i9]Ramji Venkataramanan, Sekhar Tatikonda, Andrew R. Barron:
Sparse Regression Codes. CoRR abs/1911.00771 (2019) - 2018
- [i8]Andrew R. Barron, Jason M. Klusowski:
Approximation and Estimation for High-Dimensional Deep Learning Networks. CoRR abs/1809.03090 (2018) - 2017
- [i7]Jason M. Klusowski, Andrew R. Barron:
Minimax Lower Bounds for Ridge Combinations Including Neural Nets. CoRR abs/1702.02828 (2017) - 2014
- [i6]Xiao Yang, Andrew R. Barron:
Large Alphabet Compression and Predictive Distributions through Poissonization and Tilting. CoRR abs/1401.3760 (2014) - [i5]Andrew R. Barron, Teemu Roos, Kazuho Watanabe:
Bayesian Properties of Normalized Maximum Likelihood and its Fast Computation. CoRR abs/1401.7116 (2014) - 2012
- [i4]Antony Joseph, Andrew R. Barron:
Fast Sparse Superposition Codes have Exponentially Small Error Probability for R < C. CoRR abs/1207.2406 (2012) - 2010
- [i3]Andrew R. Barron, Antony Joseph:
Least Squares Superposition Codes of Moderate Dictionary Size, Reliable at Rates up to Capacity. CoRR abs/1006.3780 (2010) - [i2]Andrew R. Barron, Antony Joseph:
Toward Fast Reliable Communication at Rates Near Capacity with Gaussian Noise. CoRR abs/1006.3870 (2010) - 2006
- [i1]Mokshay M. Madiman, Andrew R. Barron:
Generalized Entropy Power Inequalities and Monotonicity Properties of Information. CoRR abs/cs/0605047 (2006)
Coauthor Index
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