Andrew R. Barron

58 papers A* 2B 20Journal 35Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Asymptotically Minimax Regret by Bayes Mixtures. CoRR Jun'ichi Takeuchi, Andrew R. Barron
2024	B	`conf`	Log-Concave Coupling for Sampling Neural Net Posteriors. ISIT Curtis McDonald, Andrew R. Barron
2024	J	`jnl`	Log-Concave Coupling for Sampling Neural Net Posteriors. CoRR Curtis McDonald, Andrew R. Barron
2023	J	`jnl`	Improved MDL Estimators Using Fiber Bundle of Local Exponential Families for Non-exponential Families. CoRR Kohei Miyamoto, Andrew R. Barron, Jun'ichi Takeuchi
2022	J	`jnl`	Proposal of a Score Based Approach to Sampling Using Monte Carlo Estimation of Score and Oracle Access to Target Density. CoRR Curtis McDonald, Andrew R. Barron
2019	J	`jnl`	Complexity, Statistical Risk, and Metric Entropy of Deep Nets Using Total Path Variation. CoRR Andrew R. Barron, Jason M. Klusowski
2019	B	`conf`	Improved MDL Estimators Using Local Exponential Family Bundles Applied to Mixture Families. ISIT Kohei Miyamoto, Andrew R. Barron, Jun'ichi Takeuchi
2019	J	`jnl`	Sparse Regression Codes. CoRR Ramji Venkataramanan, Sekhar Tatikonda, Andrew R. Barron
2019	J	`jnl`	Sparse Regression Codes. Found. Trends Commun. Inf. Theory Ramji Venkataramanan, Sekhar Tatikonda, Andrew R. Barron
2018	J	`jnl`	Approximation and Estimation for High-Dimensional Deep Learning Networks. CoRR Andrew R. Barron, Jason M. Klusowski
2018	J	`jnl`	Approximation by Combinations of ReLU and Squared ReLU Ridge Functions With ℓ IEEE Trans. Inf. Theory Jason M. Klusowski, Andrew R. Barron
2017	J	`jnl`	Minimax Compression and Large Alphabet Approximation Through Poissonization and Tilting. IEEE Trans. Inf. Theory Xiao Yang, Andrew R. Barron
2017	J	`jnl`	Minimax Lower Bounds for Ridge Combinations Including Neural Nets. CoRR Jason M. Klusowski, Andrew R. Barron
2017	B	`conf`	Minimax lower bounds for ridge combinations including neural nets. ISIT Jason M. Klusowski, Andrew R. Barron
2014	B	`conf`	Asymptotically minimax regret for models with hidden variables. ISIT Jun'ichi Takeuchi, Andrew R. Barron
2014	J	`jnl`	Bayesian Properties of Normalized Maximum Likelihood and its Fast Computation. CoRR Andrew R. Barron, Teemu Roos, Kazuho Watanabe
2014	B	`conf`	Bayesian properties of normalized maximum likelihood and its fast computation. ISIT Andrew R. Barron, Teemu Roos, Kazuho Watanabe
2014	B	`conf`	Compression and predictive distributions for large alphabet i.i.d and Markov models. ISIT Xiao Yang, Andrew R. Barron
2014	J	`jnl`	Fast Sparse Superposition Codes Have Near Exponential Error Probability for $R<{\cal C}$. IEEE Trans. Inf. Theory Antony Joseph, Andrew R. Barron
2014	B	`conf`	Information theoretic validity of penalized likelihood. ISIT Sabyasachi Chatterjee, Andrew R. Barron
2014	J	`jnl`	Large Alphabet Compression and Predictive Distributions through Poissonization and Tilting. CoRR Xiao Yang, Andrew R. Barron
2014	B	`conf`	Stochastic Complexity for tree models. ITW Jun'ichi Takeuchi, Andrew R. Barron
2013	B	`conf`	Asymptotically minimax regret by Bayes mixtures for non-exponential families. ITW Jun'ichi Takeuchi, Andrew R. Barron
2013	J	`jnl`	Properties of Jeffreys Mixture for Markov Sources. IEEE Trans. Inf. Theory Jun'ichi Takeuchi, Tsutomu Kawabata, Andrew R. Barron
2012	J	`jnl`	Fast Sparse Superposition Codes have Exponentially Small Error Probability for R < C CoRR Antony Joseph, Andrew R. Barron
2012	B	`conf`	High-rate sparse superposition codes with iteratively optimal estimates. ISIT Andrew R. Barron, Sanghee Cho
2012	J	`jnl`	Introduction to the Issue on Signal Processing Methods in Finance and Electronic Trading. IEEE J. Sel. Top. Signal Process. Ali N. Akansu, Sanjeev R. Kulkarni, Marco Avellaneda, Andrew R. Barron
2012	J	`jnl`	Least Squares Superposition Codes of Moderate Dictionary Size Are Reliable at Rates up to Capacity. IEEE Trans. Inf. Theory Antony Joseph, Andrew R. Barron
2011	B	`conf`	Analysis of fast sparse superposition codes. ISIT Andrew R. Barron, Antony Joseph
2011	B	`conf`	Polar coding schemes for the AWGN channel. ISIT Emmanuel Abbe, Andrew R. Barron
2010	J	`jnl`	Least Squares Superposition Codes of Moderate Dictionary Size, Reliable at Rates up to Capacity CoRR Andrew R. Barron, Antony Joseph
2010	B	`conf`	Least squares superposition codes of moderate dictionary size, reliable at rates up to capacity. ISIT Andrew R. Barron, Antony Joseph
2010	J	`jnl`	Toward Fast Reliable Communication at Rates Near Capacity with Gaussian Noise CoRR Andrew R. Barron, Antony Joseph
2010	B	`conf`	Toward fast reliable communication at rates near capacity with Gaussian noise. ISIT Andrew R. Barron, Antony Joseph
2009	B	`conf`	A model for pricing data bundles based on minimax risks for estimation of a location parameter. ITW Mokshay M. Madiman, Andrew R. Barron, Abram Kagan, Tinghui Yu
2008	B	`conf`	MDL, penalized likelihood, and statistical risk. ITW Andrew R. Barron, Cong Huang, Jonathan Q. Li, Xi Luo
2007	J	`jnl`	Generalized Entropy Power Inequalities and Monotonicity Properties of Information. IEEE Trans. Inf. Theory Mokshay M. Madiman, Andrew R. Barron
2006	J	`jnl`	Generalized Entropy Power Inequalities and Monotonicity Properties of Information CoRR Mokshay M. Madiman, Andrew R. Barron
2006	J	`jnl`	Information Theory and Mixing Least-Squares Regressions. IEEE Trans. Inf. Theory Gilbert Leung, Andrew R. Barron
2006	B	`conf`	The Monotonicity of Information in the Central Limit Theorem and Entropy Power Inequalities. ISIT Mokshay Madiman, Andrew R. Barron
2005	B	`conf`	Combining least-squares regressions: an upper-bound on mean-squared error. ISIT Gilbert Leung, Andrew R. Barron
2004	J	`jnl`	Exact minimax strategies for predictive density estimation, data compression, and model selection. IEEE Trans. Inf. Theory Feng Liang, Andrew R. Barron
2001	B	`conf`	Penalized least squares, model selection, convex hull classes and neural nets. ESANN Gerald H. L. Cheang, Andrew R. Barron
2000	J	`jnl`	Asymptotic minimax regret for data compression, gambling, and prediction. IEEE Trans. Inf. Theory Qun Xie, Andrew R. Barron
1999	B	`conf`	Estimation with two hidden layer neural nets. IJCNN Gerald H. L. Cheang, Andrew R. Barron
1999	—	`conf`	Mixture Density Estimation. NIPS Jonathan Q. Li, Andrew R. Barron
1998	J	`jnl`	An Asymptotic Property of Model Selection Criteria. IEEE Trans. Inf. Theory Yuhong Yang, Andrew R. Barron
1998	J	`jnl`	The Minimum Description Length Principle in Coding and Modeling. IEEE Trans. Inf. Theory Andrew R. Barron, Jorma Rissanen, Bin Yu
1997	A*	`conf`	Information Theory in Probability, Statistics, Learning, and Neural Nets (Abstract). COLT Andrew R. Barron
1997	J	`jnl`	Minimax redundancy for the class of memoryless sources. IEEE Trans. Inf. Theory Qun Xie, Andrew R. Barron
1994	J	`jnl`	Approximation and Estimation Bounds for Artificial Neural Networks. Mach. Learn. Andrew R. Barron
1993	J	`jnl`	Universal approximation bounds for superpositions of a sigmoidal function. IEEE Trans. Inf. Theory Andrew R. Barron
1992	J	`jnl`	Distribution estimation consistent in total variation and in two types of information divergence. IEEE Trans. Inf. Theory Andrew R. Barron, László Györfi, Edward C. van der Meulen
1991	A*	`conf`	Approximation and Estimation Bounds for Artificial Neural Networks. COLT Andrew R. Barron
1991	J	`jnl`	Correction to 'Minimum Complexity Density Estimation'. IEEE Trans. Inf. Theory Andrew R. Barron, Thomas M. Cover
1991	J	`jnl`	Minimum complexity density estimation. IEEE Trans. Inf. Theory Andrew R. Barron, Thomas M. Cover
1990	J	`jnl`	Information-theoretic asymptotics of Bayes methods. IEEE Trans. Inf. Theory Bertrand S. Clarke, Andrew R. Barron
1988	J	`jnl`	A bound on the financial value of information. IEEE Trans. Inf. Theory Andrew R. Barron, Thomas M. Cover