- Exact Smoothing Properties of Schrodinger Semigroups \Lambda Archil Gulisashvili
- MAP METHODS FOR MACHINE LEARNING Mark A. Kon, Boston University
- APPROXIMATING FUNCTIONS IN REPRODUCING KERNEL HILBERT SPACES VIA STATISTICAL LEARNING THEORY
- Local Convergence for Wavelet Expansions \Lambda Susan E. Kelly y Mark A. Kon z Louise A. Raphael x
- Linear Algebra. By Peter Lax. John Wiley, 1997, xiv + 250 pp., $89.95. ISBN 0-471-11111-2. Reviewed by Mark A. Kon
- Smoothing Gene Expression Using Biological Networks Yue Fan, Mark Kon
- Building Transcription Factor Classifiers and Discovering Relevant Biological Features
- Review of Wavelet Theory and Harmonic Analysis in Applied Sciences, C.E. D'Atellis and E.M. Fernandez-Berdaguer, Ed.
- SVMotif: A Machine Learning Motif Algorithm Mark Kon , Yue Fan
- MA 717 Functional Analysis Room 259, MCS Building Cummington St."""
- PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY
- Neural Networks, Radial Basis Functions, and Complexity Mark A. Kon 1
- Pointwise Wavelet Convergence in Besov and Uniformly Local Sobolev Spaces
- Communications in Mathematical Analysis Special Volume in Honor of Prof. Peter Lax
- Exact Smoothing Properties of Schrodinger Semigroups Archil Gulisashvili
- Review of , by M. Holschneider.Wavelets: An Analysis Tool For , by Mark A. KonPhysics Today
- Reed and Simon: Some typographic errors P. 75, line -9: The extension of to ...-~]
- Neural Networks and Radial Basis Functions 1. Neural network theory
- Complexity of Neural Network Approximation with Limited Information: a Worst Case Approach
- Neural Networks, Radial Basis Functions, and Complexity Mark A. Kon1
- A Characterization of Wavelet Convergence in Sobolev Mark A. Kon 1
- SUPNORM CONVERGENCE RATES OF WAVELET EXPANSIONS IN BESOV SPACES
- MA 713 SPRING 2006 M. KON Prof. Mark Kon
- Complexity of Predictive Neural Networks Mark A. Kon
- Machine learning methods for transcription data integration D. T. Holloway M. Kon C. DeLisi
- Convergence Rates of Multiscale and Wavelet Expansions Mark A. Kon Louise Arakelian Raphael
- Complexity of Predictive Neural Networks Mark A. Kon #
- Learning Methods for DNA Binding in Computational Biology
- A CONTINOUS COMPLEXITY ANALYSIS OF SUPPORT VECTOR MACHINES
- Can Neural Network and Statistical Learning Theory be Formulated in terms
- Basics of Wavelets Referenc Daubechies (Ten Lectures on ; Orthonormal Bases ofes: I. Wavelets
- Ensemble Machine Methods for DNA Binding Yue Fan and Mark A. Kon
- Regulatory Analysis for Exploring Human Disease Progression
- Learning Methods for DNA Binding in Computational Biology Mark Kon , Dustin Holloway, Yue Fan, Chaitanya Sai and Charles DeLisi
- Complexity of Neural Network Approximation with Limited Information: a Worst Case Approach
- Complexity of Regularization RBF Networks Mark A. Kon
- Review by Mark A. Kon, Boston University Complexity and Information, by J.F. Traub and A.G. Werschulz, Cambridge
- Review of Introduction to Algebraic and Constructive Quantum Field Theory, by J.C. Baez, I.E. Segal, and Z. Zhou.
- PLEASE POST OR ANNOUNCE
- Wavelets -constructions and applications 1. Other constructions
- Neural Networks Preliminaries: Notation: Write , and in integralsB oe B B B " # .
- Problem Set 7 Due Thurs. 3/26/10
- Predictive Genomics, Biology, Medicine Learning theory: SLT what is it?
- Review of "Oscillations in Neural Systems", D. Levine, Ed. M. Kon, Boston University and A. Przybyszewski, University of Massachusetts
- Pointwise Convergence of Wavelet Expansions \Lambda Susan E. Kelly y Mark A. Kon z Louise A. Raphael x
- Information-based nonlinear approximation: an average case setting
- Notes on the paper by Park and Sandberg: Page 305, bottom: The convolution operation * for two functions f(x) and g(x) on is an`r
- Machine Learning and Kernel Methods Machine Learning
- SUP-NORM CONVERGENCE RATES OF WAVELET EXPANSIONS IN BESOV SPACES
- MA 242 -M. Kon Extra Credit Assignment 2
- EXTENDING GIROSI'S APPROXIMATION ESTIMATES FOR FUNCTIONS IN SOBOLEV SPACES
- vol. 174, no. 2 the american naturalist august 2009 A New Phylogenetic Diversity Measure Generalizing
- Machine Methods for Identifying DNA Binding Sites
- Convergence Rates of Multiscale and Wavelet Expansions Mark A. Kon1
- PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY
- 1. Vectors and forces: Space shuttle: one rocket pushes upward with force of 8 newtons and
- A Characterization of Wavelet Convergence in Sobolev Mark A. Kon1
- Machine Learning for Regulatory Analysis and Transcription Factor Target Prediction in Yeast
- BULLETIN (New Series) OF THE AMERICAN MATHEMATICAL SOCIETY
- MA 242 Spring 2011 Prof. Mark Kon
