Hrushikesh N. Mhaskar

Publication Activity (10 Years)

Years Active: 1996-2024
Publications (10 Years): 40

Top Topics

Discriminative Models

Manifold Learning

Function Approximation

Top Venues

Frontiers Appl. Math. Stat.

Neural Networks

Int. J. Autom. Comput.

Publications

Michael McKenna, Hrushikesh N. Mhaskar, Richard G. Spencer
Inversion of the Laplace Transform of Point Masses. CoRR (2024)
Hrushikesh N. Mhaskar
Approximation by non-symmetric networks for cross-domain learning. CoRR (2023)
Quoc Thong Le Gia, Hrushikesh N. Mhaskar
Numerical solutions to an inverse problem for a non-linear Helmholtz equation. CoRR (2023)
Hrushikesh N. Mhaskar, Tong Mao
Tractability of approximation by general shallow networks. CoRR (2023)
Katarina Doctor, Tong Mao, Hrushikesh N. Mhaskar
Encoding of data sets and algorithms. CoRR (2023)
Hrushikesh N. Mhaskar
Local approximation of operators. CoRR (2022)
Eric Mason, Hrushikesh N. Mhaskar, Adam Guo
A manifold learning approach for gesture recognition from micro-Doppler radar measurements. Neural Networks 152 (2022)
Ningning Han, Hrushikesh N. Mhaskar, Charles K. Chui
Theory-Inspired Deep Network for Instantaneous-Frequency Extraction and Subsignals Recovery From Discrete Blind-Source Data. IEEE Trans. Neural Networks Learn. Syst. 33 (8) (2022)
Hrushikesh N. Mhaskar, Sergei V. Pereverzyev, Maria D. van der Walt
A function approximation approach to the prediction of blood glucose levels. CoRR (2021)
Srinjoy Das, Hrushikesh N. Mhaskar, Alexander Cloninger
Kernel distance measures for time series, random fields and other structured data. CoRR (2021)
Srinjoy Das, Hrushikesh N. Mhaskar, Alexander Cloninger
Kernel Distance Measures for Time Series, Random Fields and Other Structured Data. Frontiers Appl. Math. Stat. 7 (2021)
Eric Mason, Hrushikesh N. Mhaskar, Adam Guo
A manifold learning approach for gesture identification from micro-Doppler radar measurements. CoRR (2021)
Hrushikesh N. Mhaskar, Sergei V. Pereverzyev, Maria D. van der Walt
A Function Approximation Approach to the Prediction of Blood Glucose Levels. Frontiers Appl. Math. Stat. 7 (2021)
Hrushikesh N. Mhaskar, Xiuyuan Cheng, Alexander Cloninger
A Witness Function Based Construction of Discriminative Models Using Hermite Polynomials. Frontiers Appl. Math. Stat. 6 (2020)
Hrushikesh N. Mhaskar
Dimension independent bounds for general shallow networks. Neural Networks 123 (2020)
Alexander Cloninger, Hrushikesh N. Mhaskar
Cautious Active Clustering. CoRR (2020)
Charles K. Chui, Ningning Han, Hrushikesh N. Mhaskar
Theory inspired deep network for instantaneous-frequency extraction and signal components recovery from discrete blind-source data. CoRR (2020)
Hrushikesh N. Mhaskar
A direct approach for function approximation on data defined manifolds. Neural Networks 132 (2020)
Hrushikesh N. Mhaskar, Tomaso A. Poggio
An analysis of training and generalization errors in shallow and deep networks. Neural Networks 121 (2020)
Alex Cloninger, Hrushikesh N. Mhaskar
A low discrepancy sequence on graphs. CoRR (2020)
Hrushikesh N. Mhaskar
Kernel-Based Analysis of Massive Data. Frontiers Appl. Math. Stat. 6 (2020)
Hrushikesh N. Mhaskar
Kernel based analysis of massive data. CoRR (2020)
Hrushikesh N. Mhaskar, Alex Cloninger, Xiuyuan Cheng
A witness function based construction of discriminative models using Hermite polynomials. CoRR (2019)
Hrushikesh N. Mhaskar
Deep Gaussian networks for function approximation on data defined manifolds. CoRR (2019)
Hrushikesh N. Mhaskar
Dimension independent bounds for general shallow networks. CoRR (2019)
Hrushikesh N. Mhaskar, Tomaso A. Poggio
Function approximation by deep networks. CoRR (2019)
Hrushikesh N. Mhaskar
Super-resolution meets machine learning: approximation of measures. CoRR (2019)
Hrushikesh N. Mhaskar, Sergei V. Pereverzyev, Vasyl Yu. Semenov, Evgeniya V. Semenova
Data Based Construction of Kernels for Semi-Supervised Learning With Less Labels. Frontiers Appl. Math. Stat. 5 (2019)
Hrushikesh N. Mhaskar
Function approximation with zonal function networks with activation functions analogous to the rectified linear unit functions. J. Complex. 51 (2019)
Tomaso A. Poggio, Kenji Kawaguchi, Qianli Liao, Brando Miranda, Lorenzo Rosasco, Xavier Boix, Jack Hidary, Hrushikesh N. Mhaskar
Theory of Deep Learning III: explaining the non-overfitting puzzle. CoRR (2018)
Hrushikesh N. Mhaskar, Tomaso A. Poggio
An analysis of training and generalization errors in shallow and deep networks. CoRR (2018)
Charles K. Chui, Hrushikesh N. Mhaskar
Deep Nets for Local Manifold Learning. Frontiers Appl. Math. Stat. 4 (2018)
Hrushikesh N. Mhaskar, Sergei V. Pereverzyev, Maria D. van der Walt
A Deep Learning Approach to Diabetic Blood Glucose Prediction. Frontiers Appl. Math. Stat. 3 (2017)
Hrushikesh N. Mhaskar, Qianli Liao, Tomaso A. Poggio
When and Why Are Deep Networks Better Than Shallow Ones? AAAI (2017)
Hrushikesh N. Mhaskar, Sergei V. Pereverzyev, Maria D. van der Walt
A deep learning approach to diabetic blood glucose prediction. CoRR (2017)
Tomaso A. Poggio, Hrushikesh N. Mhaskar, Lorenzo Rosasco, Brando Miranda, Qianli Liao
Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review. Int. J. Autom. Comput. 14 (5) (2017)
Hrushikesh N. Mhaskar
Function approximation with ReLU-like zonal function networks. CoRR (2017)
Hrushikesh N. Mhaskar, Tomaso A. Poggio
Deep vs. shallow networks : An approximation theory perspective. CoRR (2016)
Hrushikesh N. Mhaskar, Qianli Liao, Tomaso A. Poggio
Learning Real and Boolean Functions: When Is Deep Better Than Shallow. CoRR (2016)
Tomaso A. Poggio, Hrushikesh N. Mhaskar, Lorenzo Rosasco, Brando Miranda, Qianli Liao
Why and When Can Deep - but Not Shallow - Networks Avoid the Curse of Dimensionality: a Review. CoRR (2016)
Hrushikesh N. Mhaskar
A generalized diffusion frame for parsimonious representation of functions on data defined manifolds. Neural Networks 24 (4) (2011)
Hrushikesh N. Mhaskar
Eignets for function approximation on manifolds CoRR (2009)
Quoc Thong Le Gia, Hrushikesh N. Mhaskar
Localized Linear Polynomial Operators and Quadrature Formulas on the Sphere. SIAM J. Numer. Anal. 47 (1) (2008)
Kerstin Hesse, Hrushikesh N. Mhaskar, Ian H. Sloan
Quadrature in Besov spaces on the Euclidean sphere. J. Complex. 23 (4-6) (2007)
Mahadevan Ganesh, Hrushikesh N. Mhaskar
Matrix-free Interpolation on the Sphere. SIAM J. Numer. Anal. 44 (3) (2006)
Quoc Thong Le Gia, Hrushikesh N. Mhaskar
Polynomial operators and local approximation of solutions of pseudo-differential equations on the sphere. Numerische Mathematik 103 (2) (2006)
Hrushikesh N. Mhaskar
Neural Networks for Optimal Approximation of Smooth and Analytic Functions. Neural Comput. 8 (1) (1996)