3 papers
math.NA2025
Multiscale Methods for Discretized Continuous Optimization: Convergence and Cost Analysis
Nicholas J. E. Richardson, Noah Marusenko, Michael P. Friedlander
Discretized versions of optimization problems over continuous arguments are routinely solved at a single fine resolution, incurring a per-iteration cost that grows, often superline…
eess.SP2022
SRMD: Sparse Random Mode Decomposition
Nicholas Richardson, Hayden Schaeffer, Giang Tran
Signal decomposition and multiscale signal analysis provide many useful tools for time-frequency analysis. We proposed a random feature method for analyzing time-series data by con…
cs.LG2021
Adaptive Group Lasso Neural Network Models for Functions of Few Variables and Time-Dependent Data
Lam Si Tung Ho, Nicholas Richardson, Giang Tran
In this paper, we propose an adaptive group Lasso deep neural network for high-dimensional function approximation where input data are generated from a dynamical system and the tar…