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Scalable Operator Learning via Nyström Approximation With Denoising Applications
Naveen Gupta, Vaibhav Silmana, S. Sivananthan
In this paper, we study Nyström subsampling for vector-valued regression in vector-valued reproducing kernel Hilbert spaces. Standard kernel methods often suffer from prohibitive c…
Minimax Optimal Estimation of Mean and Covariance Functions with Spectral Regularization
Naveen Gupta, Bharath K Sriperumbudur
Estimation of the mean and covariance functions is a fundamental problem in functional data analysis, particularly for discretely observed functional data. In this work, we study a…
Optimal Rates for Functional Linear Regression with General Regularization
Naveen Gupta, S. Sivananthan, Bharath K. Sriperumbudur
Functional linear regression is one of the fundamental and well-studied methods in functional data analysis. In this work, we investigate the functional linear regression model wit…
Convergence Analysis of Kernel Conjugate Gradient for Functional Linear Regression
Naveen Gupta, S. Sivananthan, Bharath K. Sriperumbudur
In this paper, we discuss the convergence analysis of the conjugate gradient-based algorithm for the functional linear model in the reproducing kernel Hilbert space framework, util…