23 citations · 32 across the 4 of their papers we have counts for
5 papers
Revisiting general source condition in learning over a Hilbert space
Naveen Gupta, S. Sivananthan
In Learning Theory, the smoothness assumption on the target function (known as source condition) is a key factor in establishing theoretical convergence rates for an estimator. The…
Convergence Analysis of regularised Nyström method for Functional Linear Regression
Naveen Gupta, Sivananthan Sampath
The functional linear regression model has been widely studied and utilized for dealing with functional predictors. In this paper, we study the Nyström subsampling method, a strate…
Random Sampling in reproducing kernel subspaces of
Dhiraj Patel, Sivananthan Sampath
In this paper, we study random sampling on reproducing kernel space , which is a range of an idempotent integral operator. Under certain decay condition on the integral kernel,…
Manifold regularization based on Nystr{ö}m type subsampling
Abhishake Rastogi, Sivananthan Sampath
In this paper, we study the Nystr{ö}m type subsampling for large scale kernel methods to reduce the computational complexities of big data. We discuss the multi-penalty regularizat…
Optimal rates for the regularized learning algorithms under general source condition
Abhishake Rastogi, Sivananthan Sampath
We consider the learning algorithms under general source condition with the polynomial decay of the eigenvalues of the integral operator in vector-valued function setting. We discu…