1.3k citations · 3.8k across the 222 of their papers we have counts for
6 papers · 2 filters
Kernel Conjugate Gradient Methods with Random Projections
Junhong Lin, Volkan Cevher
We propose and study kernel conjugate gradient methods (KCGM) with random projections for least-squares regression over a separable Hilbert space. Considering two types of random p…
Adversarially Robust Optimization with Gaussian Processes
Ilija Bogunovic, Jonathan Scarlett, Stefanie Jegelka +1
In this paper, we consider the problem of Gaussian process (GP) optimization with an added robustness requirement: The returned point may be perturbed by an adversary, and we requi…
Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces
Junhong Lin, Volkan Cevher
We investigate regularized algorithms combining with projection for least-squares regression problem over a Hilbert space, covering nonparametric regression over a reproducing kern…
Robust Maximization of Non-Submodular Objectives
Ilija Bogunovic, Junyao Zhao, Volkan Cevher
We study the problem of maximizing a monotone set function subject to a cardinality constraint in the setting where some number of elements is deleted from the returned set…
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms
Junhong Lin, Volkan Cevher
We study generalization properties of distributed algorithms in the setting of nonparametric regression over a reproducing kernel Hilbert space (RKHS). We first investigate distrib…
Optimal Rates for Spectral Algorithms with Least-Squares Regression over Hilbert Spaces
Junhong Lin, Alessandro Rudi, Lorenzo Rosasco +1
In this paper, we study regression problems over a separable Hilbert space with the square loss, covering non-parametric regression over a reproducing kernel Hilbert space. We inve…