Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
This paper addresses the need for nonlinear programming algorithms that provide fast local convergence guarantees no matter if a problem is feasible or infeasible. We present an a...
Many image denoising methods can be characterized as minimizing "loss + penalty," where the "loss" measures the fidelity of the denoised image to the data, and ...
A Schnorr test relative to some oracle A may informally be called "universal" if it covers all Schnorr tests. Since no true universal Schnorr test exists, such an A cann...