5 citations · 13 across the 27 of their papers we have counts for
4 papers · 1 filter
Agnostic PAC Learning of k-juntas Using L2-Polynomial Regression
Mohsen Heidari, Wojciech Szpankowski
Many conventional learning algorithms rely on loss functions other than the natural 0-1 loss for computational efficiency and theoretical tractability. Among them are approaches ba…
Expected Worst Case Regret via Stochastic Sequential Covering
Changlong Wu, Mohsen Heidari, Ananth Grama +1
We study the problem of sequential prediction and online minimax regret with stochastically generated features under a general loss function. We introduce a notion of expected wors…
Precise Regret Bounds for Log-loss via a Truncated Bayesian Algorithm
Changlong Wu, Mohsen Heidari, Ananth Grama +1
We study the sequential general online regression, known also as the sequential probability assignments, under logarithmic loss when compared against a broad class of experts. We f…
On Agnostic PAC Learning using -polynomial Regression and Fourier-based Algorithms
Mohsen Heidari, Wojciech Szpankowski
We develop a framework using Hilbert spaces as a proxy to analyze PAC learning problems with structural properties. We consider a joint Hilbert space incorporating the relation bet…