3 citations · 14 across the 17 of their papers we have counts for
5 papers · 1 filter
A Theoretical Framework for Learning from Quantum Data
Mohsen Heidari, Arun Padakandla, Wojciech Szpankowski
Over decades traditional information theory of source and channel coding advances toward learning and effective extraction of information from data. We propose to go one step furth…
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…
Learning k-qubit Quantum Operators via Pauli Decomposition
Mohsen Heidari, Wojciech Szpankowski
Motivated by the limited qubit capacity of current quantum systems, we study the quantum sample complexity of -qubit quantum operators, i.e., operations applicable on only o…
Low Complexity Approximate Bayesian Logistic Regression for Sparse Online Learning
Gil I. Shamir, Wojciech Szpankowski
Theoretical results show that Bayesian methods can achieve lower bounds on regret for online logistic regression. In practice, however, such techniques may not be feasible especial…
On maximum-likelihood estimation in the all-or-nothing regime
Luca Corinzia, Paolo Penna, Wojciech Szpankowski +1
We study the problem of estimating a rank-1 additive deformation of a Gaussian tensor according to the \emph{maximum-likelihood estimator} (MLE). The analysis is carried out in the…