356 citations · 418 across the 5 of their papers we have counts for
5 papers
A Sampling Theory Perspective of Graph-based Semi-supervised Learning
Aamir Anis, Aly El Gamal, Salman Avestimehr +1
Graph-based methods have been quite successful in solving unsupervised and semi-supervised learning problems, as they provide a means to capture the underlying geometry of the data…
Efficient Sampling Set Selection for Bandlimited Graph Signals Using Graph Spectral Proxies
Aamir Anis, Akshay Gadde, Antonio Ortega
We study the problem of selecting the best sampling set for bandlimited reconstruction of signals on graphs. A frequency domain representation for graph signals can be defined usin…
Asymptotic Justification of Bandlimited Interpolation of Graph signals for Semi-Supervised Learning
Aamir Anis, Aly El Gamal, A. Salman Avestimehr +1
Graph-based methods play an important role in unsupervised and semi-supervised learning tasks by taking into account the underlying geometry of the data set. In this paper, we cons…
Active Semi-Supervised Learning Using Sampling Theory for Graph Signals
Akshay Gadde, Aamir Anis, Antonio Ortega
We consider the problem of offline, pool-based active semi-supervised learning on graphs. This problem is important when the labeled data is scarce and expensive whereas unlabeled…
Maximum-likelihood coherent-state quantum process tomography
Aamir Anis, A. I. Lvovsky
Coherent-state quantum process tomography (csQPT) is a method of completely characterizing a quantum-optical "black box" by probing it with coherent states and performing homodyne…