613 citations · 2k across the 113 of their papers we have counts for
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On Data-Dependent Random Features for Improved Generalization in Supervised Learning
Shahin Shahrampour, Ahmad Beirami, Vahid Tarokh
The randomized-feature approach has been successfully employed in large-scale kernel approximation and supervised learning. The distribution from which the random features are draw…
Wavelet Shrinkage and Thresholding based Robust Classification for Brain Computer Interface
Taposh Banerjee, John Choi, Bijan Pesaran +2
A macaque monkey is trained to perform two different kinds of tasks, memory aided and visually aided. In each task, the monkey saccades to eight possible target locations. A classi…
Classification of Local Field Potentials using Gaussian Sequence Model
Taposh Banerjee, John Choi, Bijan Pesaran +2
A problem of classification of local field potentials (LFPs), recorded from the prefrontal cortex of a macaque monkey, is considered. An adult macaque monkey is trained to perform…
On Optimal Generalizability in Parametric Learning
Ahmad Beirami, Meisam Razaviyayn, Shahin Shahrampour +1
We consider the parametric learning problem, where the objective of the learner is determined by a parametric loss function. Employing empirical risk minimization with possibly reg…
Bayesian model comparison with the Hyvärinen score: computation and consistency
Stephane Shao, Pierre E. Jacob, Jie Ding +1
The Bayes factor is a widely used criterion in model comparison and its logarithm is a difference of out-of-sample predictive scores under the logarithmic scoring rule. However, wh…
On the Spectral Norms of Pseudo-Wigner and Related Matrices
Ilya Soloveychik, Vahid Tarokh
We investigate the spectral norms of symmetric matrices from two pseudo-random ensembles. The first is the pseudo-Wigner ensemble introduced in "Pseudo-Wigner Matrices…