42 citations · 44 across the 8 of their papers we have counts for
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cs.IT2021
Fundamental limits of over-the-air optimization: Are analog schemes optimal?
Shubham K Jha, Prathamesh Mayekar, Himanshu Tyagi
We consider over-the-air convex optimization on a dimensional space where coded gradients are sent over an additive Gaussian noise channel with variance . The codewords sa…
math.OC2021★ 1 cited
Information-constrained optimization: can adaptive processing of gradients help?
Jayadev Acharya, Clément L. Canonne, Prathamesh Mayekar +1
We revisit first-order optimization under local information constraints such as local privacy, gradient quantization, and computational constraints limiting access to a few coordin…