Ashok V. Makkuva — accepted AI-conference papers

2021

KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning

Ashok V Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath

ICML 2021spotlight

Landmark codes underpin reliable physical layer communication, e.g., Reed-Muller, BCH, Convolution, Turbo, LDPC, and Polar codes: each is a linear code and represents a mathematical breakthrough. The impact on humanity is huge: each of these codes has been used in global wireless communication stand…

Cited by 47 Source ↗PDF ↗code ↗Scholar ↗

2019

Learning One-hidden-layer Neural Networks under General Input Distributions

Weihao Gao, Ashok V. Makkuva, Sewoong Oh, Pramod Viswanath

AISTATS 2019poster

Significant advances have been made recently on training neural networks, where the main challenge is in solving an optimization problem with abundant critical points. However, existing approaches to address this issue crucially rely on a restrictive assumption: the training data is drawn from a Gau…

Cited by 35 Source ↗PDF ↗Scholar ↗