Author

Adel Javanmard

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Preprint Sep 2026

A Proof of the Most Informative Boolean Function Conjecture

Let $X$ be uniform on $\{-1,1\}^n$, let $Y$ be obtained by passing its coordinates independently through a binary symmetric channel with crossover probability $p$, and let $g:\{-1,1\}^n\to\{0,1\}$ be a Boolean function. We give a computer-assisted proof of the Courtade--Kumar conjecture $I(g(X);Y)\le1-H_2(p)$, where $H...

Zi-Jie Chen, Amin Gohari, Adel Javanmard et al. · 0 citations

#machine learning Preprint Aug 2026

SSTQ:Privacy-Preserving Vector Quantization via Subsampled Stochastic TurboQuant

This work proposes Subsampled Stochastic TurboQuant (SSTQ), a framework that combines overcomplete equal-norm tight frames, coordinate subsampling, and privacy-aware one-dimensional quantization and empirically evaluates SSTQ against established baselines on federated learning tasks using CIFAR-10 and Fashion-MNIST, de...

Adel Javanmard, David P. Woodruff, V. Mirrokni · 0 citations