5 citations · 7 across the 5 of their papers we have counts for
5 papers
Scaling ML Products At Startups: A Practitioner's Guide
Atul Dhingra, Gaurav Sood
How do you scale a machine learning product at a startup? In particular, how do you serve a greater volume, velocity, and variety of queries cost-effectively? We break down costs i…
Instate: Predicting the State of Residence From Last Name
Atul Dhingra, Gaurav Sood
India has twenty-two official languages. Serving such a diverse language base is a challenge for survey statisticians, call center operators, software developers, and other such se…
QBF Merge Resolution is powerful but unnatural
Meena Mahajan, Gaurav Sood
The Merge Resolution proof system (M-Res) for QBFs, proposed by Beyersdorff et al. in 2019, explicitly builds partial strategies inside refutations. The original motivation for thi…
Hard QBFs for Merge Resolution
Olaf Beyersdorff, Joshua Blinkhorn, Meena Mahajan +2
We prove the first genuine QBF proof size lower bounds for the proof system Merge Resolution (MRes [Olaf Beyersdorff et al., 2020]), a refutational proof system for prenex quantifi…
MaxSAT Resolution and Subcube Sums
Yuval Filmus, Meena Mahajan, Gaurav Sood +1
We study the MaxRes rule in the context of certifying unsatisfiability. We show that it can be exponentially more powerful than tree-like resolution, and when augmented with weaken…