Christopher Ré

Asynchronous stochastic convex optimization

2015 · arXiv (Cornell University)

We show that asymptotically, completely asynchronous stochastic gradient procedures achieve optimal (even to constant factors) convergence rates for the solution of convex optimization problems under nearly the same conditions required for asymptotic optimality of standard …

The Beckman report on database research

2016 · Communications of the ACM

Database researchers paint big data as a defining challenge. To make the most of the enormous opportunities at hand will require focusing on five research areas.

A Two Pronged Progress in Structured Dense Matrix Multiplication

2016 · arXiv (Cornell University)

Matrix-vector multiplication is one of the most fundamental computing primitives. Given a matrix $A\in\mathbb{F}^{N\times N}$ and a vector $b$, it is known that in the worst case $Θ(N^2)$ operations over $\mathbb{F}$ are needed to compute …

Snorkel MeTaL

2018

Many real-world machine learning problems are challenging to tackle for two reasons: (i) they involve multiple sub-tasks at different levels of granularity; and (ii) they require large volumes of labeled training data. We propose Snorkel …