Publications (27)
WONDERBREAD: A Benchmark for Evaluating Multimodal Foundation Models on Business Process Management Tasks
Michael Wornow, Avanika Narayan, Ben Viggiano +15
Existing ML benchmarks lack the depth and diversity of annotations needed for evaluating models on business process management (BPM) tasks. BPM is the practice of documenting, meas…
Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees
Jue Wang, Binhang Yuan, Luka Rimanic +5
Communication compression is a crucial technique for modern distributed learning systems to alleviate their communication bottlenecks over slower networks. Despite recent intensive…
Infrastructure for Usable Machine Learning: The Stanford DAWN Project
Peter Bailis, Kunle Olukotun, Christopher Re +1
Despite incredible recent advances in machine learning, building machine learning applications remains prohibitively time-consuming and expensive for all but the best-trained, best…
Sparse Recovery for Orthogonal Polynomial Transforms
Anna Gilbert, Albert Gu, Christopher Re +2
In this paper we consider the following sparse recovery problem. We have query access to a vector $\vx \in \R^N$ such that $\vhx = \vF \vx$ is -sparse (or nearly -sparse) for…
Beneath the valley of the noncommutative arithmetic-geometric mean inequality: conjectures, case-studies, and consequences
Benjamin Recht, Christopher Re
Randomized algorithms that base iteration-level decisions on samples from some pool are ubiquitous in machine learning and optimization. Examples include stochastic gradient descen…
GRIP: A Graph Neural Network Accelerator Architecture
Kevin Kiningham, Christopher Re, Philip Levis
We present GRIP, a graph neural network accelerator architecture designed for low-latency inference. AcceleratingGNNs is challenging because they combine two distinct types of comp…