Accelerating LLM Inference with Staged Speculative Decoding

no code implementations • 8 Aug 2023 • Benjamin Spector, Chris Re

Recent advances with large language models (LLM) illustrate their diverse capabilities.

Weak Supervision for Time Series: Wearable Sensor Classification with Limited Labeled Data

no code implementations • 25 Mar 2019 • Saelig Khattar, Hannah O’Day, Paroma Varma, Jason Fries, Jen Hicks, Scott Delp, Helen Bronte-Stewart, Chris Re

Using modern deep learning models to make predictions on time series data from wearable sensors generally requires large amounts of labeled data.

Time Series Time Series Analysis

Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark

no code implementations • 4 Jun 2018 • Cody Coleman, Daniel Kang, Deepak Narayanan, Luigi Nardi, Tian Zhao, Jian Zhang, Peter Bailis, Kunle Olukotun, Chris Re, Matei Zaharia

In this work, we analyze the entries from DAWNBench, which received optimized submissions from multiple industrial groups, to investigate the behavior of TTA as a metric as well as trends in the best-performing entries.

Benchmarking BIG-bench Machine Learning

CYCLADES: Conflict-free Asynchronous Machine Learning

1 code implementation • NeurIPS 2016 • Xinghao Pan, Maximilian Lam, Stephen Tu, Dimitris Papailiopoulos, Ce Zhang, Michael. I. Jordan, Kannan Ramchandran, Chris Re, Benjamin Recht

We present CYCLADES, a general framework for parallelizing stochastic optimization algorithms in a shared memory setting.

BIG-bench Machine Learning Stochastic Optimization