908 citations · 2.4k across the 149 of their papers we have counts for
3 papers · 1 filter
The ZipML Framework for Training Models with End-to-End Low Precision: The Cans, the Cannots, and a Little Bit of Deep Learning
Hantian Zhang, Jerry Li, Kaan Kara +3
Recently there has been significant interest in training machine-learning models at low precision: by reducing precision, one can reduce computation and communication by one order…
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding
Dan Alistarh, Demjan Grubic, Jerry Li +2
Parallel implementations of stochastic gradient descent (SGD) have received significant research attention, thanks to excellent scalability properties of this algorithm, and to its…
Time-Space Trade-offs in Population Protocols
Dan Alistarh, James Aspnes, David Eisenstat +2
Population protocols are a popular model of distributed computing, in which randomly-interacting agents with little computational power cooperate to jointly perform computational t…