2.3k citations · 4.7k across the 64 of their papers we have counts for
6 papers · 1 filter
Express: Lowering the Cost of Metadata-hiding Communication with Cryptographic Privacy
Saba Eskandarian, Henry Corrigan-Gibbs, Matei Zaharia +1
Existing systems for metadata-hiding messaging that provide cryptographic privacy properties have either high communication costs, high computation costs, or both. In this paper, w…
MLPerf Training Benchmark
Peter Mattson, Christine Cheng, Cody Coleman +34
Machine learning (ML) needs industry-standard performance benchmarks to support design and competitive evaluation of the many emerging software and hardware solutions for ML. But M…
Spectral Lower Bounds on the I/O Complexity of Computation Graphs
Saachi Jain, Matei Zaharia
We consider the problem of finding lower bounds on the I/O complexity of arbitrary computations in a two level memory hierarchy. Executions of complex computations can be formalize…
Selection via Proxy: Efficient Data Selection for Deep Learning
Cody Coleman, Christopher Yeh, Stephen Mussmann +5
Data selection methods, such as active learning and core-set selection, are useful tools for machine learning on large datasets. However, they can be prohibitively expensive to app…
Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference
Peter Kraft, Daniel Kang, Deepak Narayanan +3
Systems for ML inference are widely deployed today, but they typically optimize ML inference workloads using techniques designed for conventional data serving workloads and miss cr…
MLSys: The New Frontier of Machine Learning Systems
Alexander Ratner, Dan Alistarh, Gustavo Alonso +66
Machine learning (ML) techniques are enjoying rapidly increasing adoption. However, designing and implementing the systems that support ML models in real-world deployments remains…