Variational Inference for DPGMM with Coresets

Olivier Bachem
Olivier Bachem
Andreas Krause
Andreas Krause

2017.

Cited by: 0|Views1

Abstract:

Performing estimation and inference on massive datasets under time and memory constraints is a critical task in machine learning. One approach to tackle these challenges is offered by coresets, succinct data summaries that come with strong theoretical guarantees, and can operate under computational resource restrictions. In this work, we ...More

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