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BLaST: High Performance Inference and Pretraining using BLock Sparse Transformers
Patrik Okanovic, Sameer Deshmukh, Grzegorz Kwasniewski +8
The energy consumption of large-scale ML models is dominated by data movement, shuffling billions of parameters across memory hierarchies and data centers. Sparsification offers a…
All models are wrong, some are useful: Model Selection with Limited Labels
Patrik Okanovic, Andreas Kirsch, Jannes Kasper +3
We introduce MODEL SELECTOR, a framework for label-efficient selection of pretrained classifiers. Given a pool of unlabeled target data, MODEL SELECTOR samples a small subset of hi…
EntryPrune: Neural Network Feature Selection using First Impressions
Felix Zimmer, Patrik Okanovic, Torsten Hoefler
There is an ongoing effort to develop feature selection algorithms to improve interpretability, reduce computational resources, and minimize overfitting in predictive models. Neura…