13 citations · 22 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Addition is almost all you need: Compressing large language models with double binary factorization
Vladimír Boža, Vladimír Macko
Binary quantization approaches, which replace weight matrices with binary matrices and substitute costly multiplications with cheaper additions, offer a computationally efficient a…
cs.LG2019★ 13 cited
AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles
Charles Weill, Javier Gonzalvo, Vitaly Kuznetsov +9
AdaNet is a lightweight TensorFlow-based (Abadi et al., 2015) framework for automatically learning high-quality ensembles with minimal expert intervention. Our framework is inspire…
cs.LG2019★ 9 cited
Improving Neural Architecture Search Image Classifiers via Ensemble Learning
Vladimir Macko, Charles Weill, Hanna Mazzawi +1
Finding the best neural network architecture requires significant time, resources, and human expertise. These challenges are partially addressed by neural architecture search (NAS)…