1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Narrowing the Focus: Learned Optimizers for Pretrained Models
Gus Kristiansen, Mark Sandler, Andrey Zhmoginov +4
In modern deep learning, the models are learned by applying gradient updates using an optimizer, which transforms the updates based on various statistics. Optimizers are often hand…
cs.LG2022★ 1 cited
Decentralized Learning with Multi-Headed Distillation
Andrey Zhmoginov, Mark Sandler, Nolan Miller +2
Decentralized learning with private data is a central problem in machine learning. We propose a novel distillation-based decentralized learning technique that allows multiple agent…
cs.LG2017★ 1 cited
EnergyNet: Energy-based Adaptive Structural Learning of Artificial Neural Network Architectures
Gus Kristiansen, Xavi Gonzalvo
We present E NERGY N ET , a new framework for analyzing and building artificial neural network architectures. Our approach adaptively learns the structure of the networks in an uns…