4 papers
What Scalable Second-Order Information Knows for Pruning at Initialization
Ivo Gollini Navarrete, Nicolás Mauricio Cuadrado Ãvila, Martin TakÃ¡Ä +1
Pruning remains an effective strategy for reducing both the costs and environmental impact associated with deploying large neural networks (NNs) while maintaining performance. Clas…
Generalising Battery Control in Net-Zero Buildings via Personalised Federated RL
Nicolas M Cuadrado Avila, Samuel Horváth, Martin TakáÄ
This work studies the challenge of optimal energy management in building-based microgrids through a collaborative and privacy-preserving framework. We evaluated two common RL algor…
Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization
Yury Demidovich, Petr Ostroukhov, Grigory Malinovsky +4
Non-convex Machine Learning problems typically do not adhere to the standard smoothness assumption. Based on empirical findings, Zhang et al. (2020b) proposed a more realistic gene…
Revisiting LocalSGD and SCAFFOLD: Improved Rates and Missing Analysis
Ruichen Luo, Sebastian U Stich, Samuel Horváth +1
LocalSGD and SCAFFOLD are widely used methods in distributed stochastic optimization, with numerous applications in machine learning, large-scale data processing, and federated lea…