44 citations · 44 across the 2 of their papers we have counts for
5 papers
Sparse Training Theory for Scalable and Efficient Agents
Decebal Constantin Mocanu, Elena Mocanu, Tiago Pinto +5
A fundamental task for artificial intelligence is learning. Deep Neural Networks have proven to cope perfectly with all learning paradigms, i.e. supervised, unsupervised, and reinf…
Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for Autoencoders
Zahra Atashgahi, Ghada Sokar, Tim van der Lee +4
Major complications arise from the recent increase in the amount of high-dimensional data, including high computational costs and memory requirements. Feature selection, which iden…
One-Shot Learning using Mixture of Variational Autoencoders: a Generalization Learning approach
Decebal Constantin Mocanu, Elena Mocanu
Deep learning, even if it is very successful nowadays, traditionally needs very large amounts of labeled data to perform excellent on the classification task. In an attempt to solv…
On-line Building Energy Optimization using Deep Reinforcement Learning
Elena Mocanu, Decebal Constantin Mocanu, Phuong H. Nguyen +4
Unprecedented high volumes of data are becoming available with the growth of the advanced metering infrastructure. These are expected to benefit planning and operation of the futur…
Energy Disaggregation for Real-Time Building Flexibility Detection
Elena Mocanu, Phuong H. Nguyen, Madeleine Gibescu
Energy is a limited resource which has to be managed wisely, taking into account both supply-demand matching and capacity constraints in the distribution grid. One aspect of the sm…