research
∙
02/13/2023
Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning
Tomorrow's robots will need to distinguish useful information from noise...
share
research
∙
12/19/2022
Dynamic Sparse Network for Time Series Classification: Learning What to "see”
The receptive field (RF), which determines the region of time series to ...
research
∙
06/28/2021
FreeTickets: Accurate, Robust and Efficient Deep Ensemble by Training with Dynamic Sparsity
Recent works on sparse neural networks have demonstrated that it is poss...
research
∙
06/08/2021
Dynamic Sparse Training for Deep Reinforcement Learning
Deep reinforcement learning has achieved significant success in many dec...
research
∙
03/02/2021
Sparse Training Theory for Scalable and Efficient Agents
A fundamental task for artificial intelligence is learning. Deep Neural ...
research
∙
12/01/2020
Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for Autoencoders
Major complications arise from the recent increase in the amount of high...
research
∙
04/18/2018
One-Shot Learning using Mixture of Variational Autoencoders: a Generalization Learning approach
Deep learning, even if it is very successful nowadays, traditionally nee...
research
∙
07/18/2017
On-line Building Energy Optimization using Deep Reinforcement Learning
Unprecedented high volumes of data are becoming available with the growt...
research
∙
07/15/2017
Evolutionary Training of Sparse Artificial Neural Networks: A Network Science Perspective
Through the success of deep learning, Artificial Neural Networks (ANNs) ...
research
∙
05/06/2016
Energy Disaggregation for Real-Time Building Flexibility Detection
Energy is a limited resource which has to be managed wisely, taking into...
research
∙
04/20/2016
