19 citations · 41 across the 9 of their papers we have counts for
4 papers · 1 filter
Asynchronous Evolution of Deep Neural Network Architectures
Jason Liang, Hormoz Shahrzad, Risto Miikkulainen
Many evolutionary algorithms (EAs) take advantage of parallel evaluation of candidates. However, if evaluation times vary significantly, many worker nodes (i.e.,\ compute clients)…
Evolutionary Neural AutoML for Deep Learning
Jason Liang, Elliot Meyerson, Babak Hodjat +3
Deep neural networks (DNNs) have produced state-of-the-art results in many benchmarks and problem domains. However, the success of DNNs depends on the proper configuration of its a…
Evolutionary Architecture Search For Deep Multitask Networks
Jason Liang, Elliot Meyerson, Risto Miikkulainen
Multitask learning, i.e. learning several tasks at once with the same neural network, can improve performance in each of the tasks. Designing deep neural network architectures for…
Evolving Deep Neural Networks
Risto Miikkulainen, Jason Liang, Elliot Meyerson +8
The success of deep learning depends on finding an architecture to fit the task. As deep learning has scaled up to more challenging tasks, the architectures have become difficult t…