42 citations · 132 across the 20 of their papers we have counts for
3 papers · 1 filter
Improving Gradient Estimation in Evolutionary Strategies With Past Descent Directions
Florian Meier, Asier Mujika, Marcelo Matheus Gauy +1
Evolutionary Strategies (ES) are known to be an effective black-box optimization technique for deep neural networks when the true gradients cannot be computed, such as in Reinforce…
Decoupling Hierarchical Recurrent Neural Networks With Locally Computable Losses
Asier Mujika, Felix Weissenberger, Angelika Steger
Learning long-term dependencies is a key long-standing challenge of recurrent neural networks (RNNs). Hierarchical recurrent neural networks (HRNNs) have been considered a promisin…
Optimal Kronecker-Sum Approximation of Real Time Recurrent Learning
Frederik Benzing, Marcelo Matheus Gauy, Asier Mujika +2
One of the central goals of Recurrent Neural Networks (RNNs) is to learn long-term dependencies in sequential data. Nevertheless, the most popular training method, Truncated Backpr…