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Found 5 papers, 2 papers with code
Improving Gradient Estimation in Evolutionary Strategies With Past Descent Directions
Finally, we evaluate our approach empirically on MNIST and reinforcement learning tasks and show that it considerably improves the gradient estimation of ES at no extra computational cost.
The linear hidden subset problem for the (1+1) EA with scheduled and adaptive mutation rates
For the first setup, we give a schedule that achieves a runtime of $(1\pm o(1))\beta n \ln n$, where $\beta \approx 3. 552$, which is an asymptotic improvement over the runtime of the static setup.
Approximating Real-Time Recurrent Learning with Random Kronecker Factors
Despite all the impressive advances of recurrent neural networks, sequential data is still in need of better modelling.
Fast-Slow Recurrent Neural Networks
Processing sequential data of variable length is a major challenge in a wide range of applications, such as speech recognition, language modeling, generative image modeling and machine translation.
Ranked #10 on
Language Modelling
on Penn Treebank (Character Level)
Analytical Model for IEEE 802.15.4 Multi-Hop Networks with Improved Handling of Acknowledgements and Retransmissions
The unslotted CSMA/CA MAC layer of IEEE 802. 15. 4 is closely modeled as well as an enhanced model of the neighborhood allows for consideration of collisions of packets including interferences with acknowledgements.
Networking and Internet Architecture
