67 citations · 148 across the 6 of their papers we have counts for
6 papers
Evolution Strategies at the Hyperscale
Bidipta Sarkar, Mattie Fellows, Juan Agustin Duque +17
Evolution Strategies (ES) is a class of powerful black-box optimisation methods that are highly parallelisable and can handle non-differentiable and noisy objectives. However, naïv…
How Should We Meta-Learn Reinforcement Learning Algorithms?
Alexander David Goldie, Zilin Wang, Jaron Cohen +2
The process of meta-learning algorithms from data, instead of relying on manual design, is growing in popularity as a paradigm for improving the performance of machine learning sys…
SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning
Benjamin Ellis, Jonathan Cook, Skander Moalla +5
The availability of challenging benchmarks has played a key role in the recent progress of machine learning. In cooperative multi-agent reinforcement learning, the StarCraft Multi-…
Multitask Soft Option Learning
Maximilian Igl, Andrew Gambardella, Jinke He +4
We present Multitask Soft Option Learning(MSOL), a hierarchical multitask framework based on Planning as Inference. MSOL extends the concept of options, using separate variational…
Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem
Masrour Zoghi, Shimon Whiteson, Remi Munos +1
This paper proposes a new method for the K-armed dueling bandit problem, a variation on the regular K-armed bandit problem that offers only relative feedback about pairs of arms. O…
Measurement of the top quark mass with dilepton events selected using neuroevolution at CDF
CDF Collaboration, T. Aaltonen
We report a measurement of the top quark mass in the dilepton decay channel . Events are selected with a neural netw…