Search Results for author: Wendyam Eric Lionel Ilboudo

Found 4 papers, 2 papers with code

AdaTerm: Adaptive T-Distribution Estimated Robust Moments for Noise-Robust Stochastic Gradient Optimization

1 code implementation18 Jan 2022 Wendyam Eric Lionel Ilboudo, Taisuke Kobayashi, Takamitsu Matsubara

In this paper, we propose AdaTerm, a novel approach that incorporates the Student's t-distribution to derive not only the first-order moment but also all the associated statistics.

Adaptive t-Momentum-based Optimization for Unknown Ratio of Outliers in Amateur Data in Imitation Learning

no code implementations2 Aug 2021 Wendyam Eric Lionel Ilboudo, Taisuke Kobayashi, Kenji Sugimoto

In order to allow the imitators to effectively learn from imperfect demonstrations, we propose to employ the robust t-momentum optimization algorithm.

Imitation Learning

t-Soft Update of Target Network for Deep Reinforcement Learning

no code implementations25 Aug 2020 Taisuke Kobayashi, Wendyam Eric Lionel Ilboudo

The problem with its conventional update rule is the fact that all the parameters are smoothly copied with the same speed from the main network, even when some of them are trying to update toward the wrong directions.

reinforcement-learning Reinforcement Learning (RL)

TAdam: A Robust Stochastic Gradient Optimizer

3 code implementations29 Feb 2020 Wendyam Eric Lionel Ilboudo, Taisuke Kobayashi, Kenji Sugimoto

Machine learning algorithms aim to find patterns from observations, which may include some noise, especially in robotics domain.

Reinforcement Learning (RL)

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