TAdam: A Robust Stochastic Gradient Optimizer. - Wendyam Eric Lionel Ilboudo; Taisuke Kobayashi; Kenji Sugimoto (CoRR, 2020)

Adaptive t-Momentum-based Optimization for Unknown Ratio of Outliers in Amateur Data in Imitation Learning. - Wendyam Eric Lionel Ilboudo; Taisuke Kobayashi; Kenji Sugimoto (IROS, 2021)

t-soft update of target network for deep reinforcement learning. - Taisuke Kobayashi; Wendyam Eric Lionel Ilboudo (Neural Networks, 2021)

AdaTerm: Adaptive T-Distribution Estimated Robust Moments towards Noise-Robust Stochastic Gradient Optimizer. - Wendyam Eric Lionel Ilboudo; Taisuke Kobayashi; Kenji Sugimoto (CoRR, 2022)

Robust Stochastic Gradient Descent With Student-t Distribution Based First-Order Momentum. - Wendyam Eric Lionel Ilboudo; Taisuke Kobayashi; Kenji Sugimoto (IEEE Trans. Neural Networks Learn. Syst., 2022)

Domains as Objectives: Multi-Domain Reinforcement Learning with Convex-Coverage Set Learning for Domain Uncertainty Awareness. - Wendyam Eric Lionel Ilboudo; Taisuke Kobayashi; Takamitsu Matsubara (IROS, 2023)

AdaTerm: Adaptive T-distribution estimated robust moments for Noise-Robust stochastic gradient optimization. - Wendyam Eric Lionel Ilboudo; Taisuke Kobayashi; Takamitsu Matsubara (Neurocomputing, 2023)

Domains as Objectives: Domain-Uncertainty-Aware Policy Optimization through Explicit Multi-Domain Convex Coverage Set Learning. - Wendyam Eric Lionel Ilboudo; Taisuke Kobayashi; Takamitsu Matsubara (CoRR, 2024)