• This paper proposes a time-efficient model for solving the Weapon-target assignment (WTA) problem with actorcritic reinforcement learning. While typical heuristic algorithms and recently studied artif…

  • Agent-based models (ABMs) highlight the importance of simulation validation, such as qualitative face validation and quantitative empirical validation. In particular, we focused on quantitative valida…

  • In recent years, developing a digital twin for a complex system has been a key research effort in the modeling and simulation (M&S) community. This paper presents one of the digital twin systems for a…

  • With significant advancements in diffusion models, addressing the potential risks of dataset bias becomes increasingly important. Since generated outputs directly suffer from dataset bias, mitigating …

  • Conditional diffusion models have shown remarkable performance in various generative tasks, but training them requires large-scale datasets that often contain noise in conditional inputs, a.k.a. noisy…

  • For learning with noisy labels, the transition matrix, which explicitly models the relation between noisy label distribution and clean label distribution, has been utilized to achieve the statistical …

  • The objective of domain generalization (DG) is to enhance the transferability of the model learned from a source domain to unobserved domains. To prevent overfitting to a specific domain, Sharpness-Aw…

  • In cooperative multi-agent reinforcement learning (MARL), agents aim to achieve a common goal, such as defeating enemies or scoring a goal. Existing MARL algorithms are effective but still require sig…

  • This paper presents FreD, a novel parameterization method for dataset distillation, which utilizes the frequency domain to distill a small-sized synthetic dataset from a large-sized original dataset. …

  • While deep neural networks play significant roles in many research areas, they are also prone to overfitting problems under limited data instances. To overcome overfitting, this paper introduces the f…

  • The proposed method, Discriminator Guidance, aims to improve sample generation of pre-trained diffusion models. The approach introduces a discriminator that gives explicit supervision to a denoising s…

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