Symmetric Mean-field Langevin Dynamics for Distributional Minimax Problems

no code implementations • 2 Dec 2023 • Juno Kim, Kakei Yamamoto, Kazusato Oko, Zhuoran Yang, Taiji Suzuki

In this paper, we extend mean-field Langevin dynamics to minimax optimization over probability distributions for the first time with symmetric and provably convergent updates.

Sparse-firing regularization methods for spiking neural networks with time-to-first spike coding

no code implementations • 24 Jul 2023 • Yusuke Sakemi, Kakei Yamamoto, Takeo Hosomi, Kazuyuki Aihara

The training of multilayer spiking neural networks (SNNs) using the error backpropagation algorithm has made significant progress in recent years.

Timing-Based Backpropagation in Spiking Neural Networks Without Single-Spike Restrictions

no code implementations • 29 Nov 2022 • Kakei Yamamoto, Yusuke Sakemi, Kazuyuki Aihara

That was not seen in conventional SNNs with single-spike restrictions on time-to-fast-spike (TTFS) coding.