Yuma Ichikawa

According to our database, Yuma Ichikawa authored at least 11 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2025

Quantization Error Propagation: Revisiting Layer-Wise Post-Training Quantization.

Yamato Arai, Yuma Ichikawa

CoRR, April, 2025

Optimization by Parallel Quasi-Quantum Annealing with Gradient-Based Sampling.

Yuma Ichikawa, Yamato Arai

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Statistical Mechanics of Min-Max Problems.

Yuma Ichikawa, Koji Hukushima

Trans. Mach. Learn. Res., 2024

Ratio Divergence Learning Using Target Energy in Restricted Boltzmann Machines: Beyond Kullback-Leibler Divergence Learning.

Yuichi Ishida, Yuma Ichikawa, Aki Dote, Toshiyuki Miyazawa, Koji Hukushima

CoRR, 2024

Training-Free Time-Series Anomaly Detection: Leveraging Image Foundation Models.

Nobuo Namura, Yuma Ichikawa

CoRR, 2024

Continuous Tensor Relaxation for Finding Diverse Solutions in Combinatorial Optimization Problems.

Yuma Ichikawa, Hiroaki Iwashita

CoRR, 2024

Controlling Continuous Relaxation for Combinatorial Optimization.

Yuma Ichikawa

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Adaptive Flip Graph Algorithm for Matrix Multiplication.

Yamato Arai, Yuma Ichikawa, Koji Hukushima

Proceedings of the 2024 International Symposium on Symbolic and Algebraic Computation, 2024

Learning Dynamics in Linear VAE: Posterior Collapse Threshold, Superfluous Latent Space Pitfalls, and Speedup with KL Annealing.

Yuma Ichikawa, Koji Hukushima

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Dataset Size Dependence of Rate-Distortion Curve and Threshold of Posterior Collapse in Linear VAE.

Yuma Ichikawa, Koji Hukushima

CoRR, 2023

2022

Toward Unlimited Self-Learning Monte Carlo with Annealing Process Using VAE's Implicit Isometricity.

Yuma Ichikawa, Akira Nakagawa, Hiromoto Masayuki, Yuhei Umeda

CoRR, 2022