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Ayaka Sakata

2 accepted papers

2026

High-Dimensional Learning Dynamics of Quantized Models with Straight-Through Estimator

ICML 2026poster

Quantized neural network training optimizes a discrete, non-differentiable objective. The straight-through estimator (STE) enables backpropagation through surrogate gradients and is widely used. While previous studies have primarily focused on the properties of surrogate gradients and their converge…

Cited by 0SourceScholar
2025

The Effect of Optimal Self-Distillation in Noisy Gaussian Mixture Model

NeurIPS 2025poster

Self-distillation (SD), a technique where a model improves itself using its own predictions, has attracted attention as a simple yet powerful approach in machine learning. Despite its widespread use, the mechanisms underlying its effectiveness remain unclear. In this study, we investigate the effica…

Cited by 0SourcecodeScholar