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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…

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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…

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