works on

From the 2 of 8 linked papers with an AI index.

collaborators

8 papers

cs.GT2026

Sensitivity and Differential Privacy in Metric Voting with Distortion below Three

Shinsaku Sakaue, Kaito Fujii, Soh Kumabe +1

The paper proposes randomized voting rules that achieve a metric distortion slightly below three while maintaining low worst‑case sensitivity and providing approximate differential…

cs.DS2026

Testing Monotonicity of Real-Valued Functions on DAGs

Yuichi Yoshida

The paper investigates how to test whether real-valued functions on directed acyclic graphs are monotone, providing tight non‑adaptive query complexity bounds that depend on the si…

cs.DS2026

Approximate Colorwise Tensorization of Entropy and Optimal Mixing of the Wang-Swendsen-Kotecký Dynamics

Chunyang Wang, Yuichi Yoshida, Zihan Zhang

We study the mixing time of Wang-Swendsen-Kotecký (WSK) dynamics for uniformly sampling proper -colorings. The WSK dynamics is widely used in statistical physics for sampling f…

cs.DS2026

Sensitivity Lower Bounds via Locally Testable Codes

Yuichi Yoshida, Zihan Zhang

Sensitivity quantifies how far an algorithm's output can move in Hamming distance when a single input element is perturbed. We present a general scheme turning any locally testable…

stat.ML2026

From Average Sensitivity to Small-Loss Regret Bounds under Random-Order Model

Shinsaku Sakaue, Yuichi Yoshida

We study online learning in the random-order model, where the multiset of loss functions is chosen adversarially but revealed in a uniformly random order. By extending the batch-to…

cs.LG2026

Noise Stability of Transformer Models

Themistoklis Haris, Zihan Zhang, Yuichi Yoshida

Understanding simplicity biases in deep learning offers a promising path toward developing reliable AI. A common metric for this, inspired by Boolean function analysis, is average…