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cs.LG2024
Black-Box Anomaly Attribution
Tsuyoshi Idé, Naoki Abe
When the prediction of a black-box machine learning model deviates from the true observation, what can be said about the reason behind that deviation? This is a fundamental and ubi…
cs.LG2024
Improving Transformers using Faithful Positional Encoding
Tsuyoshi Idé, Jokin Labaien, Pin-Yu Chen
We propose a new positional encoding method for a neural network architecture called the Transformer. Unlike the standard sinusoidal positional encoding, our approach is based on s…
cs.LG2024
Decentralized Collaborative Learning Framework with External Privacy Leakage Analysis
Tsuyoshi Idé, Dzung T. Phan, Rudy Raymond
This paper presents two methodological advancements in decentralized multi-task learning under privacy constraints, aiming to pave the way for future developments in next-generatio…