290 citations · 1.2k across the 29 of their papers we have counts for
5 papers · 1 filter
Continual Density Ratio Estimation in an Online Setting
Yu Chen, Song Liu, Tom Diethe +1
In online applications with streaming data, awareness of how far the training or test set has shifted away from the original dataset can be crucial to the performance of the model.…
Semi-Discriminative Representation Loss for Online Continual Learning
Yu Chen, Tom Diethe, Peter Flach
The use of episodic memory in continual learning has demonstrated effectiveness for alleviating catastrophic forgetting. In recent studies, gradient-based approaches have been deve…
-IRT: A New Item Response Model and its Applications
Yu Chen, Telmo Silva Filho, Ricardo B. C. Prudêncio +2
Item Response Theory (IRT) aims to assess latent abilities of respondents based on the correctness of their answers in aptitude test items with different difficulty levels. In this…
Non-Parametric Calibration of Probabilistic Regression
Hao Song, Meelis Kull, Peter Flach
The task of calibration is to retrospectively adjust the outputs from a machine learning model to provide better probability estimates on the target variable. While calibration has…
Probabilistic Sensor Fusion for Ambient Assisted Living
Tom Diethe, Niall Twomey, Meelis Kull +2
There is a widely-accepted need to revise current forms of health-care provision, with particular interest in sensing systems in the home. Given a multiple-modality sensor platform…