ICML'26 submission accepted - Congratulations to Xiaojie!

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PACEattn

"PACEAttention: Principled and Adaptive Feature Compression-Expansion Grounded in the Geometry of MCR2", has been accepted by ICML'26. Authors are: Xiaojie Yu, Haibo Zhang, Jeremiah D. Deng, and Lizhi Peng.

Yuan's work published by JoP!

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"Obesity, microRNACirculating MicroRNA Signatures Reveal Core and Reversible Dysregulations in Obesity via Machine Learning", is published by Journal of Physiology. Authors are: Yuan Yue, Rajesh Katare, Jeremiah D. Deng, Patrick John Manning, and Daniel Alencar Da Costa.

New paper accepted by Nature Communications Medicine

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"Machine Learning-Based Identification of Abnormal Functional Connectivity in Obesity Across Different Metabolic States", is published by Nature Communications Medicine. Authors are: Yuan Yue, Patrick Manning, Dirk De Ridder, Matthew Hall, Divya Bharatkumar Adhia, Samantha Ross, Daniel Alencar da Costa, and Jeremiah D. Deng.

New paper on finding Fibromyalgia biomarkers

Jean Li

Jean's paper, "EEG Connectivity Features Associated with Fibromyalgia Revealed by Machine Learning", is accepted by Frontiers in Pain Research. Co-authors include J. Deng, D. Adhia, M. Hall, R Mani and D De Ridder.

New paper using multi-domain zero-shot learning published by IEEE JBHI

X Yao, G Yue, JD Deng et al., AMLPF-CLIP: Adaptive Prompting and Distilled Learning for Imbalanced Histopathological Image Classification, JBHI

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We employ multi-level textual cues, class-balanced resampling, and a cross-architecture knowledge-distilation component to enhance accuracy and efficiency in histopathological image classification.

New study on feature selection for chronic pain diagnosis is published by IEEE Transactions on Biomedical Engineering

J Li, D De Ridder, D Adhia, M Hall, R Mani, JD Deng: Modified Feature Selection for Improved Classification of Resting-State Raw EEG Signals in Chronic Knee Pain

Jean

A modified forward sequential subset search method is proposed to diverge from local minima and branch out alternative feature selections that achieve better class separability of EEG functionaly connectivity features of chronic pain patients and healthy controls.