109 citations · 709 across the 84 of their papers we have counts for
92 papers
Accelerating Spectral Clustering under Fairness Constraints
Francesco Tonin, Alex Lambert, Johan A. K. Suykens +1
Fairness of decision-making algorithms is an increasingly important issue. In this paper, we focus on spectral clustering with group fairness constraints, where every demographic g…
Generative Kernel Spectral Clustering
David Winant, Sonny Achten, Johan A. K. Suykens
Modern clustering approaches often trade interpretability for performance, particularly in deep learning-based methods. We present Generative Kernel Spectral Clustering (GenKSC), a…
Learning Analysis of Kernel Ridgeless Regression with Asymmetric Kernel Learning
Fan He, Mingzhen He, Lei Shi +2
Ridgeless regression has garnered attention among researchers, particularly in light of the ``Benign Overfitting'' phenomenon, where models interpolating noisy samples demonstrate…
Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method
Qinghua Tao, Francesco Tonin, Alex Lambert +3
In contrast with Mercer kernel-based approaches as used e.g., in Kernel Principal Component Analysis (KPCA), it was previously shown that Singular Value Decomposition (SVD) inheren…
HeNCler: Node Clustering in Heterophilous Graphs via Learned Asymmetric Similarity
Sonny Achten, Zander Op de Beeck, Francesco Tonin +2
Clustering nodes in heterophilous graphs is challenging as traditional methods assume that effective clustering is characterized by high intra-cluster and low inter-cluster connect…
Sparsity via Sparse Group -max Regularization
Qinghua Tao, Xiangming Xi, Jun Xu +1
For the linear inverse problem with sparsity constraints, the regularized problem is NP-hard, and existing approaches either utilize greedy algorithms to find almost-optimal…