Suykens, Johan

12 publications

ICML 2025 Accelerating Spectral Clustering Under Fairness Constraints Francesco Tonin, Alex Lambert, Johan Suykens, Volkan Cevher

NeurIPS 2025 Rethinking PCA Through Duality Jan Quan, Johan Suykens, Panagiotis Patrinos

ICML 2024 Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström Method Qinghua Tao, Francesco Tonin, Alex Lambert, Yingyi Chen, Panagiotis Patrinos, Johan Suykens

ICML 2024 Self-Attention Through Kernel-Eigen Pair Sparse Variational Gaussian Processes Yingyi Chen, Qinghua Tao, Francesco Tonin, Johan Suykens

ICMLW 2023 Equivariant Representation Learning with Equivariant Convolutional Kernel Networks Soutrik Roy Chowdhury, Johan Suykens

ICML 2023 Extending Kernel PCA Through Dualization: Sparsity, Robustness and Fast Algorithms Francesco Tonin, Alex Lambert, Panagiotis Patrinos, Johan Suykens

NeurIPS 2023 Primal-Attention: Self-Attention Through Asymmetric Kernel SVD in Primal Representation Yingyi Chen, Qinghua Tao, Francesco Tonin, Johan Suykens

NeurIPS 2022 On the Double Descent of Random Features Models Trained with SGD Fanghui Liu, Johan Suykens, Volkan Cevher

AISTATS 2021 Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures Fanghui Liu, Xiaolin Huang, Yingyi Chen, Johan Suykens

AISTATS 2021 Kernel Regression in High Dimensions: Refined Analysis Beyond Double Descent Fanghui Liu, Zhenyu Liao, Johan Suykens

NeurIPS 2020 A Theoretical Framework for Target Propagation Alexander Meulemans, Francesco Carzaniga, Johan Suykens, João Sacramento, Benjamin F. Grewe

NeurIPS 2007 A Risk Minimization Principle for a Class of Parzen Estimators Kristiaan Pelckmans, Johan Suykens, Bart D. Moor