Unsupervised Energy-based Out-of-distribution Detection using Stiefel-Restricted Kernel Machine. - Francesco Tonin; Arun Pandey; Panagiotis Patrinos; Johan A. K. Suykens (IJCNN, 2021)

Unsupervised learning of disentangled representations in deep restricted kernel machines with orthogonality constraints. - Francesco Tonin; Panagiotis Patrinos; Johan A. K. Suykens (Neural Networks, 2021)

Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms. - Francesco Tonin; Alex Lambert; Panagiotis Patrinos; Johan A. K. Suykens (ICML, 2023)

Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation. - Yingyi Chen; Qinghua Tao; Francesco Tonin; Johan A. K. Suykens (NeurIPS, 2023)

Combining Primal and Dual Representations in Deep Restricted Kernel Machines Classifiers. - Francesco Tonin; Panagiotis Patrinos; Johan A. K. Suykens (PKDD/ECML Workshops (4), 2023)

Semi-Supervised Classification with Graph Convolutional Kernel Machines. - Sonny Achten; Francesco Tonin; Panagiotis Patrinos; Johan A. K. Suykens (CoRR, 2023)

Nonlinear SVD with Asymmetric Kernels: feature learning and asymmetric Nyström method. - Qinghua Tao; Francesco Tonin; Panagiotis Patrinos; Johan A. K. Suykens (CoRR, 2023)

Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification. - Sonny Achten; Francesco Tonin; Panagiotis Patrinos; Johan A. K. Suykens (AAAI, 2024)

Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes. - Yingyi Chen; Qinghua Tao; Francesco Tonin; Johan A. K. Suykens (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 A. K. Suykens (ICML, 2024)

Membership Inference Attacks against Large Vision-Language Models. - Zhan Li; Yongtao Wu; Yihang Chen; Francesco Tonin; Elías Abad-Rocamora; Volkan Cevher (NeurIPS, 2024)

HeNCler: Node Clustering in Heterophilous Graphs through Learned Asymmetric Similarity. - Sonny Achten; Francesco Tonin; Volkan Cevher; Johan A. K. Suykens (CoRR, 2024)

Tensor-based multi-view spectral clustering via shared latent space. - Qinghua Tao; Francesco Tonin; Panagiotis Patrinos; Johan A. K. Suykens (Inf. Fusion, 2024)

Deep Kernel Principal Component Analysis for multi-level feature learning. - Francesco Tonin; Qinghua Tao; Panagiotis Patrinos; Johan A. K. Suykens (Neural Networks, 2024)

Quantum-PEFT: Ultra parameter-efficient fine-tuning. - Toshiaki Koike-Akino; Francesco Tonin; Yongtao Wu; Frank Zhengqing Wu; Leyla Naz Candogan; Volkan Cevher (ICLR, 2025)

Linear Attention for Efficient Bidirectional Sequence Modeling. - Arshia Afzal; Elías Abad-Rocamora; Leyla Naz Candogan; Pol Puigdemont; Francesco Tonin; Yongtao Wu; Mahsa Shoaran; Volkan Cevher (CoRR, 2025)

Efficient Large Language Model Inference with Neural Block Linearization. - Mete Erdogan; Francesco Tonin; Volkan Cevher (CoRR, 2025)

Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning. - Wanyun Xie; Francesco Tonin; Volkan Cevher (CoRR, 2025)

Accelerating Spectral Clustering under Fairness Constraints. - Francesco Tonin; Alex Lambert; Johan A. K. Suykens; Volkan Cevher (CoRR, 2025)