Francesco Tonin

According to our database, Francesco Tonin authored at least 13 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Deep Kernel Principal Component Analysis for multi-level feature learning.

Francesco Tonin, Qinghua Tao, Panagiotis Patrinos, Johan A. K. Suykens

Neural Networks, 2024

Tensor-based multi-view spectral clustering via shared latent space.

Qinghua Tao, Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens

Inf. Fusion, 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

CoRR, 2024

HeNCler: Node Clustering in Heterophilous Graphs through Learned Asymmetric Similarity.

Sonny Achten, Francesco Tonin, Volkan Cevher, Johan A. K. Suykens

CoRR, 2024

Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes.

Yingyi Chen, Qinghua Tao, Francesco Tonin, Johan A. K. Suykens

CoRR, 2024

Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification.

Sonny Achten, Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Nonlinear SVD with Asymmetric Kernels: feature learning and asymmetric Nyström method.

Qinghua Tao, Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens

CoRR, 2023

Combining Primal and Dual Representations in Deep Restricted Kernel Machines Classifiers.

Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens

CoRR, 2023

Semi-Supervised Classification with Graph Convolutional Kernel Machines.

Sonny Achten, Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens

CoRR, 2023

Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation.

Yingyi Chen, Qinghua Tao, Francesco Tonin, Johan A. K. Suykens

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms.

Francesco Tonin, Alex Lambert, Panagiotis Patrinos, Johan A. K. Suykens

Proceedings of the International Conference on Machine Learning, 2023

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

Unsupervised Energy-based Out-of-distribution Detection using Stiefel-Restricted Kernel Machine.

Francesco Tonin, Arun Pandey, Panagiotis Patrinos, Johan A. K. Suykens

Proceedings of the International Joint Conference on Neural Networks, 2021