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2020 – today
- 2024
[j3]Qinghua Tao
, Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens:
Tensor-based multi-view spectral clustering via shared latent space. Inf. Fusion 108: 102405 (2024)- [j2]Francesco Tonin, Qinghua Tao, Panagiotis Patrinos, Johan A. K. Suykens:
Deep Kernel Principal Component Analysis for multi-level feature learning. Neural Networks 170: 578-595 (2024) - [c6]Sonny Achten, Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens:
Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification. AAAI 2024: 10766-10774 - [c5]Yingyi Chen, Qinghua Tao, Francesco Tonin, Johan A. K. Suykens:
Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes. ICML 2024 - [c4]Qinghua Tao, Francesco Tonin, Alex Lambert, Yingyi Chen, Panagiotis Patrinos, Johan A. K. Suykens:
Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method. ICML 2024 - [i12]Yingyi Chen, Qinghua Tao, Francesco Tonin, Johan A. K. Suykens:
Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes. CoRR abs/2402.01476 (2024) - [i11]Sonny Achten, Francesco Tonin, Volkan Cevher, Johan A. K. Suykens:
HeNCler: Node Clustering in Heterophilous Graphs through Learned Asymmetric Similarity. CoRR abs/2405.17050 (2024) - [i10]Qinghua Tao, Francesco Tonin, Alex Lambert, Yingyi Chen, Panagiotis Patrinos, Johan A. K. Suykens:
Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method. CoRR abs/2406.08748 (2024) - 2023
- [c3]Francesco Tonin, Alex Lambert, Panagiotis Patrinos, Johan A. K. Suykens:
Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms. ICML 2023: 34379-34393 - [c2]Yingyi Chen, Qinghua Tao, Francesco Tonin, Johan A. K. Suykens:
Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation. NeurIPS 2023 - [i9]Sonny Achten, Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens:
Semi-Supervised Classification with Graph Convolutional Kernel Machines. CoRR abs/2301.13764 (2023) - [i8]Francesco Tonin, Qinghua Tao, Panagiotis Patrinos, Johan A. K. Suykens:
Deep Kernel Principal Component Analysis for Multi-level Feature Learning. CoRR abs/2302.11220 (2023) - [i7]Yingyi Chen, Qinghua Tao, Francesco Tonin, Johan A. K. Suykens:
Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation. CoRR abs/2305.19798 (2023) - [i6]Francesco Tonin, Alex Lambert, Panagiotis Patrinos, Johan A. K. Suykens:
Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms. CoRR abs/2306.05815 (2023) - [i5]Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens:
Combining Primal and Dual Representations in Deep Restricted Kernel Machines Classifiers. CoRR abs/2306.07015 (2023) - [i4]Qinghua Tao, Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens:
Nonlinear SVD with Asymmetric Kernels: feature learning and asymmetric Nyström method. CoRR abs/2306.07040 (2023) - 2022
- [i3]Qinghua Tao, Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens:
Tensor-based Multi-view Spectral Clustering via Shared Latent Space. CoRR abs/2207.11559 (2022) - 2021
- [j1]Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens:
Unsupervised learning of disentangled representations in deep restricted kernel machines with orthogonality constraints. Neural Networks 142: 661-679 (2021) - [c1]Francesco Tonin, Arun Pandey, Panagiotis Patrinos, Johan A. K. Suykens:
Unsupervised Energy-based Out-of-distribution Detection using Stiefel-Restricted Kernel Machine. IJCNN 2021: 1-8 - [i2]Francesco Tonin, Arun Pandey, Panagiotis Patrinos, Johan A. K. Suykens:
Unsupervised Energy-based Out-of-distribution Detection using Stiefel-Restricted Kernel Machine. CoRR abs/2102.08443 (2021) - 2020
- [i1]Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens:
Unsupervised learning of disentangled representations in deep restricted kernel machines with orthogonality constraints. CoRR abs/2011.12659 (2020)
Coauthor Index
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