Francesco Tonin

Orcid: 0000-0002-5644-0086

According to our database¹, Francesco Tonin authored at least 22 papers between 2021 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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Book In proceedings Article PhD thesis Dataset Other

Bibliography

2026

Sequence Modeling Architectures: Foundations [Special Issue on the Mathematics of Deep Learning].

[BibT_eX]

[DOI]

IEEE Signal Process. Mag., May, 2026

MaD-Mix: Multi-Modal Data Mixtures via Latent Space Coupling for Vision-Language Model Training.

[BibT_eX]

[DOI]

Wanyun Xie

Francesco Tonin

Volkan Cevher

CoRR, February, 2026

2025

Efficient Large Language Model Inference with Neural Block Linearization.

[BibT_eX]

[DOI]

Mete Erdogan

Francesco Tonin

Volkan Cevher

CoRR, May, 2025

Linear Attention for Efficient Bidirectional Sequence Modeling.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning.

[BibT_eX]

[DOI]

Wanyun Xie

Francesco Tonin

Volkan Cevher

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Accelerating Spectral Clustering under Fairness Constraints.

[BibT_eX]

[DOI]

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Quantum-PEFT: Ultra parameter-efficient fine-tuning.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning. ICANN 2025 International Workshops and Special Sessions, 2025

2024

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

[BibT_eX]

[DOI]

Neural Networks, 2024

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

[BibT_eX]

[DOI]

Inf. Fusion, 2024

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

[BibT_eX]

[DOI]

CoRR, 2024

Membership Inference Attacks against Large Vision-Language Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

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

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

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

[BibT_eX]

[DOI]

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

2023

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

[BibT_eX]

[DOI]

CoRR, 2023

Semi-Supervised Classification with Graph Convolutional Kernel Machines.

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

Francesco Tonin

Panagiotis Patrinos

Johan A. K. Suykens

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023

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

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

2021

Unsupervised learning of disentangled representations in deep restricted kernel machines with orthogonality constraints.

[BibT_eX]

[DOI]

Francesco Tonin

Panagiotis Patrinos

Johan A. K. Suykens

Neural Networks, 2021

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

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2021

Francesco Tonin

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