Search Results - Cervino, Juan

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  1. 1
    Learning by Transference: Training Graph Neural Networks on Growing Graphs

    Learning by Transference: Training Graph Neural Networks on Growing Graphs by Cervino, Juan, Ruiz, Luana, Ribeiro, Alejandro

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  2. 2
    Training Stable Graph Neural Networks Through Constrained Learning

    Training Stable Graph Neural Networks Through Constrained Learning by Cervino, Juan, Ruiz, Luana, Ribeiro, Alejandro

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  3. 3
    The Conway–Sloane tetralattice pairs are non-isometric

    The Conway–Sloane tetralattice pairs are non-isometric by Cerviño, Juan Marcos, Hein, Georg

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  4. 4
    Training Graph Neural Networks on Growing Stochastic Graphs

    Training Graph Neural Networks on Growing Stochastic Graphs by Cervino, Juan, Ruiz, Luana, Ribeiro, Alejandro

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  5. 5
    Multi-Task Reinforcement Learning in Reproducing Kernel Hilbert Spaces via Cross-Learning

    Multi-Task Reinforcement Learning in Reproducing Kernel Hilbert Spaces via Cross-Learning by Cervino, Juan, Bazerque, Juan Andres, Calvo-Fullana, Miguel, Ribeiro, Alejandro

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  6. 6
    Multi-Task Bias-Variance Trade-Off Through Functional Constraints

    Multi-Task Bias-Variance Trade-Off Through Functional Constraints by Cervino, Juan, Bazerque, Juan Andres, Calvo-Fullana, Miguel, Ribeiro, Alejandro

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  7. 7
    Meta-Learning through Coupled Optimization in Reproducing Kernel Hilbert Spaces

    Meta-Learning through Coupled Optimization in Reproducing Kernel Hilbert Spaces by Cervino, Juan, Bazerque, Juan Andres, Calvo-Fullana, Miguel, Ribeiro, Alejandro

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  8. 8
    A Manifold Perspective on the Statistical Generalization of Graph Neural Networks

    A Manifold Perspective on the Statistical Generalization of Graph Neural Networks by Wang, Zhiyang, Cervino, Juan, Ribeiro, Alejandro

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  9. 9
    Generalization of Graph Neural Networks is Robust to Model Mismatch

    Generalization of Graph Neural Networks is Robust to Model Mismatch by Wang, Zhiyang, Cervino, Juan, Ribeiro, Alejandro

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  10. 10
    Generalization of Geometric Graph Neural Networks

    Generalization of Geometric Graph Neural Networks by Wang, Zhiyang, Cervino, Juan, Ribeiro, Alejandro

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  11. 11
    Constrained Learning for Decentralized Multi-Objective Coverage Control

    Constrained Learning for Decentralized Multi-Objective Coverage Control by Cervino, Juan, Agarwal, Saurav, Kumar, Vijay, Ribeiro, Alejandro

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  12. 12
    Training Graph Neural Networks on Growing Stochastic Graphs

    Training Graph Neural Networks on Growing Stochastic Graphs by Cervino, Juan, Ruiz, Luana, Ribeiro, Alejandro

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  13. 13
    Federated Representation Learning via Maximal Coding Rate Reduction

    Federated Representation Learning via Maximal Coding Rate Reduction by Cervino, Juan, NaderiAlizadeh, Navid, Ribeiro, Alejandro

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  14. 14
    Learning by Transference: Training Graph Neural Networks on Growing Graphs

    Learning by Transference: Training Graph Neural Networks on Growing Graphs by Cervino, Juan, Ruiz, Luana, Ribeiro, Alejandro

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  15. 15
    Training Stable Graph Neural Networks Through Constrained Learning

    Training Stable Graph Neural Networks Through Constrained Learning by Cervino, Juan, Ruiz, Luana, Ribeiro, Alejandro

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  16. 16
    Multi-task Reinforcement Learning in Reproducing Kernel Hilbert Spaces via Cross-learning

    Multi-task Reinforcement Learning in Reproducing Kernel Hilbert Spaces via Cross-learning by Cervino, Juan, Juan Andres Bazerque, Calvo-Fullana, Miguel, Ribeiro, Alejandro

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  17. 17
    Multi-task Bias-Variance Trade-off Through Functional Constraints

    Multi-task Bias-Variance Trade-off Through Functional Constraints by Cervino, Juan, Juan Andres Bazerque, Calvo-Fullana, Miguel, Ribeiro, Alejandro

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  18. 18
    Distributed Training of Large Graph Neural Networks with Variable Communication Rates

    Distributed Training of Large Graph Neural Networks with Variable Communication Rates by Cervino, Juan, Md Asadullah Turja, Mostafa, Hesham, Himayat, Nageen, Ribeiro, Alejandro

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  19. 19
    Parameter Critic: a Model Free Variance Reduction Method Through Imperishable Samples

    Parameter Critic: a Model Free Variance Reduction Method Through Imperishable Samples by Cervino, Juan, Kumar, Harshat, Ribeiro, Alejandro

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  20. 20
    Intrinsically motivated graph exploration using network theories of human curiosity

    Intrinsically motivated graph exploration using network theories of human curiosity by Patankar, Shubhankar P, Ouellet, Mathieu, Cervino, Juan, Ribeiro, Alejandro, Murphy, Kieran A, Bassett, Dani S

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