Tomoharu Iwata

Venues

Frequent coauthors

Papers

1. Energy-consistent Neural Operators for Hamiltonian and Dissipative Partial Differential Equations
   AISTATS 2025 ·

   Yusuke Tanaka

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2. Fast Proximal Gradient Methods with Node Pruning for Tree-Structured Sparse Regularization
   ECML-PKDD 2025 ·

   Yasutoshi Ida

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3. Importance-weighted Positive-unlabeled Learning for Distribution Shift Adaptation
   AISTATS 2025 ·

   Atsutoshi Kumagai

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4. K2IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes
   ICML 2025 ·

   Hideaki Kim

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5. Learning to Generate Projections for Reducing Dimensionality of Heterogeneous Linear Programming Problems
   ICML 2025 · Tomoharu Iwata
6. Meta-learning Task-specific Regularization Weights for Few-shot Linear Regression
   AISTATS 2025 · Tomoharu Iwata
7. Meta-learning from Heterogeneous Tensors for Few-shot Tensor Completion
   AISTATS 2025 · Tomoharu Iwata
8. Meta-learning of Class Knowledge in Zero-shot Learning
   SDM 2025 ·

   Yuta Nambu

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9. Positive-Unlabeled Diffusion Models for Preventing Sensitive Data Generation
   ICLR 2025 ·

   Hiroshi Takahashi

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10. Positive-unlabeled AUC Maximization under Covariate Shift
    ICML 2025 ·

    Atsutoshi Kumagai

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11. AUC Maximization under Positive Distribution Shift
    NeurIPS 2024 ·

    Atsutoshi Kumagai

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12. Explanation-based Training with Differentiable Insertion/Deletion Metric-aware Regularizers
    AISTATS 2024 ·

    Yuya Yoshikawa

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13. Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations
    NeurIPS 2024 ·

    Yasutoshi Ida

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14. Information-theoretic Analysis of Bayesian Test Data Sensitivity
    AISTATS 2024 ·

    Futoshi Futami

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15. Symplectic Neural Gaussian Processes for Meta-learning Hamiltonian Dynamics
    IJCAI 2024 · Tomoharu Iwata
16. Warped Diffusion for Latent Differentiation Inference
    AISTATS 2024 ·

    Masahiro Nakano

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17. Zero-Shot Task Adaptation with Relevant Feature Information
    AAAI 2024 ·

    Atsutoshi Kumagai

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