Futoshi Futami

According to our database, Futoshi Futami authored at least 17 papers between 2017 and 2024.

Collaborative distances:

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

2024

PAC-Bayes Analysis for Recalibration in Classification.

Masahiro Fujisawa, Futoshi Futami

CoRR, 2024

Information-theoretic Generalization Analysis for Expected Calibration Error.

Futoshi Futami, Masahiro Fujisawa

CoRR, 2024

Information-theoretic Analysis of Bayesian Test Data Sensitivity.

Futoshi Futami, Tomoharu Iwata

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Information-theoretic Analysis of Test Data Sensitivity in Uncertainty.

Futoshi Futami, Tomoharu Iwata

CoRR, 2023

Time-Independent Information-Theoretic Generalization Bounds for SGLD.

Futoshi Futami, Masahiro Fujisawa

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

2022

Excess risk analysis for epistemic uncertainty with application to variational inference.

Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama

CoRR, 2022

Predictive variational Bayesian inference as risk-seeking optimization.

Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Accelerated Diffusion-Based Sampling by the Non-Reversible Dynamics with Skew-Symmetric Matrices.

Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato

Entropy, 2021

Loss function based second-order Jensen inequality and its application to particle variational inference.

Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Skew-symmetrically perturbed gradient flow for convex optimization.

Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Ikko Yamane

Proceedings of the Asian Conference on Machine Learning, 2021

Scalable gradient matching based on state space Gaussian Processes.

Futoshi Futami

Proceedings of the Asian Conference on Machine Learning, 2021

2020

Time-varying Gaussian Process Bandit Optimization with Non-constant Evaluation Time.

Hideaki Imamura, Nontawat Charoenphakdee, Futoshi Futami, Issei Sato, Junya Honda, Masashi Sugiyama

CoRR, 2020

Accelerating the diffusion-based ensemble sampling by non-reversible dynamics.

Futoshi Futami, Issei Sato, Masashi Sugiyama

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Bayesian Posterior Approximation via Greedy Particle Optimization.

Futoshi Futami, Zhenghang Cui, Issei Sato, Masashi Sugiyama

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Frank-Wolfe Stein Sampling.

Futoshi Futami, Zhenghang Cui, Issei Sato, Masashi Sugiyama

CoRR, 2018

Variational Inference based on Robust Divergences.

Futoshi Futami, Issei Sato, Masashi Sugiyama

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Expectation Propagation for t-Exponential Family Using q-Algebra.

Futoshi Futami, Issei Sato, Masashi Sugiyama

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017