Futoshi Futami

29 papers A* 6A 4C 2Journal 16Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Estimating Expected Calibration Error for Positive-Unlabeled Learning. Trans. Mach. Learn. Res. Ryuichi Kiryo, Futoshi Futami, Masashi Sugiyama
2026	J	`jnl`	Robust and Computationally Efficient Linear Contextual Bandits under Adversarial Corruption and Heavy-Tailed Noise. CoRR Naoto Tani, Futoshi Futami
2025	J	`jnl`	Data-driven Projection Generation for Efficiently Solving Heterogeneous Quadratic Programming Problems. CoRR Tomoharu Iwata, Futoshi Futami
2025	A	`conf`	Epistemic Uncertainty and Excess Risk in Variational Inference. AISTATS Futoshi Futami
2025	J	`jnl`	Information-theoretic Generalization Analysis for VQ-VAEs: A Role of Latent Variables. CoRR Futoshi Futami, Masahiro Fujisawa
2025	J	`jnl`	L CoRR Masahiro Fujisawa, Futoshi Futami
2025	J	`jnl`	On the Convergence of SVGD in KL divergence via Approximate gradient flow. Trans. Mach. Learn. Res. Masahiro Fujisawa, Futoshi Futami
2025	A*	`conf`	PAC-Bayes Analysis for Recalibration in Classification. ICML Masahiro Fujisawa, Futoshi Futami
2025	J	`jnl`	Uniform convergence of the smooth calibration error and its relationship with functional gradient. CoRR Futoshi Futami, Atsushi Nitanda
2024	A	`conf`	Information-theoretic Analysis of Bayesian Test Data Sensitivity. AISTATS Futoshi Futami, Tomoharu Iwata
2024	A*	`conf`	Information-theoretic Generalization Analysis for Expected Calibration Error. NeurIPS Futoshi Futami, Masahiro Fujisawa
2024	J	`jnl`	Information-theoretic Generalization Analysis for Expected Calibration Error. CoRR Futoshi Futami, Masahiro Fujisawa
2024	J	`jnl`	PAC-Bayes Analysis for Recalibration in Classification. CoRR Masahiro Fujisawa, Futoshi Futami
2023	J	`jnl`	Information-theoretic Analysis of Test Data Sensitivity in Uncertainty. CoRR Futoshi Futami, Tomoharu Iwata
2023	A*	`conf`	Time-Independent Information-Theoretic Generalization Bounds for SGLD. NeurIPS Futoshi Futami, Masahiro Fujisawa
2023	J	`jnl`	Time-Independent Information-Theoretic Generalization Bounds for SGLD. CoRR Futoshi Futami, Masahiro Fujisawa
2022	J	`jnl`	Excess risk analysis for epistemic uncertainty with application to variational inference. CoRR Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama
2022	A	`conf`	Predictive variational Bayesian inference as risk-seeking optimization. AISTATS Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama
2021	J	`jnl`	Accelerated Diffusion-Based Sampling by the Non-Reversible Dynamics with Skew-Symmetric Matrices. Entropy Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato
2021	A*	`conf`	Loss function based second-order Jensen inequality and its application to particle variational inference. NeurIPS Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama
2021	J	`jnl`	Loss function based second-order Jensen inequality and its application to particle variational inference. CoRR Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama
2021	C	`conf`	Scalable gradient matching based on state space Gaussian Processes. ACML Futoshi Futami
2021	C	`conf`	Skew-symmetrically perturbed gradient flow for convex optimization. ACML Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Ikko Yamane
2020	A*	`conf`	Accelerating the diffusion-based ensemble sampling by non-reversible dynamics. ICML Futoshi Futami, Issei Sato, Masashi Sugiyama
2020	J	`jnl`	Time-varying Gaussian Process Bandit Optimization with Non-constant Evaluation Time. CoRR Hideaki Imamura, Nontawat Charoenphakdee, Futoshi Futami, Issei Sato, Junya Honda, Masashi Sugiyama
2019	A*	`conf`	Bayesian Posterior Approximation via Greedy Particle Optimization. AAAI Futoshi Futami, Zhenghang Cui, Issei Sato, Masashi Sugiyama
2018	J	`jnl`	Frank-Wolfe Stein Sampling. CoRR Futoshi Futami, Zhenghang Cui, Issei Sato, Masashi Sugiyama
2018	A	`conf`	Variational Inference based on Robust Divergences. AISTATS Futoshi Futami, Issei Sato, Masashi Sugiyama
2017	—	`conf`	Expectation Propagation for t-Exponential Family Using q-Algebra. NIPS Futoshi Futami, Issei Sato, Masashi Sugiyama