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fltech - 富士通研究所の技術ブログ

富士通研究所の研究員がさまざまなテーマで語る技術ブログ

Conference Paper

“CLUMAP: Clustered Mapper for CGRAs with Predication” presented at DAC 2024

Hello, I am Omar Ragheb from Computing Laboratory. Fujitsu have been developing reconfigurable architectures and CAD tools to accelerate AI workloads. In June 2024, we presented a mapping algorithm at the flagship DAC conference in the fie…

"LayeredLiNGAM: A Practical and Fast Method for Learning a Linear Non-Gaussian Structural Equation Model" presented at ECML-PKDD 2024

Introduction Hello! I'm Suzuki from Artificial Intelligence Laboratory. We are conducting R&D on "Decision Making via Causal Discovery" and working on real-world decision-making tasks such as improving employee productivity based on engage…

”YolOOD: Utilizing Object Detection Concepts for Multi-Label Out-of-Distribution Detection” presented at CVPR 2024

Hello, I am Satoru Koda at AI Laboratory. Fujitsu has been developing technologies for realizing the world where people can safely use AI. In June 2024, we presented our achievement at CVPR 2024, a flagship conference in the computer vision…

"Learning Decision Trees and Forests with Algorithmic Recourse" presented on ICML 2024

Introduction Hi! This is Kentaro Kanamori from Artificial Intelligence Laboratory. We are conducting research and development on "XAI-based Decision-Making Assistant" and trying to apply our technologies to real decision-making tasks (e.g.…

“Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve” accepted at ICLR2023 as notable-top-5%

Recently, in our joint research with the University of Toronto, we have developed an AI technology called Multi-Rate VAE (MR-VAE), enabling the acquisition of the full rate-distortion curve by only a single training run. We will present ou…

"Cost-Sensitive Self-Training for Optimizing Non-Decomposable Metrics" presented on NeurIPS 2022

Recently, in our joint research with the Indian Institute of Science, we have developed an AI technology called cost-sensitive self-training that can optimize practical real-world metrics which are complex and present it at NeurIPS 2022. I…

"Exploring the Whole Rashomon Set of Sparse Decision Trees" presented on NeurIPS 2022

We are conducting research and development on "AI-based Knowledge Discovery". Recently, We have started a joint research project with [Duke University's Interpretable Machine Learning Lab (https://users.cs.duke.edu/~cynthia/lab.html), and …

Our research result on systematic generalization presented at NeurIPS 2021

Japanese version I'm Tomotake Sasaki, a senior researcher at Autonomous Learning Project in Fujitsu Research. Fujitsu Research aims to create “AI that can learn autonomously”, and has been running a joint research program towards this goal…