Result for "Transfer Learning",135

Atsutoshi Kumagai | NTT R&D Website

/center/dept Machine Learning for Knowledge Transfer We aim to develop machine learning algorithms that

https://www.rd.ntt/e/organization/researcher/special/s_056.html

C06-e.pdf

in data transfer performance, which is a problem in AI learning in a distributed environment. #C06 As

https://www.rd.ntt/forum/2025/doc/C06-e.pdf

NTT Communication Science Laboratories Open House 2020

Exhibition Download Contact Home / Exhibition Program Exhibition Program Science of Machine Learning 04 Fast

https://www.rd.ntt/cs/event/openhouse/2020/exhibition4/index_en.html

G03-01-e.pdf

-01 Motor-skill transfer: Movement support via brainwaves You can control devices such as wheelchairs

https://www.rd.ntt/forum/2024/doc/G03-01-e.pdf

E37_leaf_e.pdf

coordination control mechanism in the spinal cord. It is expected that the model will enable learning of muscle

https://www.rd.ntt/forum/2023/doc/E37_leaf_e.pdf

D01-10-e.pdf

LLMs. • Advanced AI algorithms such as transfer learning and federated learning. • Solutions can be

https://www.rd.ntt/forum/2024/doc/D01-10-e.pdf

NTT Communication Science Laboratories Open House 2020 Exhibition

Exhibition Program Science of Machine Learning People of the WWW, give us your computation each! Generating

https://www.rd.ntt/cs/event/openhouse/2020/exhibition_en.html

Cybernetics | NTT R&D Website

human capabilities by making it possible to transfer skills independent of time and place. We are

https://www.rd.ntt/e/hil/category/cybernetics/

スライド 1

Transfer anomaly detection for unseen datasets We propose a method to improve the anomaly detection

https://www.rd.ntt/cs/event/openhouse/2020/download/a_04_en.pdf

Real-Time Monitoring of Neural Activity in the Brain

efficient functions including transfer, storage and other forms of processing of a large quantity of

https://www.rd.ntt/e/brl/result/activities/file/report00/E/report07_e.html

頑健な半教師あり学習法と自然言語処理への応用

semi-supervised classification method for transfer learning,” Proc. of the 19th ACM International

https://www.rd.ntt/cs/event/openhouse/2012/panel/panel_4.pdf

TAKASAKI, Chikako

, "Meta Learner-Based Transfer Learning: Bridging Simulation and Actual Router Metrics," 2024 IEEE 25th

https://www.rd.ntt/e/ns/qos/person/takasaki/

Motor-skill-transfer technology | NTT R&D Website

Motor-skill-transfer technology | NTT R&D Website NTT R&D Website NTT Human Informatics

https://www.rd.ntt/e/hil/category/cybernetics/motorskilltransfer/

0053.pdf

separation (BSS)[4] is a possible candidate for multi-channel noise cancellation. However, the learning of a

https://www.rd.ntt/cs/team_project/icl/signal/iwaenc03/cdrom/data/0053.pdf

0141.pdf

following sections. Below, matrix X and transfer function matrix X(z) = ΣτXτ z−τare M×N matrices. X can be

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0141.pdf

poster_en_23.pdf

textures, we will be able not only to transfer the content of a sound but also to manipulate its fine

https://www.rd.ntt/cs/event/openhouse/2017/exhibition/23/poster_en_23.pdf

Stage Production for Celebration of Torch Relay × Ultra-realistic Communication Technology Kirari!｜NTT R&D Website

transfer the artist on the main stage and the other was to transfer the fans at the venue next to the

https://www.rd.ntt/e/research/JN202111_16128.html

Technical fields

, signal processing theory, coding theory, modeling methods, simulation, transfer protocol Demand/traffic

https://www.rd.ntt/e/ns/qos/outline/

KORIKAWA, Tomohiro

), 2024 pp. 1-5. K. Hattori, T. Korikawa, and C. Takasaki, “Meta Learner-Based Transfer Learning: Bridging

https://www.rd.ntt/e/ns/qos/person/korikawa/

The Preferential Reconstitution of Receptor Proteins into Model Lipid Domains Studied by Atomic Force Microscopy

role in biological membranes. They bind to ligand molecules and transfer signals into the cells by

https://www.rd.ntt/e/brl/result/activities/file/report08/report11.html

Position under active recruitment:Research and development of energy networks｜Careers｜NTT Space Environment and Energy Laboratories｜NTT R&D Website

learning and inference processed by GPUs and workloads for cellular base stations as well as algorithms for

https://www.rd.ntt/e/se/recruitment/focus03.html

About Us | NTT Access Network Service Systems Laboratories | NTT R&D Website

transfer not dependent on specific protocols. Wireless Access Technology: multi-wireless proactive control

https://www.rd.ntt/e/as/overview/

Optimal operation technologies for fusion reactors | NTT Space Environment and Energy Laboratories | NTT R&D Website

(AI) and machine learning (ML) for high-speed control of fusion plasma with temperatures above 100

https://www.rd.ntt/e/se/technology/nuclear_fusion.html

main.dvi

main.dvi INTRODUCING NEW MECHANISM IN THE LEARNING PROCESS OF FDICA-BASED SPEECH SEPARATION

https://www.rd.ntt/cs/team_project/icl/signal/iwaenc03/cdrom/data/0045.pdf

Development of Next-Generation Data Hub Technology That Connects Data Owners and Data Users with Peace of Mind, Safety and Ultra-low Latency｜NTT R&D Website

-analyzed data, reduced data-transfer costs through metadata-based delivery, more advanced data access, and

https://www.rd.ntt/e/infrastructure/0001.html

Computational Modeling Research Group | NTT Communication Science Laboratories | NTT R&D Website

). Macau, China. Yuto Kondo, Hirokazu Kameoka, Kou Tanaka, Takuhiro Kaneko & Noboru Harada (2024). LEARNING

https://www.rd.ntt/e/cs/team_project/media/computational_modeling/

Major issues and research trends in the evolution of artificial intelligence (AI)｜NTT R&D Website

, aggregate and analyze data for each field of application, so cost increases dramatically. Transfer learning

https://www.rd.ntt/e/ai/0001.html

Molecular and Bio Science Research Group | NTT Basic Research Laboratories | NTT R&D Website

Rate at the Anaerobic Threshold Using a Machine Learning Model Based on a Large-Scale Population

https://www.rd.ntt/e/brl/group_introduction/group_003.html

事象モデリング研究グループ｜NTTコミュニケーション科学基礎研究所｜NTT R&D Website

). LEARNING TO ASSESS SUBJECTIVE IMPRESSIONS CONVEYED THROUGH SPEECH. European Signal Processing Conference

https://www.rd.ntt/cs/team_project/media/computational_modeling/

論文｜NTT物性科学基礎研究所｜NTT R&D Website

), 102001 (2024). S. Himori, R. Takahashi, A. Tanaka, and M. Yamaguchi "Direct Metal Transfer on Swellable

https://www.rd.ntt/brl/result/publications/paper_2024.html

Publications | NTT Basic Research Laboratories | NTT R&D Website

. Takahashi, A. Tanaka, and M. Yamaguchi "Direct Metal Transfer on Swellable Hydrogel with Dehydration-Induced

https://www.rd.ntt/e/brl/result/publications/paper_2024.html

分子生体機能研究グループ｜NTT物性科学基礎研究所｜NTT R&D Website

Using a Machine Learning Model Based on a Large-Scale Population Dataset J. Clin. Med. 14 (1), 21 (2025

https://www.rd.ntt/brl/group_introduction/group_003.html

0067.pdf

z−W A A . Here, the norm of transfer function matrix ( )zX is defined as ( )zX 1/ 2 2 k k

https://www.rd.ntt/cs/team_project/icl/signal/iwaenc03/cdrom/data/0067.pdf

0003.pdf

, we consider the situation that the transfer function matrix of the mixing process becomes almost

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0003.pdf

知能創発環境研究グループ｜NTTコミュニケーション科学基礎研究所｜NTT R&D Website

. Bastiaan Kleijn, "Revisiting 1-peer Exponential Graph for Enhancing Decentralized Learning Efficiency

https://www.rd.ntt/cs/team_project/icl/ls/

Learning and Intelligent Systems Research Group | NTT Communication Science Laboratories | NTT R&D Website

Learning and Intelligent Systems Research Group | NTT Communication Science Laboratories | NTT R&D

https://www.rd.ntt/e/cs/team_project/icl/ls/

NTT Communication Science Laboratories Open House 2019

, thanks to recent AI developments especially in deep learning, computers are approaching?and surpassing in

https://www.rd.ntt/cs/event/openhouse/2019/director/index_en.html

Introduction of Evangelists | NTT Social Informatics Laboratories | NTT R&D Website

transfer from diverse data. Goal is to create machine learning techniques that enable value extraction by

https://www.rd.ntt/e/sil/overview/evangelist/

Signal Processing Research Group | NTT Communication Science Laboratories | NTT R&D Website

, Atsunori Ogawa & Marc Delcroix (2023). Transfer Learning from Pre-trained Language Models Improves End-to

https://www.rd.ntt/e/cs/team_project/media/signal/

Microsoft Word - ica2003_cdma_fin.doc

diagonalization of the global transfer function. The global transfer function presents the combined effect of the

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0148.pdf

Media Information Laboratory Past news | NTT Communication Science Laboratories | NTT R&D Website

, Tomohiro Tanaka, Takatomo Kano, Atsunori Ogawa, Marc Delcroix, ” Transfer Learning from Pre-trained

https://www.rd.ntt/e/cs/team_project/media/past_news.html

Media Information Laboratory | NTT Communication Science Laboratories | NTT R&D Website

, Atsunori Ogawa & Marc Delcroix (2023). Transfer Learning from Pre-trained Language Models Improves End-to

https://www.rd.ntt/e/cs/team_project/media/

NTT R&D Forum - Road to IOWN 2022｜NTT R&D Website

with high-precision AI N-E16IOWN EvolutionSelf-evolving NW-AI framework using autonomous and transfer

https://www.rd.ntt/e/forum/2022/exhibit.html

Wireless Technologies toward Extreme NaaS—Multi-radio Proactive Control Technologies (Cradio®)｜NTT R&D Website

base station targeted for use. Prediction technology using AI also uses transfer learning technology

https://www.rd.ntt/e/research/JN202108_14898.html

2020_booklet_en.pdf

Science of Machine Learning Science of Communication and Computation 01. People on the WWW, give

https://www.rd.ntt/cs/event/openhouse/2020/download/2020_booklet_en.pdf

0015.pdf

number called the learning rate. Thus, 0 < c ≤ 1 is a region for faster convergence with the ratio of r

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0015.pdf

メディア情報研究部　過去のニュース｜NTTコミュニケーション科学基礎研究所｜NTT R&D Website

, ” Transfer Learning from Pre-trained Language Models Improves End-to-End Speech Summarization” ・Takuhiro

https://www.rd.ntt/cs/team_project/media/past_news.html

筋協調運動を促す運動能力転写技術【運動能力転写技術の一形態】 | NTT R&D Website

. Motor-Skill-Transfer Technology for Piano Playing with Electrical Muscle Stimulation. In SIGGRAPH Asia

https://www.rd.ntt/iown_tech/post_39.html

メディア情報研究部｜NTTコミュニケーション科学基礎研究所｜NTT R&D Website

, Atsunori Ogawa & Marc Delcroix (2023). Transfer Learning from Pre-trained Language Models Improves End-to

https://www.rd.ntt/cs/team_project/media/

0090.pdf

learning algorithm. Based on a local convergence anal- ysis, the optimal nonlinearity gm(.) is suggested to

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0090.pdf