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

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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

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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

R&D History | NTT R&D Website

) and heart rate. Developed Jubatus, an open source machine learning platform that intelligently

https://www.rd.ntt/e/about/chronicle/

0193.pdf

generalization of the INFO- MAX method in two directions: (1) handling of nonlinear mixtures, and (2) learning

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0193.pdf

Xuebin Hu and Hidefumi Kobatake

ambiguity of permutation and scaling. Then we can either transfer the bin unmixing filters into time domain

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0026.pdf

Recognition Research Group | NTT Communication Science Laboratories | NTT R&D Website

Networks (IJCNN), 2019, pp. 1-8. A. Kumagai, T. Iwata, Y. Fujiwara, "Transfer metric learning for unseen

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

0136.pdf

incorporating the natural gradient ex- tension. We also present a learning method for the unknown parameters of

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0136.pdf

Unlimited Innovation for a Global Sustainable Society by IOWN | NTT R&D Website

communication infrastructure with an AI infrastructure designed for learning from diverse data. At Toyota, we

https://www.rd.ntt/e/forum/2024/keynote_3.html

0032.pdf

-GEOMETRIC LEARNING Tomoya TAKATANI, Tsuyoki NISHIKAWA, Hiroshi SARUWATARI, and Kiyohiro SHIKANO Graduate

https://www.rd.ntt/cs/team_project/icl/signal/iwaenc03/cdrom/data/0032.pdf

信号処理研究グループ｜NTTコミュニケーション科学基礎研究所｜NTT R&D Website

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

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

2019_booklet_english.pdf

Venue: NTT Keihanna Building 01 Learning and finding congestion-free routes ～Online shortest path

https://www.rd.ntt/cs/event/openhouse/2019/download/2019_booklet_english.pdf

NTTBrl_honbun_E_220301-2.indd

transfer and detection Nanodevices with Novel Functions Novel and high performance nanodevices based on

https://www.rd.ntt/e/brl/result/activities/file/annual_report/Annual_report_2021_E.pdf

0152.pdf

transfer function should be reduced. For the BSD based on independent component analysis (ICA), various

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0152.pdf

List of exhibits｜NTT R&D FORUM 2023 — IOWN ACCELERATION Report

delivers ultra big data to computing resources without copying for LLM learning Leaflet List of IOWN Now

https://www.rd.ntt/e/forum/2023/exhibit.html

西田 京介 | NTT R&D Website

Nishida, Koki Maeda, Kuniko Saito, "DueT: Image-Text Contrastive Transfer Learning with Dual-adapter

https://www.rd.ntt/organization/researcher/superior/s_033.html

感性情報処理 | NTT R&D Website

, Masahiro Kohjima, Yuki Kurauchi, Ryuji Yamamoto and Atsuyuki Morishima. "A Cluster-Aware Transfer Learning

https://www.rd.ntt/hil/category/emotion/

メディア認識研究グループ｜NTTコミュニケーション科学基礎研究所｜NTT R&D Website

), 2019, pp. 1-8. A. Kumagai, T. Iwata, Y. Fujiwara, "Transfer metric learning for unseen domains" in Proc

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

0062.pdf

algorithm [6] which attempts to maximize the information transfer from input to output using a neural

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0062.pdf

Report on the NTT R&D Forum 2018 (Autumn) | NTT R&D Website

, machine learning can obtain close to the most optimal guidance in a limited amount of time. In the future

https://www.rd.ntt/e/forum/forum2018_autumn.html

Microsoft Word - 3E3495A9-54B4-18FBD3.doc

Newton’s iterative methods are fast but sensitive to the initial value from which iterative learning

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0082.pdf

IOWN INTEGRAL | NTT R&D Website

transfer distance to slow down transfer speed and significantly increase backup time. On the other hand

https://www.rd.ntt/e/forum/2024/keynote_2.html

Abstracts of all papers, ICA2003

, and (B) the effect of the nonnegative constraints in ICA using the ensemble learning algorithm. Our

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/abst.html

Abstracts of all papers, ICA2003

, and (B) the effect of the nonnegative constraints in ICA using the ensemble learning algorithm. Our

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/abst.htm

List of Exhibitions | NTT R&D Website

preferred expressions. View the detail PDF Research UI/UX γ03-01Motor-skill transfer: Movement support via

https://www.rd.ntt/e/forum/2024/exhibit.html

Research and Development for Pioneering a New Communications Paradigm with Wide-area Coverage | NTT R&D Website

high-speed remote data-transfer technology for achieving high-capacity, low-latency data transfers

https://www.rd.ntt/e/research/JN202205_18109.html

Frontier Communication Laboratory | NTT Network Innovation Laboratories | NTT R&D Website

Remote Direct Memory Access (RDMA) that can directly transfer data between memory units with low latency

https://www.rd.ntt/e/mirai/organization/product_2/

NTT R&D FORUM 2024 | NTT R&D Website

deep learning software technology and computing infrastructure technology) and an NTT researcher who

https://www.rd.ntt/e/forum/2024/

Report on the NTT R&D Forum 2020｜NTT R&D Website

prediction, overlay network, video transfer, image analysis and network coordination device control. Moving

https://www.rd.ntt/e/forum/2020/

感性コミュニケーション | NTT R&D Website

2025 2024 2023 2022 2025 論文 Takeru Isaka and Iwaki Toshima. "Learning-Support Method for Professional

https://www.rd.ntt/dtc/gc1/

0110.pdf

extensive attention in signal and speech processing, machine learning, and neuroscience communities

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0110.pdf

論文｜NTT物性科学基礎研究所｜NTT R&D Website

. Friedland, Y. Hirayama, T. Fujisawa, T. Saku, and S. Tarucha "Tunnelling and transfer between 1D and 2D

https://www.rd.ntt/brl/result/publications/paper_1996.html

グラフィカルな文書を理解できる「tsuzumi」 | NTT R&D Website

．Saito：“DueT: Image-Text Contrastive Transfer Learning with Dual-adapter Tuning，”EMNLP 2023，pp．13607

https://www.rd.ntt/research/JN202406_26653.html

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

, and S. Tarucha "Tunnelling and transfer between 1D and 2D electrons in adjusted quantum wells with

https://www.rd.ntt/e/brl/result/publications/paper_1996.html

KIKKAWA.dvi

dynamical system: � ��� � ������� ! "��� # �� $��#&%�#(')'*'+# (1) where �,�-�. is a discrete-time transfer

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0106.pdf

Complete_Program_r1.pdf

for Deterministic Electron Transfer N. Ubbelohde, D. Reifert, M. Kokainis, A. Ambainis, V. Kashcheyevs

https://www.rd.ntt/brl/event/isntt2019/download/Complete_Program_r1.pdf

Annual_report_2020_E.pdf

thin films, which were achieved by a machine learning-assisted thin film growth technique. This first

https://www.rd.ntt/e/brl/result/activities/file/annual_report/Annual_report_2020_E.pdf

サイバネティックス | NTT R&D Website

Control System for Learning Circular Breathing. In Companion Proceedings of the Annual Symposium on

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

低次元構造研究グループ｜NTT物性科学基礎研究所｜NTT R&D Website

, M. Hashisaka, K. Sasaki, S. Sasaki, K. Watanabe, T. Taniguchi, and N. Kumada On-chip transfer of

https://www.rd.ntt/brl/group_introduction/group_002.html

Low-Dimensional Nanomaterials Research Group | NTT Basic Research Laboratories | NTT R&D Website

. Taniguchi, and N. Kumada On-chip transfer of ultrashort graphene plasmon wave packets using terahertz

https://www.rd.ntt/e/brl/group_introduction/group_002.html

NTT版LLM「tsuzumi」 | NTT R&D Website

. (3)T. Hasegawa, K. Nishida, K. Maeda, and K. Saito：“DueT：Image-Text Contrastive Transfer Learning

https://www.rd.ntt/research/JN202406_26651.html

program_for_web.pdf

Multichannel Least Squares Equalization of Room Transfer Functions

https://www.rd.ntt/cs/team_project/icl/signal/waspaa2007/program_for_web.pdf

0084.pdf

matrix, i.e. the transfer function matrix from the speakers to the microphones, becomes almost singular

https://www.rd.ntt/cs/team_project/icl/signal/iwaenc03/cdrom/data/0084.pdf

0031.pdf

marginal PDFs of yl(t). The iterative learning rule is given by w[j+1](n) = w[j](n) + η D−1X d=0 ( Iδ(n− d

https://www.rd.ntt/cs/team_project/icl/signal/iwaenc03/cdrom/data/0031.pdf

ICA2003_v2.dvi

function of EPICA, and (B) the effect of the nonnegative constraints in ICA using the ensem- ble learning

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0066.pdf

0128.pdf

original sources, which is a convolution of the ori- ginal source with the appropriate acoustic transfer

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0128.pdf

論文｜NTT物性科学基礎研究所｜NTT R&D Website

(2025). T. Okajima, R. Ohta, T. Sato, Y. Tachizaki, X. Xu, H. Okamoto, and Y. Ota "Transfer-printed

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

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

(2025). T. Okajima, R. Ohta, T. Sato, Y. Tachizaki, X. Xu, H. Okamoto, and Y. Ota "Transfer-printed

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

abst.pdf

2A-05] Stable Learning Algorithm for Blind Separation of Temporally Correlated Signals Combining

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

abst.pdf

2A-05] Stable Learning Algorithm for Blind Separation of Temporally Correlated Signals Combining

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/abst.pdf

Inclusive Core: Integrative and Cooperative Network Architecture for the 6G/IOWN Era - White paper | NTT R&D Website

infrastructure using artificial intelligence (AI) and machine learning (ML) in a variety of scenarios to secure

https://www.rd.ntt/e/ns/inclusivecore/whitepaper_ver1.html

Inclusive Core: Integrative and Cooperative Network Architecture for the 6G/IOWN Era - White paper | NTT R&D Website

machine learning (ML) in a variety of scenarios to secure efficiency, quality and performance, and

https://www.rd.ntt/e/ns/inclusivecore/whitepaper_ver2.html

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

effect in graphene transferred by water-soluble transfer sheet and home-use laminator" Jpn. J. Appl. Phys

https://www.rd.ntt/e/brl/result/publications/paper_2023.html