poster_en.pdf
【Reference】【Co nt ac t】 Abstract Fast and Accurate Deep Learning Yasutoshi Ida Software Innovation
https://www.rd.ntt/cs/event/openhouse/2016/exhibition/7/poster_en.pdf
High-speed optical interconnect for AI : Distributed deep learning accelerator | NTT Device Technology Laboratories | NTT R&D Website
High-speed optical interconnect for AI : Distributed deep learning accelerator | NTT Device
https://www.rd.ntt/e/dtl/technology/pe_product-optical-interconnect.html
NTT Communication Science Laboratories Open House 2016
Fast and accurate deep learning - Efficient learning utilizing directions of past gradients - Abstract
https://www.rd.ntt/cs/event/openhouse/2016/exhibition/7/index_en.html
Sekitoshi Kanai | NTT Software Innovation Center | NTT R&D Website
Project Researcher (As of November 2018) Making the current deep learning with AI faster, easier and safer
https://www.rd.ntt/e/sic/team_researchers/researcher/249.html
スライド 1
Improving the accuracy of deep learning - Larger capacity output function for deep learning - Deep learning
https://www.rd.ntt/cs/event/openhouse/2019/download/04_a_en.pdf
NTT Communication Science Laboratories Open House 2019
Improving the accuracy of deep learning - Larger capacity output function for deep learning - Abstract Deep
https://www.rd.ntt/cs/event/openhouse/2019/exhibition4/index_en.html
スライド 1
for efficient object search We propose Adaptive Spotting, a deep reinforcement learning approach to
https://www.rd.ntt/cs/event/openhouse/2020/download/c_19_en.pdf
Network-AI技術 – 主要な外部発表
. Matsuo and K. Watanabe, "Fault Detection of ICT systems with Deep Learning Model for Missing Data, " 2021
https://www.rd.ntt/ns/qos/research/05/presentation.html
スライド 1
from their voices with deep learning model Applications Call center response decision, marketing
https://www.rd.ntt/cs/event/openhouse/2020/download/c_15_en.pdf
NTT Communication Science Laboratories Open House 2018 Program
environmental sensing and machine learning Memory efficient deep learning for mobile devices Quantized neural
https://www.rd.ntt/cs/event/openhouse/2018/program_en.html
NTT Communication Science Laboratories Open House 2018
analysis by environmental sensing and machine learning Memory efficient deep learning for mobile devices
https://www.rd.ntt/cs/event/openhouse/2018/en_simple/index_en.html
NTT Communication Science Laboratories Open House 2016
Thursday, June 2th 15:30 - 16:10 Avenues toward super-human speech recognizers - Advances in deep learning
https://www.rd.ntt/cs/event/openhouse/2016/talk/research1/index_en.html
NTT Communication Science Laboratories Open House 2017
Abstract The rapid progress of deep learning is impacting the world we live in. Media generation (e.g
https://www.rd.ntt/cs/event/openhouse/2017/talk/research2/index_en.html
KOBAYASHI, Masahiro
, May 2018. A. Suzuki and M. Kobayashi, "Multi-Agent Deep Reinforcement Learning for Cooperative
https://www.rd.ntt/e/ns/qos/person/m_kobayashi/
スライド 1
modeling,” under review.[2] T. Ngo, Z. Lu, G. Carneiro,“Combining deep learning and level set for the
https://www.rd.ntt/cs/event/openhouse/2020/download/c_21_en.pdf
NTT Communication Science Laboratories Open House 2020
technology and our approaches with the theme "What can be done when the voice is combined with deep learning
https://www.rd.ntt/cs/event/openhouse/2020/research1/index_en.html
スライド 1
Signal Processing Research Group, Media Information Laboratory We propose an AI system (a deep learning
https://www.rd.ntt/cs/event/openhouse/2018/exhibition/17/poster_en_17.pdf
NTT Communication Science Laboratories Open House 2017 Program
) 11:00 - 11:40 Generative personal assistance with audio and visual examples Deep learning opens the
https://www.rd.ntt/cs/event/openhouse/2017/program_en.html
田尻 兼悟
, Yasuhiro Ikeda, Yuusuke Nakano, Keishiro Watanabe“Dividing Deep Learning Model for Continuous Anomaly
https://www.rd.ntt/ns/qos/person/tajiri/
Automated Data Analysis "RakuDA" | NTT Software Innovation Center | NTT R&D Website
of distributed data processing platform SE project includes deep learning and machine learning. Our
https://www.rd.ntt/e/sic/team_researchers/team/250.html