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检索条件"机构=Computer And Data Science Laboratories"
337 条 记 录,以下是91-100 订阅
排序:
Effects of local minima and bifurcation delay on combinatorial optimization with continuous variables
arXiv
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arXiv 2022年
作者: Sato, Shintaro NTT Computer and Data Science Laboratories NTT Corporation Musashino180-8585 Japan
Combinatorial optimization problems can be mapped onto Ising models, and their ground state is generally difficult to find. A lot of heuristics for these problems have been proposed, and one promising approach is to u... 详细信息
来源: 评论
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning
StyleAdv: Meta Style Adversarial Training for Cross-Domain F...
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Conference on computer Vision and Pattern Recognition (CVPR)
作者: Yuqian Fu Yu Xie Yanwei Fu Yu-Gang Jiang Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University Purple Mountain Laboratories Nanjing China School of Data Science Fudan University
Cross-Domain Few-Shot Learning (CD-FSL) is a recently emerging task that tackles few-shot learning across different domains. It aims at transferring prior knowledge learned on the source dataset to novel target datase...
来源: 评论
Recurrent neural networks for learning long-term temporal dependencies with reanalysis of time scale representation
arXiv
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arXiv 2021年
作者: Ohno, Kentaro Kumagai, Atsutoshi NTT Computer and Data Science Laboratories
Recurrent neural networks with a gating mechanism such as an LSTM or GRU are powerful tools to model sequential data. In the mechanism, a forget gate, which was introduced to control information flow in a hidden state... 详细信息
来源: 评论
Research on Transfer Learning to Give AI the Same Versatility and Skill as Humans
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NTT Technical Review 2021年 第12期19卷 12-15页
作者: Kumagai, Atsutoshi NTT Computer and Data Science Laboratories NTT Social Informatics Laboratories Japan
Machine learning is needed to build artificial intelligence (AI), and this requires a large amount of training data. Sometimes, however, you cannot get enough high-quality training data. What’s more, to prevent an AI... 详细信息
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Recurrent Neural Networks for Learning Long-term Temporal Dependencies with Reanalysis of Time Scale Representation
Recurrent Neural Networks for Learning Long-term Temporal De...
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IEEE International Conference on Big Knowledge (ICBK)
作者: Kentaro Ohno Atsutoshi Kumagai NTT Computer and Data Science Laboratories
Recurrent neural networks with a gating mechanism such as an LSTM or GRU are powerful tools to model sequential data. In the mechanism, a forget gate, which was introduced to control information flow in a hidden state... 详细信息
来源: 评论
Scheduling Space Expander: An Extension of Concurrency Control for data Ingestion Queries
arXiv
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arXiv 2023年
作者: Nakazono, Sho Uchiyama, Hiroyuki Fujiwara, Yasuhiro Kawashima, Hideyuki NTT Computer and Data Science Laboratories Tokyo Japan Recruit Co. Ltd. Tokyo Japan NTT Communication Science Laboratories Kanagawa Japan Faculty of Environment and Information Studies Keio University Kanagawa Japan
With the continuing advances of sensing devices and IoT applications, database systems needs to process data ingestion queries that update the sensor data frequently. To process data ingestion queries with transaction... 详细信息
来源: 评论
Few-shot learning for unsupervised feature selection
arXiv
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arXiv 2021年
作者: Kumagai, Atsutoshi Iwata, Tomoharu Fujiwara, Yasuhiro NTT Computer and Data Science Laboratories NTT Communication Science Laboratories
We propose a few-shot learning method for unsupervised feature selection, which is a task to select a subset of relevant features in unlabeled data. Existing methods usually require many instances for feature selectio... 详细信息
来源: 评论
Meta-learning for relative density-ratio estimation  21
Meta-learning for relative density-ratio estimation
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Proceedings of the 35th International Conference on Neural Information Processing Systems
作者: Atsutoshi Kumagai Tomoharu Iwata Yasuhiro Fujiwara NTT Computer and Data Science Laboratories NTT Communication Science Laboratories
The ratio of two probability densities, called a density-ratio, is a vital quantity in machine learning. In particular, a relative density-ratio, which is a bounded extension of the density-ratio, has received much at...
来源: 评论
Meta-learning for relative density-ratio estimation
arXiv
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arXiv 2021年
作者: Kumagai, Atsutoshi Iwata, Tomoharu Fujiwara, Yasuhiro NTT Computer and Data Science Laboratories NTT Communication Science Laboratories
The ratio of two probability densities, called a density-ratio, is a vital quantity in machine learning. In particular, a relative density-ratio, which is a bounded extension of the density-ratio, has received much at... 详细信息
来源: 评论
Designing Secure Sparse Coding via Multiple Random Unitary Transforms
Designing Secure Sparse Coding via Multiple Random Unitary T...
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2021 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2021
作者: Nakachi, Takayuki Bandoh, Yukihiro University of The Ryukyus Information Technology Center Okinawa Japan Nippon Telegraph and Telephone Corporation NTT Computer and Data Science Laboratories Kanagawa Japan
In this paper, we propose a design method of secure sparse coding via multiple random unitary transforms (RUTs). The proposed method operates as an Encryption-then-Compression (EtC) system. The multiple RUTs will incr... 详细信息
来源: 评论