Kento Nozawa
Short bio
Kento Nozawa is an engineer at Preferred Networks, Inc. and Preferred Elements, Inc. Recently, he has fine-tuned in-house LLMs, PLaMo. He completed his Ph.D. under the supervision of Dr. Issei Sato at Issei Sato Lab in The University of Tokyo. Back then, he was working on self-supervised representation learning, especially contrastive representation learning.
Selected papers
- Han Bao, Yoshihiro Nagano and Kento Nozawa. On the Surrogate Gap between Contrastive and Supervised Losses. In ICML, pages 1585–1606, 2022.
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.Alphabetical ordering and equal contribution. - Kento Nozawa and Issei Sato. Evaluation Methods for Representation Learning: A Survey. In IJCAI-ECAI Survey Track, pages 5556–5563, 2022.
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.Extended version: ``Empirical Evaluation and Theoretical Analysis for Representation Learning: A Survey’’. 2022.arXiv
- Kento Nozawa and Issei Sato. Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning. In NeurIPS, pages 5784–5797, 2021.
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. - Kento Nozawa, Pascal Germain and Benjamin Guedj. PAC-Bayesian Contrastive Unsupervised Representation Learning. In UAI, pages 21–30, 2020.
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. - Atsunori Kanemura, Yuhsen Cheng, Takumi Kaneko, Kento Nozawa and Shuichi Fukunaga. Imputing Missing Values in EEG with Multivariate Autoregressive Models. In EMBC, pages 2639–2642, 2018.
Pre-print
- Kento Nozawa, Takashi Masuko and Toru Taniguchi. Enhancing Large Language Model-based Speech Recognition by Contextualization for Rare and Ambiguous Words. 2024.
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The full publication list is available on Google Scholar.