nanofi

machine learning, statistics, functional estimation, fairness, privacy.

[nanofi @white_output]

めちゃくちゃ揺れた

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帰宅

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帰国

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ワークショップ1日分出てないけど疲労困憊

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帰る。

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日本戻ると暑いのか

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ホテル着いた

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金浦空港　着

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搭乗。

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Heading to ICML 2026. Looking forward to meeting all of you in Seoul, Korea! Here is the list of presentations from our laboratory and our collaborators. #ICML2026

https://t.co/DyTRLyRz4z
https://t.co/hC56A2Yo8z

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to 羽田

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モダンMLにおいてERMの概念はいらない？

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Thrilled to share that our paper, "Fair Classification with Efficient and Post-hoc Controllable Fairness-Accuracy Trade-off," has been accepted as a Spotlight at ICML 2026! Looking forward to presenting it in Seoul next week. Hope to see you there! https://t.co/caUwllCsmh

[情報論的学習理論と機械学習：IBISML @ibisml]

IBIS2026のホームページを公開しました。
・日時：2026年10月26日～29日
・会場：ソニックシティ（埼玉）
追加情報は決定次第、更新していきます。今年もアツいIBISに乞うご期待！
https://t.co/I64BZoVnfo

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余震

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Our new preprint about data scaling laws for pre-training is out!

[Statistics (Machine Learning) Papers @StatsPapers]

Provable Data Scaling Law for Meta Learning via Complexity Minimization

Kazuto Fukuchi, Ryuichiro Hataya, Kota Matsui
https://t.co/IDI2UnywlX [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶]

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Gold Reviewer at ICML2026!

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帰宅。皆様お疲れ様でした。

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帰国

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ヘルシンキから東京