Nontawat Ch. (@NolfwinMk) header
Nontawat Ch. (@NolfwinMk) profile picture

Researcher at Preferred Networks (PFN, @PreferredNet).

Tokyo-to, Japan
Joined July 2012
Photo by Nontawat Ch. (@NolfwinMk)Photo by Nontawat Ch. (@NolfwinMk)Photo by Nontawat Ch. (@NolfwinMk)Photo by Nontawat Ch. (@NolfwinMk)Photo by Nontawat Ch. (@NolfwinMk)Photo by Nontawat Ch. (@NolfwinMk)Photo by Nontawat Ch. (@NolfwinMk)Photo by Nontawat Ch. (@NolfwinMk)Photo by Nontawat Ch. (@NolfwinMk)Photo by Nontawat Ch. (@NolfwinMk)
I graduated last September and received the Dean’s award today (2022/03/24). I have been fortunate to meet with so many wonderful people here in UTokyo. I wish them the best for their future. I would not have been able to receive this award without their support.
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After graduation, I have joined Preferred Networks in October 2021 as a researcher to work on applications in healthcare and quantum chemistry domains. I will still be in Tokyo for a while :)
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Nontawat Ch. retweeted
🖼 A picture is worth a thousand words - especially when the words used to describe it are wrong. In this #MadeWithTFJS episode, @helloksong shows how adversarial.js can break any neural network in browser to change a 🐕 into a 🌭 and more. 📺 → goo.gle/3sgpGJY
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Nontawat Ch. retweeted
We're going to hold a talk even "Learning theory of loss functions" on Dec 15 morning (Dec 14 evening in the US). Three Ph.D. student speakers (Jessie from CU Boulder, Yutong from UMich, and I) introduce recent work. Please check it out! c5dc59ed978213830355fc8978.d…
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The pre-print of our #emnlp2020 paper is now on ArXiv. arxiv.org/pdf/2010.04987.pdf So, I would like to use this thread to explain what we did. Basically, we proposed FIND -- a framework which enables humans to debug deep text classifiers. FIND = Feature Investigation aNd Disabling
Our work on human-in-the-loop debugging deep text classifiers (joint work with my amazing supervisors @fra_toni and @lspecia) has been accepted to appear at #emnlp2020 !! Here, we made interpretability more actionable for debugging. Stay tuned for the details. 🎉
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Nontawat Ch. retweeted
Great online talk event organized by @DiadochosT! I found a lot of enjoyable future work in transfer learning :) teapaw.org/DiadochosT/status/1314…
10/22(木)午前にPhD学生によるトークイベントを開催します! 「Transfer Learning between Largely Different Distributions」のテーマで,StanfordとMITのPhDの3名を招待して25分ずつのトークをして頂き,自分も最後に話します. なにとぞご参加ください! 参加登録はこちらから↓
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I am very thankful to Google for this award! I also would like to express my gratitude to my lab members, colleagues, friends, and family for their support. Thank you so much :)
Google created the PhD Fellowship Program in 2009 to recognize and support outstanding graduate students pursuing exceptional research in computer science and related fields. Today, we congratulate the recipients of the 2020 Google PhD Fellowship! goo.gle/3nt9unn
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Nontawat Ch. retweeted
Fresh from the press: "An Elementary Introduction to Information Geometry" mdpi.com/1099-4300/22/10/110… @Entropy_MDPI #InformationGeometry
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Nontawat Ch. retweeted
Our work "Learning from Aggregate Observations" has been accepted to #NeurIPS 2020! We study a general *weakly-supervised learning* problem where supervision signals are given to *sets* of instances, while the goal is still to predict labels of unseen individuals.
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ตู้เย็นมาเสียอะไรตอนนี้~
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Nontawat Ch. retweeted
Our new work is out!
Time-varying Gaussian Process Bandit Optimization with Non-constant Evaluation Time. (arXiv:2003.04691v1 [stat.ML]) ift.tt/2vNFtZE
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This work explores how causal models can be fully exploited for domain adaptation! Intuition: humans care about causality (partially) because causal knowledge, once discovered, applies to different systems. ---- Joint work w/ Prof. Sato and Prof. Sugiyama. Comments appreciated!
Few-shot Domain Adaptation by Causal Mechanism Transfer. arxiv.org/abs/2002.03497
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Nontawat Ch. retweeted
Our paper on linear-fractional metric optimization (arxiv.org/abs/1905.12511) has been accepted to AISTATS2020! (the preprint will be updated soon) 久々に主著論文が採択されました。あと地味に今日誕生日(東海岸時間で)なので、誕生日アクセプトです。よかった、、
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Totally agree! Definitely one of the best talks at #NeurIPS2019. Very well-prepared and impressive.
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Today at #NeurIPS2019, @nichenri1995 will present our work "On the Calibration of Multiclass Classification with Rejection" by Chenri Ni, Nontawat Charoenphakdee, Junya Honda, and Masashi Sugiyama. Tue Dec 10th, 10:45-12:45 East Exhibition Hall B+C #224 papers.nips.cc/paper/8527-on…
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Please come to our poster if you are interested! Poster: nolfwin.github.io/assets/pos… Paper: papers.nips.cc/paper/8527-on…
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Nontawat Ch. retweeted
Tutorial starts at 8:30 am (sorry not at 9am). Slides and a paper with some of the proofs are here. Slides might take a while to download (heavy!) emtiyaz.github.io/papers/neu… emtiyaz.github.io/papers/lea…
Excited for the tutorial tomorrow (Dec 9) at 9am at #NeurIPS2019 If you are at the conference and would to chat, please send me an email (also, if you are interested in a post-doc position in our group at Tokyo). nips.cc/Conferences/2019/Sch…
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