cvpaper.challenge の Meta Study Group 発表スライド
cvpaper.challenge はコンピュータビジョン分野の今を映し、トレンドを創り出す挑戦です。論文サマリ・アイディア考案・議論・実装・論文投稿に取り組み、凡ゆる知識を共有します。2019の目標「トップ会議30+本投稿」「2回以上のトップ会議網羅的サーベイ」
http://xpaperchallenge.org/cv/
2019/10/16
初心者向けCTFのWeb分野の強化法
CTFのweb分野を勉強しているものの本番でなかなか解けないと悩んでいないでしょうか?そんな悩みを持った方を対象に、私の経験からweb分野の強化法を解説します。
How to strengthen the CTF Web field for beginners !!
Although you are studying the CTF web field, are you worried that you can't solve it in production?
For those who have such problems, I will explain how to strengthen the web field based on my experience.
(study group) https://yahoo-osaka.connpass.com/event/149524/
- The document discusses several papers related to algorithmic fairness in machine learning. It summarizes papers that propose definitions of fairness, present algorithms for learning fair representations and classifiers, and analyze fairness in contextual settings like bandits and reinforcement learning.
- The summaries cover work on ensuring equality of opportunity, calibration, awareness-based fairness, reduction-based approaches, learning fair representations without adversarial training, and analyzing fairness in online and sequential decision making problems.
- Concerns about potential issues like inherent tradeoffs in fairness, fairwashing by rationalization, and faking fairness through sampling biases are also mentioned.
最高の統計ソフトウェアはどれか? "What’s the Best Statistical Software? A Comparison of R, Py...ケンタ タナカ
"What’s the Best Statistical Software? A Comparison of R, Python, SAS, SPSS and STATA" https://www.inwt-statistics.com/read-blog/comparison-of-r-python-sas-spss-and-stata.html の抄訳です。
cvpaper.challenge の Meta Study Group 発表スライド
cvpaper.challenge はコンピュータビジョン分野の今を映し、トレンドを創り出す挑戦です。論文サマリ・アイディア考案・議論・実装・論文投稿に取り組み、凡ゆる知識を共有します。2019の目標「トップ会議30+本投稿」「2回以上のトップ会議網羅的サーベイ」
http://xpaperchallenge.org/cv/
2019/10/16
初心者向けCTFのWeb分野の強化法
CTFのweb分野を勉強しているものの本番でなかなか解けないと悩んでいないでしょうか?そんな悩みを持った方を対象に、私の経験からweb分野の強化法を解説します。
How to strengthen the CTF Web field for beginners !!
Although you are studying the CTF web field, are you worried that you can't solve it in production?
For those who have such problems, I will explain how to strengthen the web field based on my experience.
(study group) https://yahoo-osaka.connpass.com/event/149524/
- The document discusses several papers related to algorithmic fairness in machine learning. It summarizes papers that propose definitions of fairness, present algorithms for learning fair representations and classifiers, and analyze fairness in contextual settings like bandits and reinforcement learning.
- The summaries cover work on ensuring equality of opportunity, calibration, awareness-based fairness, reduction-based approaches, learning fair representations without adversarial training, and analyzing fairness in online and sequential decision making problems.
- Concerns about potential issues like inherent tradeoffs in fairness, fairwashing by rationalization, and faking fairness through sampling biases are also mentioned.
最高の統計ソフトウェアはどれか? "What’s the Best Statistical Software? A Comparison of R, Py...ケンタ タナカ
"What’s the Best Statistical Software? A Comparison of R, Python, SAS, SPSS and STATA" https://www.inwt-statistics.com/read-blog/comparison-of-r-python-sas-spss-and-stata.html の抄訳です。