Personal Information
Organização/Local de trabalho
Within 23 wards, Tokyo, Japan Japan
Cargo
Data Scientist
Setor
Technology / Software / Internet
Sobre
My responsibilities are
- to deliver relevant ads or organic news article for docomo user
- to optimize advertiser's KPI(ROAS, CPA, CVR).
Through these job experiences, I have grown up the following four strong points, ①Service Strategy②Research③Development④Sales and Consulting.
①Service Strategy
Google has so sophiscated Sponsord Search ads, on the other hand we also have the product.
So, we have to think about why advertisers use D2C Sponsord Search ads.
I think the solution is so simple and it is just the more efficient performance compared with the Google product.
To do so, we have to hold some mathematical model to predict or recommend relevant information for many users.
②Researc...
Marcadores
regret minimization
Ver mais
Apresentações
(15)Documentos
(4)Gostaram
(314)「ベータ分布の謎に迫る」第6回 プログラマのための数学勉強会 LT資料
Ken'ichi Matsui
•
Há 8 anos
動的計画法を極める！
HCPC: 北海道大学競技プログラミングサークル
•
Há 7 anos
最適化超入門
Takami Sato
•
Há 9 anos
Conditional Image Generation with PixelCNN Decoders
suga93
•
Há 7 anos
20170422 数学カフェ Part2
Kenta Oono
•
Há 7 anos
ConvNetの歴史とResNet亜種、ベストプラクティス
Yusuke Uchida
•
Há 7 anos
機械学習の精度と売上の関係
Tokoroten Nakayama
•
Há 6 anos
Recommender Systems: Advances in Collaborative Filtering
Changsung Moon
•
Há 8 anos
音源分離における音響モデリング（Acoustic modeling in audio source separation）
Daichi Kitamura
•
Há 6 anos
Diversity and novelty for recommendation system
Zhenv5
•
Há 11 anos
More modern gpu
Preferred Networks
•
Há 8 anos
Deep Learning and Automatic Differentiation from Theano to PyTorch
inside-BigData.com
•
Há 6 anos
Assurtech : shift technology
Serrerom
•
Há 6 anos
Utilizing Marginal Net Utility for Recommendation in E-commerce
Liangjie Hong
•
Há 11 anos
[Rec sys2013勉強会]using maximum coverage to optimize recommendation systems in e commerce
Motoya Wakiyama
•
Há 10 anos
Recsys 2016: Modeling Contextual Information in Session-Aware Recommender Systems with Neural Networks (Bartłomiej Twardowski)
Bartlomiej Twardowski
•
Há 7 anos
C++による数値解析の並列化手法
dc1394
•
Há 7 anos
論文輪読資料「Gated Feedback Recurrent Neural Networks」
kurotaki_weblab
•
Há 8 anos
Outbrain click prediction by vishalchangrani
Vishal Changrani
•
Há 7 anos
Outbrain Click Prediction
Alexey Grigorev
•
Há 7 anos
文章を読み、理解する機能の獲得に向けて-Machine Comprehensionの研究動向-
Takahiro Kubo
•
Há 7 anos
[AWSマイスターシリーズ] Amazon Elastic MapReduce (EMR)
Amazon Web Services Japan
•
Há 10 anos
Deep learning を用いた画像から説明文の自動生成に関する研究の紹介
株式会社メタップスホールディングス
•
Há 8 anos
Heterogeneous Workflows With Spark At Netflix
Jen Aman
•
Há 7 anos
Learning to understand phrases by embedding the dictionary
Roelof Pieters
•
Há 9 anos
Improving neural networks by preventing co adaptation of feature detectors
Junya Saito
•
Há 10 anos
畳み込みニューラルネットワークを用いた複単語表現の解析
奈良先端大 情報科学研究科
•
Há 7 anos
深層リカレントニューラルネットワークを用いた日本語述語項構造解析
Hiroki Ouchi
•
Há 7 anos
Personal Information
Organização/Local de trabalho
Within 23 wards, Tokyo, Japan Japan
Cargo
Data Scientist
Setor
Technology / Software / Internet
Sobre
My responsibilities are
- to deliver relevant ads or organic news article for docomo user
- to optimize advertiser's KPI(ROAS, CPA, CVR).
Through these job experiences, I have grown up the following four strong points, ①Service Strategy②Research③Development④Sales and Consulting.
①Service Strategy
Google has so sophiscated Sponsord Search ads, on the other hand we also have the product.
So, we have to think about why advertisers use D2C Sponsord Search ads.
I think the solution is so simple and it is just the more efficient performance compared with the Google product.
To do so, we have to hold some mathematical model to predict or recommend relevant information for many users.
②Researc...
Marcadores
regret minimization
Ver mais