Takanori Nakai

25 Followers

19 SlideShares 25 Followers 4 Followings

19 SlideShares 25 Followers 4 Followings

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...

regret minimization

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Activity
About

Topic discovery through data dependent and random projections

10 years ago • 433 Views

Psychological Advertising_Exploring User Psychology for Click Prediction in Sponsored Search

10 years ago • 597 Views

Unsupervised Graph-based Topic Labelling using DBpedia

10 years ago • 694 Views

Query driven context aware recommendation

10 years ago • 1714 Views

Similarity component analysis

10 years ago • 4718 Views

Modeling Mass Protest Adoption in Social Network Communities using Geometric Brownian Motion

9 years ago • 913 Views

Positive Unlabeled Learning for Deceptive Reviews Detection

9 years ago • 6463 Views

Analysis of Learning from Positive and Unlabeled Data

9 years ago • 6191 Views

高次元データの統計：スパース正則化の近似誤差と推定誤差

9 years ago • 1747 Views

Preference-oriented Social Networks_Group Recommendation and Inference

8 years ago • 524 Views

Learning Better Embeddings for Rare Words Using Distributional Representations

8 years ago • 13103 Views

GBDTを使ったfeature transformationの適用例

7 years ago • 24010 Views

ICLR2017読み会 Data Noising as Smoothing in Neural Network Language Models @Dena

6 years ago • 33533 Views

WSDM2018 読み会 Latent cross making use of context in recurrent recommender systems.slide

6 years ago • 1800 Views

Sentence-State LSTM for Text Representation

5 years ago • 4009 Views

金利期間構造について:Forward Martingale Measureの導出

10 years ago • 676 Views

PUCKモデルの適用例：修論を仕上げた後、個人的にやっていたリサーチ

10 years ago • 2855 Views

Adaptive subgradient methods for online learning and stochastic optimization note

7 years ago • 390 Views

Note : Noise constastive estimation of unnormalized statictics methods

7 years ago • 797 Views

「ベ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 • 8 years ago

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 • 7 years ago

最適化超入門

Takami Sato • 9 years ago

Deep time-to-failure: predicting failures, churns and customer lifetime with RNN by Gianmario Spacagna, Chief Scientist at Cubeyou AI

Data Science Milan • 5 years ago

Conditional Image Generation with PixelCNN Decoders

suga93 • 7 years ago

20170422 数学カフェ Part2

Kenta Oono • 7 years ago

ConvNetの歴史とResNet亜種、ベストプラクティス

Yusuke Uchida • 7 years ago

機械学習の精度と売上の関係

Tokoroten Nakayama • 6 years ago

Recommender Systems: Advances in Collaborative Filtering

Changsung Moon • 8 years ago

音源分離における音響モデリング（Acoustic modeling in audio source separation）

Daichi Kitamura • 6 years ago

Factorization Meets the Item Embedding: Regularizing Matrix Factorization with Item Co-occurrence

Dawen Liang • 7 years ago

Diversity and novelty for recommendation system

Zhenv5 • 11 years ago

More modern gpu

Preferred Networks • 8 years ago

Deep Learning and Automatic Differentiation from Theano to PyTorch

inside-BigData.com • 6 years ago

Assurtech : shift technology

Serrerom • 6 years ago

Utilizing Marginal Net Utility for Recommendation in E-commerce

Liangjie Hong • 11 years ago

[Rec sys2013勉強会]using maximum coverage to optimize recommendation systems in e commerce

Motoya Wakiyama • 10 years ago

Recsys 2016: Modeling Contextual Information in Session-Aware Recommender Systems with Neural Networks (Bartłomiej Twardowski)

Bartlomiej Twardowski • 7 years ago

C++による数値解析の並列化手法

dc1394 • 7 years ago

論文輪読資料「Gated Feedback Recurrent Neural Networks」

kurotaki_weblab • 8 years ago

Outbrain click prediction by vishalchangrani

Vishal Changrani • 7 years ago

Outbrain Click Prediction

Alexey Grigorev • 7 years ago

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 • 7 years ago

[AWSマイスターシリーズ] Amazon Elastic MapReduce (EMR)

Amazon Web Services Japan • 10 years ago

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 • 8 years ago

Heterogeneous Workflows With Spark At Netflix

Jen Aman • 7 years ago

Learning to understand phrases by embedding the dictionary

Roelof Pieters • 9 years ago

Improving neural networks by preventing co adaptation of feature detectors

Junya Saito • 10 years ago

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 • 7 years ago

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 • 7 years ago

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...

regret minimization

See more