Project Natick Phase 2
A research project to determine the feasibility of subsea datacenters powered by offshore renewable energy Project Natick seeks to understand the benefits and difficulties in deploying subsea datacenters worldwide. Phase two extends the research we accomplished in phase one by deploying a full-scale datacenter module in the North Sea, powered by renewable energy. This is the continuing story of Pr
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Microsoft Researchら、リアルタイムで異常事象を検出し要約ビデオを作成するAIベースのホームセキュリティ・システムを開発。学校や店内、交差点などで活用
Microsoft Researchら、リアルタイムで異常事象を検出し要約ビデオを作成するAIベースのホームセキュリティ・システムを開発。学校や店内、交差点などで活用 2017-06-17 Microsoft Research Asiaと中国の上海交通大学は、リアルタイムで異常事象を検出し、必要なオンライン要約ビデオを作成する機械学習を用いたスマートホームセキュリティ・システムを開発しました。 本システムは、屋内外のセキュリティにおいて、何か事象が起きた時にそれを検知し分析・記録するAIベースのシステムです。家、お店、ショッピングモール、学校、ストリート、交差点、などでの活用を目的としています。 ビジュアルオブジェクト検出、トラッキング、イベント解析を多層構造のニューラルネットワークDeep learningに基づくリアルタイムイベント検出方法を提案しました。この方法は、異なるシナリオで何
F# Manual
F# is similar to the Caml programming language family, and was partially inspired by OCaml. However, the F# compiler implementation is a new re-implementation of a Caml-style language, and some relatively minor differences in the implemented languages exist, much as relatively minor differences exist between "Caml Light" and "OCaml". One of the explicit aims of F# is to make it feasible to cross-c
Efficient Non-greedy Optimization of Decision Trees
Decision trees and randomized forests are widely used in computer vision and machine learning. Standard algorithms for decision tree induction optimize the split functions one node at a time according to some splitting criteria. This greedy procedure often leads to suboptimal trees. In this paper, we present an algorithm for optimizing the split functions at all levels of the tree jointly with the
The Implementation of Functional Programming Languages
Simon Peyton Jones Published by Prentice Hall Internaltional (UK) Ltd. | April 1987 Chapters also by: Philip Wadler, Programming Research Group, Oxford; Peter Hancock, Metier Management Systems, Ltd.; David Turner, University of Kent, Canterbury “The Implementation of Functional Languages” is a book about implementing functional programming languages using lazy graph reduction, and it divides into
池内克史 - Wikipedia
池内 克史（いけうち かつし）は、日本のコンピュータビジョン分野の計算機科学者。 経歴・人物[編集] 大阪府生まれ。大阪府立茨木高等学校卒業。京都大学工学部機械工学科卒業。東京大学大学院工学系研究科情報工学専攻博士課程修了、工学博士。 学位論文は「Graph description principle based on image processing by human（人間の視覚のモデル化に基づく図形記述方針）」[1]。人間の漢字読み取りの過程のモデル化を行い、短時間漢字を見せ読み取り誤りの減少をこのモデルで予測することで、モデルの正当性を検証した。 博士取得後すぐにMIT人工知能研究所にポスドクとして渡米、その後電子技術総合研究所（現産業技術総合研究所）を経て再度渡米、カーネギーメロン大学ロボティクス研究所の研究員となる。東京大学生産技術研究所、東京大学大学院情報学環の教授を経て、マイ
Computer Scientists Don't Learn Math
Why Don't Computer Scientists Learn Math? Last modified 28 March 2017 I recently attended the Heidelberg Laureate Forum, in which some older researchers--mainly Fields Medalists and Turing Award winners--talked to and with young researchers. The young researchers ranged from a few students just entering university to young faculty members, most being graduate students. They came from all over th
Haskell and transactional memory - Microsoft Research
Slides in Japanese (opens in new tab) O’Reilly wrote up the meeting (opens in new tab). Here’s the translation into English: 150 Haskeller were excited! “Haskellers Meeting 2010 Spring” was held in IIJ conference room, Kanda, Tokyo on April 16th. Simon Peyton Jones who is admired by Haskellers and also one of the authors of “Beautiful Code” gave a talk on “Haskell and Software Transaction Memory”.
Microsoft Concept Graph and Concept Tagging Release
Our mental world contains many concepts about worldly facts, and the Microsoft Concept Graph tries to duplicate them. It is a big graph of concepts, which is harnessed from billions of web pages and years' worth of search logs. See more details In the demo, you can input a single instance, and the return result is the its concept distribution with different scoring functions. Try the demo We provi
Microsoft Concept Graph and Concept Tagging Release
Download In this release, we only provide the core version of IsA data we mined from billions of web pages (Other data may release in future step by step). This data contains 5,376,526 unique concepts, 12,501,527 unique instances, and 85,101,174 IsA relations. The following is its sample data: Instance Concept Relations
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Time-Travel Debugging for JavaScript/Node.js - Microsoft Research
https://www.microsoft.com/en-us/research/wp-content/uploads/2016/08/dynamic.pdf?from=https://research.microsoft.com/en-us/um/people/simonpj/papers/haskell-dynamic/dynamic.pdf&type=exact
Photo Tourism: Microsoft Research, Interactive Visual Media Group
Photo Tourism: Microsoft Research, Interactive Visual Media Group
Old and New Matrix Algebra Useful for Statistics
Photo Tourism: Microsoft Research, Interactive Visual Media Group