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Microsoft News Center
Eric Horvitz, managing co-director of Microsoft Research Redmond, discusses the computing advances on the horizon, the influence they will have, and how insights from big data and smarter software will change the world.
News details
Date: 15 February 2013
Type: Headline
Inside Microsoft Research
Hoping to increase diversity within the computer-science community, researchers from New York City are organizing the Microsoft Research Data Science Summer School.
News details
Date: 27 February 2014
Type: Headline
John Bronskill
In the traditional approach to problem solving with machine learning, the developer typically selects from amongst the many machine learning algorithms developed over the last few decades. In this talk we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language and the corresponding custom machine learning code is then generated automatically. This model-based...
Video details
Date: 15 November 2012
Duration: 00:26:04
Publisher: Microsoft
When Urban Air Quality Meets Big Data Urban air quality -- the concentration of PM2.5 -- is of great importance in protecting human health. While there are limited air-quality-monitor-stations in a city, air quality varies by location significantly and is influenced by multiple complex factors, such as traffic flow and land use. Consequently, people cannot know the air quality of a location without a monitoring station. This project infers real-time, fine-grained air-quality information throughout a city, based on air-quality data reported by...
Video details
Date: 17 April 2014
Duration: 00:03:12
Collection: TechFair 2014
Publisher: Microsoft
Next at Microsoft Podcast
Microsoft researcher Drew Purves and AccuWeather Vice President Jon Porter dive deep into predictive analytics in the fourth episode of the Next at Microsoft podcast series.
News details
Date: 16 June 2015
Type: Headline
Yu Zheng, Xiuwen Yi, Ming Li, Ruiyuan Li, Zhangqing Shan, Eric Chang, and Tianrui Li

In this paper, we forecast the reading of an air quality monitoring station in the next 48 hours, using a data-driven method that considers the current meteorological data, weather forecasts, and the air quality data of the station and that of other stations within a few hundred kilometers to the station. Our predictive model is comprised of four major components: 1) a linear regression-based temporal predictor to model the local factor of air quality, 2) a neural network-based spatial predictor...

Publication details
Date: 1 August 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Microsoft Research Connections Blog
A team from a Swiss university, with help from Microsoft Research, is seeking ways to help consumers struggling to cope with the deluge of photos and videos they have amassed.
News details
Date: 5 September 2014
Type: Headline
Openness@Microsoft
Microsoft researchers discuss the latest on Naiad, an open-source, .NET-based platform for high-throughput, low-latency data analysis.
News details
Date: 28 May 2014
Type: Headline
Openness@Microsoft
Michael Isard, Derek Murray, and Frank McSherry of Microsoft discuss Naiad, an open-source, .NET-based platform for high-throughput, low-latency data analysis.
News details
Date: 28 May 2014
Type: Headline
Xconomy
On May 5, in New York’s Flatiron District, Microsoft Research New York City opened its doors to give the world a glimpse of what its data scientists are up to.
News details
Date: 6 May 2014
Type: Headline
Inside Microsoft Research
The inaugural Big-Data Analytics workshop, hosted by Microsoft Research Cambridge on May 23-24, provided discussion about the best ways to cope with the unprecedented deluge of big data that has become available in recent years.
News details
Date: 19 June 2013
Type: Headline
Microsoft Research Connections Blog
Tsinghua University and Microsoft Research Asia have established a pioneering graduate course on Big Data Foundations and Applications, to enhance students' understanding of big data and provide an opportunity to conduct experiments using Microsoft Azure.
News details
Date: 31 December 2014
Type: Headline
Mike Barnett, Badrish Chandramouli, Robert DeLine, Steven Drucker, Danyel Fisher, Jonathan Goldstein, Patrick Morrison, and John Platt

Exploratory analysis on big data requires us to rethink data management across the entire stack – from the underlying data processing techniques to the user experience. We demonstrate Stat! – a visualization and analytics environment that allows users to rapidly experiment with exploratory queries over big data. Data scientists can use Stat! to quickly refine to the correct query, while getting immediate feedback after processing a fraction of the data. Stat! can work with multiple processing engines in...

Publication details
Date: 1 June 2013
Type: Inproceeding
Publisher: ACM SIGMOD
Six Provocations for Big DataWith big data come big responsibilities, specifically in the realm of social media. There is a hint an emergence of a philosophy that big data is all one needs and that other scientific methods and disciplines are becoming outdated and unimportant. But big data can be incomplete because of how fragile data sources such as the Internet can be. Different social behaviors can be mapped but not necessarily compared because of the social channels being used. For example, a relative to whom one is close might...
Video details
Date: 27 September 2011
Duration: 00:12:38
Collection: 20th Anniversary Lecture Series
Publisher: Microsoft
Yu Zheng, Furui Liu, and Hsun-Ping Hsieh

Information about urban air quality, e.g., the concentration of PM2.5, is of great importance to protect human health and control air pollution. While there are limited air-quality-monitor-stations in a city, air quality varies in urban spaces non-linearly and depends on multiple factors, such as meteorology, traffic volume, and land uses. In this paper, we infer the real-time and fine-grained air quality information throughout a city, based on the (historical and real-time) air quality data reported by...

Publication details
Date: 1 August 2013
Type: Inproceeding
Publisher: ACM
The New York Times
The term big data connotes the certainty of truth, but there are hazards present, some human, some technological.
News details
Date: 3 June 2013
Type: Headline
Inside Microsoft Research
Kate Crawford, principal researcher at Microsoft Research New England, has contributed an article to the Harvard Business Review entitled The Hidden Biases in Big Data.
News details
Date: 2 April 2013
Type: Headline
It has become increasingly difficult to process information from the vast amount of data collected and stored in different computer systems all around us. The main challenge is how to design distributed and scalable algorithms and systems to extract useful information from this large quantity of data. The goal of this project is to address various questions related to distributed and scalable processing of big data.
Project details
Labs: Cambridge
Microsoft Research Connections Blog
Big data has become a key topic for scientists, researchers, and technologists, as became obvious to those attending Microsoft Research's 2012 eScience Workshop.
News details
Date: 8 October 2012
Type: Headline
Fortune
A new research lab in the heart of New York City is tasked with parsing the next big thing in technology.
News details
Date: 20 August 2012
Type: Headline
Milan VojnovicSENIOR RESEARCHER
Person details
Labs: Cambridge
The Web is described as a distributed, large-scale, volatile, unstructured, heterogeneous, and hidden information source, which poses big challenges to the management of Web data. The mission of Web Data Management (WDM) Group is to develop systems and algorithms to address these challenges and thus make Web data management as effective as a database system, and as flexible as an information retrieval system.
Group details
Labs: Asia
Quick interaction between a human teacher and a learning machine presents numerous benefits and challenges when working with web-scale data. The human teacher guides the machine towards accomplishing the task of interest. The system leverages big data to find examples that maximize the training value of its interaction with the teacher.
Project details
Labs: Redmond
Quick interaction between a human teacher and a learning machine presents numerous benefits and challenges when working with web-scale data. The human teacher guides the machine towards accomplishing the task of interest. The system leverages big data to find examples that maximize the training value of its interaction with the teacher.
Project details
Labs: New York | Redmond
Francis Bach and Leon Bottou
Research in Focus: Large-Scale Machine LearningThe emergence of Big Data has outstripped the power of computers. The computing power required to analyze grows exponentially with the data. Francis Bach, SIERRA Research Team Leader, INRIA, and Léon Bottou, Principal Researcher, Microsoft Research, describe how researchers are using machine learning to meet the challenge of developing algorithms that balance the competing needs of predicting well and predicting quickly.
Video details
Date: 7 March 2013
Duration: 00:09:22
Publisher: Microsoft
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