Share on Facebook Tweet on Twitter Share on LinkedIn Share by email
Our research
Content type
+
Downloads (457)
+
Events (451)
 
Groups (152)
+
News (2759)
 
People (734)
 
Projects (1111)
+
Publications (12625)
+
Videos (5807)
Labs
Research areas
Algorithms and theory47205 (859)
Communication and collaboration47188 (1467)
Computational linguistics47189 (555)
Computational sciences47190 (823)
Computer systems and networking47191 (2151)
Computer vision208594 (1160)
Data mining and data management208595 (304)
Economics and computation47192 (333)
Education47193 (818)
Gaming47194 (408)
Graphics and multimedia47195 (1211)
Hardware and devices47196 (1090)
Health and well-being47197 (515)
Human-computer interaction47198 (2326)
Machine learning and intelligence47200 (1910)
Mobile computing208596 (200)
Quantum computing208597 (90)
Search, information retrieval, and knowledge management47199 (1802)
Security and privacy47202 (840)
Social media208598 (155)
Social sciences47203 (866)
Software development, programming principles, tools, and languages47204 (1580)
Speech recognition, synthesis, and dialog systems208599 (227)
Technology for emerging markets208600 (74)
1–25 of 24096
Sort
Show 25 | 50 | 100
1234567Next 
The international annual Quantum Information Processing (QIP) series is the premier meeting for theoretical quantum information research. Since 1998, the conference has featured breakthroughs by the leaders in the disciplines of computing, cryptography, information theory, mathematics and physics. The scientific objective of the series is to gather the theoretical quantum information community to present and discuss the latest groundbreaking work in the field.
Event details
Date: 18–22 January 2017
Location: Seattle, WA
Type: Conference
While using the Internet and mobile devices, people create data, whether intentionally or unintentionally, through their interaction with messaging services, websites and other applications and devices. This means that experiments with heretofore unprecedented populations can be performed in a variety of topics. Our workshop will focus on observational studies which arise from these interactions and data, with a focus on experiments that can indicate causal inferences. Human generated content
Event details
Date: 21–23 March 2016
Location: Stanford, CA
Type: Conference
Recent strides in quantum computing have raised the prospects that near term quantum devices can expediently solve computationally intractable problems in simulation, optimization and machine learning. The opportunities that quantum computing raises for machine learning is hard to understate. The goal of this workshop is, through a series of invited and contributed talks, survey the major results in this new area and facilitate increased dialog between researchers within this field.
Event details
Date: 8 December 2015
Location: NIPS 2015, Montreal
Type: Workshop
Computational Aspects of Biological Information (CABI) 2015 is the third one-day workshop on challenges and successes in computational biology and will bring together experts in the Boston/Cambridge area to discuss computational solutions to problems in biology, including systems biology, genomics, and related areas.
Event details
Date: 1 December 2015
Location: Cambridge, Mass.
Type: Workshop
Video details
Date: 5 November 2015
Duration: 00:03:15
Publisher: Microsoft
Yu Zheng, Huichu Zhang, and Yong Yu

The collective anomaly denotes a collection of nearby locations that are anomalous during a few consecutive time intervals in terms of phenomena collectively witnessed by multiple datasets. The collective anomalies suggest there are underlying problems that may not be identified based on a single data source or in a single location. It also associates individual locations and time intervals, formulating a panoramic view of an event. To detect a collective anomaly is very challenging, however, as...

Publication details
Date: 1 November 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Bimal Viswanath, Muhammad Ahmad Bashir, Muhammad Bilal Zafar, Simon Bouget, Saikat Guha, Krishna Gummadi, Aniket Kate, and Alan Mislove
Publication details
Date: 1 November 2015
Type: Inproceeding
Publication details
Date: 1 November 2015
Type: Technical report
Publisher: USENIX – Advanced Computing Systems Association
Number: MSR-TR-2015-59
Jointly organized by Harvard University, Massachusetts Institute of Technology, and Microsoft Research New England, the Charles River Lectures on Probability and Related Topics is a one-day event for the benefit of the greater Boston area mathematics community.
Event details
Date: 2 October 2015
Location: Cambridge, Mass.
Type: Conference
Alistair Moffat, Falk Scholer, Paul Thomas, and Peter Bailey

Evaluation of information retrieval systems with test collections makes use of a suite of fixed resources: a document corpus; a set of topics; and associated judgments of the relevance of each document to each topic. With large modern collections, exhaustive judging is not feasible. Therefore an approach called pooling is typically used where, for example, the documents to be judged can be determined by taking the union of all documents returned in the top positions of the answer lists returned...

Publication details
Date: 1 October 2015
Type: Article
Publisher: ACM – Association for Computing Machinery
Meredith Ringel Morris, Andrew Begel, and Ben Wiedermann

Technology workers are often stereotyped as being socially awkward or having difficulty communicating, often with humorous intent; however, for many technology workers with atypical cognitive profiles, such issues are no laughing matter. In this paper, we explore the hidden lives of neurodiverse technology workers, e.g., those with autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), and/or other learning disabilities, such as dyslexia. We present findings from interviews...

Publication details
Date: 1 October 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Zhongyuan Wang, Haixun Wang, Ji-Rong Wen, and Yanghua Xiao

Humans understand the world by classifying objects into an appropriate level of categories. This process is often automatic and subconscious. Psychologists and linguists call it as Basic-level Categorization (BLC). BLC can benefit lots of applications such as knowledge panel, advertising and recommendation. However, how to quantify basic-level concepts is still an open problem. Recently, much work focuses on constructing knowledge bases or semantic networks from web scale text corpora, which makes it...

Publication details
Date: 1 October 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
J. Burggraaff, J. Dorn, M. D'Souza, C. P. Kamm, P. Tewarie, P. Kontschieder, C. Morrison, A. Sellen, A. Criminisi, F. Dahlke, L. Kappos, and B. M. J. Uitdehaag
Publication details
Date: 1 October 2015
Type: Inproceeding
C. Morrison, K. Huckvale, A. Sakar, P. Kontschieder, J. Dorn, S. Steinheimer, C. P. Kamm, J. Burggraaff, M. D'Souza, F. Dahlke, L. Kappos, B. Uitdehaag, A. Criminisi, and A. Sellen
Publication details
Date: 1 October 2015
Type: Inproceeding
Jianpeng Cheng, Zhongyuan Wang, Ji-Rong Wen, Jun Yan, and Zheng Chen

Representing discrete words in a continuous vector space turns out to be useful for natural language applications related to text understanding. Meanwhile, it poses extensive challenges, one of which is due to the polysemous nature of human language. A common solution (a.k.a word sense induction) is to separate each word into multiple senses and create a representation for each sense respectively. However, this approach is usually computationally expensive and prone to data sparsity, since each sense...

Publication details
Date: 1 October 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
M. D'Souza, J. Burggraaff, P. Kontschieder, J. Dorn, C.P.Kamm, S. Seinheimer, P. Tewarie, C. Morrison, A. Sellen, A. Criminisi, F. Dahlke, B Uitdehaag, and L. Kappos
Publication details
Date: 1 October 2015
Type: Inproceeding
Bhaskar Mitra and Nick Craswell

Query auto-completion (QAC) systems typically suggest queries that have previously been observed in search logs. Given a partial user query, the system looks up this query prefix against a precomputed set of candidates, then orders them using ranking signals such as popularity. Such systems can only recommend queries for prefixes that have been previously seen by the search engine with adequate frequency. They fail to recommend if the prefix is sufficiently rare such that it has no matches in the...

Publication details
Date: 1 October 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Bhanu Vattikonda, Vacha Dave, Saikat Guha, and Alex C. Scoeren
Publication details
Date: 1 October 2015
Type: Inproceeding
Abdullah-Al Mamun, Iyswarya Narayanan, Di Wang, Anand Sivasubramaniam, and Hosam K. Fathy
Publication details
Date: 1 October 2015
Type: Article
Publisher: ASME
Dongwook Yoon, Nicholas Chen, François Guimbretière, and Abigail Sellen

This paper introduces a novel document annotation system that aims to enable the kinds of rich communication that usually only occur in face-to-face meetings. Our system, RichReview, lets users create annotations on top of digital documents using three main modalities: freeform inking, voice for narration, and deictic gestures in support of voice. RichReview uses novel visual representations and timesynchronization between modalities to simplify annotation access and navigation. Moreover, RichReview’s...

Publication details
Date: 1 October 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
H. Lombaert, A. Criminisi, and N. Ayache

This paper presents a new method for classifying surface data via spectral representations of shapes. Our approach benefits classification problems that involve data living on surfaces, such as in cortical parcellation. For instance, current methods for labeling cortical points into surface parcels often involve a slow mesh deformation toward pre-labeled atlases, requiring as much as 4 hours with the established FreeSurfer. This may burden neuroscience studies involving region-specific measurements....

Publication details
Date: 1 October 2015
Type: Inproceeding
Publisher: Springer
Yi Yang, Wen-tau Yih, and Christopher Meek

We describe the WikiQA dataset, a new publicly available set of question and sentence pairs, collected and annotated for research on open-domain question answering. Most previous work on answer sentence selection focuses on a dataset created using the TREC-QA data, which includes editor-generated questions and candidate answer sentences selected by matching content words in the question. WikiQA is constructed using a more natural process and is more than an order of magnitude larger than the previous...

Publication details
Date: 21 September 2015
Type: Inproceeding
Publisher: ACL – Association for Computational Linguistics
Kristina Toutanova, Danqi Chen, Patrick Pantel, Hoifung Poon, Pallavi Choudhury, and Michael Gamon

Models that learn to represent textual and knowledge base relations in the same continuous latent space are able to perform joint inferences among the two kinds of relations and obtain high accuracy on knowledge base completion (Riedel et al. 2013). In this paper we propose a model that captures the compositional structure of textual relations, and jointly optimizes entity, knowledge base, and textual relation representations. The proposed model significantly improves performance over a model that...

Publication details
Date: 17 September 2015
Type: Inproceeding
Publisher: ACL – Association for Computational Linguistics
Vasileios Lampos, Elad Yom-Tov, Richard Pebody, and Ingemar J. Cox

Assessing the effect of a health-oriented intervention by traditional epidemiological methods is commonly based only on population segments that use healthcare services. Here we introduce a complementary framework for evaluating the impact of a targeted intervention, such as a vaccination campaign against an infectious disease, through a statistical analysis of usergenerated content submitted on web platforms. Using supervised learning, we derive a nonlinear regression model for estimating the...

Publication details
Date: 7 September 2015
Type: Article
Publisher: Springer
Inside Microsoft Research Blog
Seny Kamara, a researcher in Microsoft's cryptography group, and his academic colleagues have figured out a way to obtain personal information from certain encrypted databases even when the databases are being protected by a promising security method.
News details
Date: 3 September 2015
Type: Headline
1–25 of 24096
Sort
Show 25 | 50 | 100
1234567Next 
> Our research