Our research
Content type
+
Downloads (438)
+
Events (396)
 
Groups (150)
+
News (2571)
 
People (820)
 
Projects (1053)
+
Publications (11932)
+
Videos (5174)
Labs
Research areas
Algorithms and theory47205 (733)
Communication and collaboration47188 (1355)
Computational linguistics47189 (432)
Computational sciences47190 (738)
Computer systems and networking47191 (1996)
Computer vision208594 (105)
Data mining and data management208595 (145)
Economics and computation47192 (293)
Education47193 (762)
Gaming47194 (353)
Graphics and multimedia47195 (1119)
Hardware and devices47196 (975)
Health and well-being47197 (428)
Human-computer interaction47198 (2101)
Machine learning and intelligence47200 (1598)
Mobile computing208596 (71)
Quantum computing208597 (26)
Search, information retrieval, and knowledge management47199 (1681)
Security and privacy47202 (745)
Social media208598 (61)
Social sciences47203 (795)
Software development, programming principles, tools, and languages47204 (1425)
Speech recognition, synthesis, and dialog systems208599 (81)
Technology for emerging markets208600 (31)
1–25 of 22534
Sort
Show 25 | 50 | 100
1234567Next 
Nicholas Jing Yuan, Yu Zheng, Xing Xie, Yingzi Wang, Kai Zheng, and Hui Xiong

The step of urbanization and modern civilization fosters different functional zones in a city, such as residential areas, business districts, and educational areas. In a metropolis, people commute between these functional zones every day to engage in different socioeconomic activities, e.g., working, shopping, and entertaining. In this paper, we propose a data-driven framework to discover functional zones in a city. Specifically, we introduce the concept of Latent Activity Trajectory (LAT), which...

Publication details
Date: 1 August 2016
Type: Article
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Emerson Murphy-Hill, Thomas Zimmermann, Christian Bird, and Nachiappan Nagappan

When software engineers fix bugs, they may have several options as to how to fix those bugs. Which fix they choose has many implications, both for practitioners and researchers: What is the risk of introducing other bugs during the fix? Is the bug fix in the same code that caused the bug? Is the change fixing the cause or just covering a symptom? In this paper, we investigate alternative fixes to bugs and present an empirical study of how engineers make design choices about how to fix bugs. We start...

Publication details
Date: 1 December 2015
Type: Article
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Abram Hindle, Christian Bird, Thomas Zimmermann, and Nachiappan Nagappan

Large organizations like Microsoft tend to rely on formal requirements documentation in order to specify and design the software products that they develop. These documents are meant to be tightly coupled with the actual implementation of the features they describe. In this paper we evaluate the value of high-level topic-based requirements traceability and issue report traceability in the version control system, using Latent Dirichlet Allocation (LDA). We evaluate LDA topics on practitioners...

Publication details
Date: 1 December 2015
Type: Article
Publisher: Springer
Mohan Yang, bolin ding, surajit chaudhuri, and kaushik chakrabarti

We aim to provide table answers to keyword queries using a knowledge base. For queries referring to multiple entities, like “Washington cities population” and “Mel Gibson movies”, it is better to represent each relevant answer as a table which aggregates a set of entities or joins of entities within the same table scheme or pattern. In this paper, we study how to find highly relevant patterns in a knowledge base for user-given keyword queries to compose table answers. A knowledge base is...

Publication details
Date: 1 August 2015
Type: Inproceeding
Publisher: VLDB – Very Large Data Bases
Fuzheng Zhang, Nicholas Jing Yuan, David Wilkie, Yu Zheng, and Xing Xie

Urban transportation is an important factor in energy consumption and pollution, and is of increasing concern due to its complexity and economic significance. Its importance will only increase as urbanization continues around the world. In this paper, we explore drivers’ refueling behavior in urban areas. Compared to questionnaire-based methods of the past, we propose a complete data-driven system that pushes towards real-time sensing of individual refueling behavior and citywide petrol consumption. Our...

Publication details
Date: 1 June 2015
Type: Article
Publisher: ACM – Association for Computing Machinery
Kathryn Zyskowski, Meredith Ringel Morris, Jeffrey P. Bigham, Mary L. Gray, and Shaun Kane

We present the first formal study of crowdworkers who have disabilities via in-depth open-ended interviews of 17 people (disabled crowdworkers and job coaches for people with disabilities) and a survey of 631 adults with disabilities. Our findings establish that people with a variety of disabilities currently participate in the crowd labor marketplace, despite challenges such as crowdsourcing workflow designs that inadvertently prohibit participation by, and may negatively affect the worker reputations...

Publication details
Date: 1 March 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
VMCAI provides a forum for researchers from the communities of Verification, Model Checking, and Abstract Interpretation, facilitating interaction, cross-fertilization, and advancement of hybrid methods that combine these and related areas.
Event details
Date: 11–13 January 2015
Location: Mumbai, India
Type: Conference
Shuo Ma, Yu Zheng, and Ouri Wolfson

We proposed and developed a taxi-sharing system that accepts taxi passengers’ real-time ride requests sent from smartphones and schedules proper taxis to pick up them via ridesharing, subject to time, capacity, and monetary constraints. The monetary constraints provide incentives for both passengers and taxi drivers: passengers will not pay more compared with no ridesharing and get compensated if their travel time is lengthened due to ridesharing; taxi drivers will make money for all the detour distance...

Publication details
Date: 1 January 2015
Type: Article
Publisher: IEEE
Shipra Agrawal and Nikhil R. Devanur

We introduce the online stochastic Convex Programming (CP) problem, a very general version of stochastic online problems which allows arbitrary concave objectives and convex feasibility constraints. Many well-studied problems like online stochastic packing and covering, online stochastic matching with concave returns, etc. form a special case of online stochastic CP. We present fast algorithms for these problems, which achieve near-optimal regret guarantees for both the i.i.d. and the...

Publication details
Date: 1 January 2015
Type: Inproceeding
Publisher: SIAM – Society for Industrial and Applied Mathematics
Purushottam Kar, Harikrishna Narasimhan, and Prateek Jain

Modern applications in sensitive domains such as biometrics and medicine frequently require the use of non-decomposable loss functions such as precision@k, F-measure etc. Compared to point loss functions such as hinge-loss, these offer much more fine grained control over prediction, but at the same time present novel challenges in terms of algorithm design and analysis. In this work we initiate a study of online learning techniques for such non-decomposable loss functions with an aim to enable...

Publication details
Date: 1 December 2014
Type: Inproceeding
Publisher: Neural Information Processing Systems
Publication details
Date: 1 December 2014
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Kaisheng Yao, Baolin Peng, Yu Zhang, Dong Yu, Geoffrey Zweig, and Yangyang Shi

Neural network based approaches have recently produced record-setting performances in natural language understanding tasks such as word labeling. In the word labeling task, a tagger is used to assign a label to each word in an input sequence. Specifically, simple recurrent neural networks (RNNs) and convolutional neural networks (CNNs) have shown to significantly outperform the previous state-of-theart – conditional random fields (CRFs). This paper investigates using long short-term memory (LSTM) neural...

Publication details
Date: 1 December 2014
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Prateek Jain, Ambuj Tewari, and Purushottam Kar

The use of M-estimators in generalized linear regression models in high dimensional settings requires risk minimization with hard L0 constraints. Of the known methods, the class of projected gradient descent (also known as iterative hard thresholding (IHT)) methods is known to offer the fastest and most scalable solutions. However, the current state-of-the-art is only able to analyze these methods in very restrictive settings which do not hold in high dimensional statistical models. In this...

Publication details
Date: 1 December 2014
Type: Inproceeding
Publisher: Neural Information Processing Systems
Larry Heck and Hongzhao Huang

This paper presents an unsupervised neural knowledge graph embedding model and a coherence-based approach for semantic parsing of Twitter dialogs. The approach learns embeddings directly from knowledge graphs and scales to all of Wikipedia. Experiments show a 23.6% reduction in semanticparsing errors compared to the previously best reported results.

Publication details
Date: 1 December 2014
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
This training is offered to select research community audiences, predominantly consisting of practicing research scientists with at least basic software development skills. This one-day course will help attendees acquire a general understanding of cloud computing with Microsoft Azure at scale.
Event details
Date: 12 November 2014
Location: Tel Aviv University | Tel Aviv, Israel
Type: Other
This training is offered to select research community audiences, predominantly consisting of practicing research scientists with at least basic software development skills. This one-day course will help attendees acquire a general understanding of cloud computing with Microsoft Azure at scale.
Event details
Date: 11 November 2014
Location: Ben-Gurion University | Beer-Sheva, Israel
Type: Other
This training is offered to select research community audiences, predominantly consisting of practicing research scientists with at least basic software development skills. This one-day course will help attendees acquire a general understanding of cloud computing with Microsoft Azure at scale.
Event details
Date: 10 November 2014
Location: The Technion – Israel Institute of Technology | Haifa, Israel
Type: Other
Neha Gupta, David Martin, Ben Hanrahan, and Jacki O'Neill

Previous studies on Amazon Mechanical Turk (AMT), the most well-known marketplace for microtasks, show that the largest population of workers on AMT is U.S. based, while the second largest is based in India. In this paper, we present insights from an ethnographic study conducted in India to introduce some of these workers or ‘Turkers’ – who they are, how they work and what turking means to them. We examine the work they do to maintain their reputations and their work-life balance. In doing this, we...

Publication details
Date: 9 November 2014
Type: Inproceeding
Publisher: ACM Conference on Supporting Groupwork
Rakesh Agrawal, Sreenivas Gollapudi, Anitha Kannan, and Krishnaram Kenthapadi

The rapid proliferation of hand-held devices has led to the development of rich, interactive and immersive applications, such as e-readers for electronic books. These applications motivate retrieval systems that can implicitly satisfy any information need of the reader by exploiting the context of the user’s interactions. Such retrieval systems differ from traditional search engines in that the queries constructed using the context are typically complex objects (including the document and its...

Publication details
Date: 4 November 2014
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Sreenivas Gollapudi and Debmalya Panigrahi

where A key characteristic of a successful online market is the large specific participation of agents (producers and consumers) on both definition sides of the market. While there has been a long line of tion problems, impressive work on understanding such markets in terms of main revenue maximizing (also called max-sum) objectives, par- • ticularly in the context of allocating online impressions to interested advertisers, fairness considerations have surprisingly not received much attention in online...

Publication details
Date: 4 November 2014
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Benjamin Livshits and Todd Mytkowicz

Crowd-sourcing is increasingly being used for largescale polling and surveys. Companies such as SurveyMonkey and Instant.ly make crowd-sourced surveys commonplace by making the crowd accessible through an easy-to-use UI with easy to retrieve results. Further, they do so with a relatively low latency by having dedicated crowds at their disposal. In this paper we argue that the ease with which polls can be created conceals an inherent difficulty: the survey maker does not know how many workers to hire for...

Publication details
Date: 2 November 2014
Type: Inproceeding
Publisher: AAAI - Association for the Advancement of Artificial Intelligence
Publication details
Date: 1 November 2014
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Yelong Shen, Xiaodong He, Jianfeng Gao, Li Deng, and Gregoire Mesnil

In this paper, we propose a new latent semantic model that incorporates a convolutional-pooling structure over word sequences to learn low-dimensional, semantic vector representations for search queries and Web documents. In order to capture the rich contextual structures in a query or a document, we start with each word within a temporal context window in a word sequence to directly capture contextual features at the word n-gram level. Next, the salient word n-gram features in the word sequence are...

Publication details
Date: 1 November 2014
Type: Inproceeding
Publisher: CIKM
André N. Meyer, Thomas Fritz, Gail C. Murphy, and Thomas Zimmermann

The better the software development community becomes at creating software, the more software the world seems to demand. Although there is a large body of research about measuring and investigating productivity from an organizational point of view, there is a paucity of research about how software developers, those at the front-line of software construction, think about, assess and try to improve their productivity. To investigate software developers' perceptions of software development productivity, we...

Publication details
Date: 1 November 2014
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Emine Yilmaz, Manisha Verma, Nick Craswell, Filip Radlinski, and Peter Bailey

Relevance judgments sit at the core of test collection construction, and are assumed to model the utility of documents to real users. However, comparisons of judgments with signals of relevance obtained from real users, such as click counts and dwell time, have demonstrated a systematic mismatch.

In this paper, we study one important source of the mismatch between user data and relevance judgments: Those due to the high degree of effort required by users to identify and consume the information in...

Publication details
Date: 1 November 2014
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
1–25 of 22534
Sort
Show 25 | 50 | 100
1234567Next 
> Our research