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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
Accurate indoor localization has the potential to transform the way people navigate indoors in a similar way that GPS transformed the way people navigate outdoors. Over the last 15 years, several human-centric approaches to indoor localization have been proposed by both academia and industry, but we have yet to see large scale deployments. This competition aims to bring together real-time or near real-time indoor location technologies and compare their performance.
Event details
Date: 11–13 April 2015
Location: Seattle, WA, USA
Type: Workshop
Wen Hua, Zhongyuan Wang, Haixun Wang, Kai Zheng, and Xiaofang Zhou

Understanding short texts is crucial to many applications, but challenges abound. First, short texts do not always observe the syntax of a written language. As a result, traditional natural language processing methods cannot be easily applied. Second, short texts usually do not contain suffi cient statistical signals to support many state-of-the-art approaches for text processing such as topic modeling. Third, short texts are usually more ambiguous. We argue that knowledge is needed in order to better...

Publication details
Date: 1 April 2015
Type: Inproceeding
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
Moshe Babaioff, Moran Feldman, and Moshe Tennenholtz

We consider the problem of designing mechanisms that interact with strategic agents through strategic intermediaries (or mediators), and investigate the cost to society due to the mediators' strategic behavior. Selfish agents with private information are each associated with exactly one strategic mediator, and can interact with the mechanism exclusively through that mediator. Each mediator aims to optimize the combined utility of his agents, while the mechanism aims to optimize the combined utility of...

Publication details
Date: 11 January 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
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
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
Silvia Caldararu, Drew W. Purves, and Matthew J. Smith

Simple mechanistic models of vegetation processes are essential both to our understanding of plant behaviour and to our ability to predict future changes in vegetation. One concept that can take us closer to such models is that of plant optimality, the hypothesis that plants aim to achieve an optimal state. Conceptually, plant optimality can be either structural or functional optimality. A structural constraint would mean that plants aim to achieve a certain structural characteristic such as an...

Publication details
Date: 15 December 2014
Type: Proceedings
Oleksandra Hararuk and Matthew J. Smith

Soil is the largest terrestrial pool of carbon (C), storing 1395-2293 Pg C. Under changing climate a large portion of soil C could potentially transfer back to the atmosphere as CO₂, pushing the earth system into a positive feedback loop between increasing soil CO₂ emissions and rising temperatures. We rely on models to estimate soil responses to climate change; however recent global carbon cycle model intercomparisons have shown poor model performance in capturing C cycle processes in the soil. To gain...

Publication details
Date: 15 December 2014
Type: Proceedings
Katherine E Todd-Brown, Yiqi Luo, James Tremper Randerson, Stephen D. Allison, and Matthew J. Smith

Soil carbon stocks have the potential to be a strong source or sink for carbon dioxide over the next century, playing a critical role in climate change. These stocks are the result of small differences between much larger primary carbon fluxes: gross primary production, litter fall, autotrophic respiration and heterotrophic respiration. There was little agreement on predicted soil carbon stocks between Earth system models (ESMs) in the most recent Climate Model Intercomparison Project. Predicted...

Publication details
Date: 15 December 2014
Type: Proceedings
Matthew J. Smith, Stephen Emmott, Drew W. Purves, Lucas N. Joppa, and Vassily Lyutsarev

In scientific research and development, emphasis is placed on research over development. A significant cost is that the two-way interaction between scientific insights and societal needs does not function effectively to lead to impacts in the wider world. We simply must embrace new software and hardware approaches if we are to provide timely predictive information to address global problems, support businesses and inform governments and citizens. The Microsoft Research Computational Science Lab has been...

Publication details
Date: 15 December 2014
Type: Proceedings
Menghui Lim, Jian-Guang LOU, Hongyu Zhang, Qiang FU, Andrew Teoh, Qingwei LIN, Rui Ding, and Dongmei Zhang

For a large-scale software system, especially an online service system, when a performance issue occurs, it is desirable to check whether this issue has occurred before. If there are past similar issues, a known remedy could be applied. Otherwise, a new troubleshooting process may have to be initiated. The symptom of a performance issue can be characterized by a set of metrics. Due to the sophisticated nature of software systems, manual diagnosis of performance issues based on metric data is typically...

Publication details
Date: 14 December 2014
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Qi Li, Gokhan Tur, Dilek Hakkani-Tur, Xiang Li, Tim Paek, Asela Gunawardana, and Chris Quirk

Traditional spoken dialog systems are usually based on centralized architecture, in which the number of domains is predefined, and the provider is fixed for a given domain and intent. The spoken language understanding (SLU) component is responsible for detecting domain and intents, and filling domain-specific slots. It is expensive and time-consuming for this architecture to add new and/or competing domains, intents, or providers. The rapid growth of service providers in mobile computing market calls...

Publication details
Date: 1 December 2014
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Publication details
Date: 1 December 2014
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Kai Hong, Ye-Yi Wang, Dilek Hakkani-Tur, and Pengjun Pei
Publication details
Date: 1 December 2014
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Publication details
Date: 1 December 2014
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Fang Wang, Zhongyuan Wang, Senzhang Wang, and Zhoujun Li

Keyphrase extraction is essential for many IR and NLP tasks. Existing methods usually use the phrases of the document separately without distinguishing the potential semantic correlations among them, or other statistical features from knowledge bases such as WordNet and Wikipedia. However, the mutual semantic information between phrases is also important, and exploiting their correlations may potentially help us more effectively extract the keyphrases. Generally, phrases in the title are more likely to...

Publication details
Date: 1 December 2014
Type: Inproceeding
Sree Harsha Yella, Andreas Stolcke, and Malcolm Slaney

Speaker diarization finds contiguous speaker segments in an audio recording and clusters them by speaker identity, without any a-priori knowledge. Diarization is typically based on short-term spectral features such as Mel-frequency cepstral coefficients (MFCCs). Though these features carry average information about the vocal tract characteristics of a speaker, they are also susceptible to factors unrelated to the speaker identity. In this study, we propose an artificial neural netw ork (ANN)...

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
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
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