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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
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
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
Kai Hong, Pengjun Pei, Ye-Yi Wang, and Dilek Hakkani-Tur

We investigate the problem of entity ranking towards descriptive queries, that aims to match entities referred in user queries to entities of a large knowledge base (KB). Entity ranking faces the primary challenge of the sparseness of entity related data, such as various ways of referring to an entity. The lack of sufficient variations of entity referring expressions in KB makes it difficult to find entities referred in user queries, especially when the queries are descriptive. We tackle this problem by...

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
Matthew Henderson, Blaise Thomson, and Jason D. Williams

In spoken dialog systems, dialog state tracking refers to the task of correctly inferring the user’s goal at a given turn, given all of the dialog history up to that turn. This task is challenging because of speech recognition and language understanding errors, yet good dialog state tracking is crucial to the performance of spoken dialog systems. This paper presents results from the third Dialog State Tracking Challenge, a research community challenge task based on a corpus of annotated logs of...

Publication details
Date: 1 December 2014
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Tom Crick, Benjamin A. Hall, Samin Ishtiaq, and Kenji Takeda

The reproduction and replication of reported scientific results is a hot topic within the academic community. The retraction of numerous studies from a wide range of disciplines, from climate science to bioscience, has drawn the focus of many commentators, but there exists a wider socio-cultural problem that pervades the scientific community. Sharing data and models often requires extra effort, and this is currently seen as a significant overhead that may not be worth the time investment....

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
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
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
Publication details
Date: 1 December 2014
Type: Inproceeding
Publisher: ISCA - International Speech Communication Association
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
Publication details
Date: 1 December 2014
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
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