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Yanjie Fu, Yong Ge, Yu Zheng, Yao, Yanchi Liu, Hui Xiong, and Nicholas Jing Yuan

Ranking residential real estates based on investment values can provide decision making support for home buyers and thus plays an important role in estate marketplace. In this paper, we aim to develop methods for ranking estates based on investment values by mining users opinions about estates from online user reviews and offline moving behaviors (e.g., taxi traces, smart card transactions, check-ins). While a variety of features could be extracted from these data, these features are intercorrelated and...

Publication details
Date: 1 December 2015
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Publication details
Date: 1 December 2015
Type: Article
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
Yu Zheng

The advances in location-acquisition and mobile computing techniques have generated massive spatial trajectory data, which represent the mobility of a diversity of moving objects, such as people, vehicles and animals. Many techniques have been proposed for processing, managing and mining trajectory data in the past decade, fostering a broad range of applications. In this article, we conduct a systematic survey on the major research into trajectory data mining, providing a panorama of the field...

Publication details
Date: 1 September 2015
Type: Article
Publisher: ACM – Association for Computing Machinery
Kalin Ovtcharov, Olatunji Ruwase, Joo-Young Kim, Jeremy Fowers, Karin Strauss, and Eric Chung
Publication details
Date: 1 August 2015
Type: Proceedings
Publisher: HOTCHIPS
Gerard Pons-Moll, Jonathan Taylor, Jamie Shotton, Aaron Hertzmann, and Andrew Fitzgibbon

We present a new method for inferring dense data to model correspondences, focusing on the application of human pose estimation from depth images. Recent work proposed the use of regression forests to quickly predict correspondences between depth pixels and points on a 3D human mesh model. That work, however, used a proxy forest training objective based on the classification of depth pixels to body parts. In contrast, we introduce Metric Space Information Gain (MSIG), a new decision forest training...

Publication details
Date: 1 August 2015
Type: Article
Publisher: Springer
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
Publication details
Date: 1 August 2015
Type: Proceedings
Publisher: ACL – Association for Computational Linguistics
Bhaskar Mitra

Search logs contain examples of frequently occurring patterns of user reformulations of queries. Intuitively, the reformulation "san francisco" → "san francisco 49ers" is semantically similar to "detroit" →"detroit lions". Likewise, "london"→"things to do in london" and "new york"→"new york tourist attractions" can also be considered similar transitions in intent. The reformulation "movies" → "new movies" and "york" → "new york", however, are clearly different despite the lexical similarities in the two...

Publication details
Date: 1 August 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Publication details
Date: 1 August 2015
Type: Inproceeding
Publisher: SIGKDD
J. Valentin, V. Vineet, M.-M. Cheng, D. Kim, J. Shotton, P. Kohli, M. Niessner, A. Criminisi, S. Izadi, and P. Torr
Publication details
Date: 1 August 2015
Type: Article
Publisher: ACM – Association for Computing Machinery
Publication details
Date: 1 July 2015
Type: Inproceeding
Publisher: ACL – Association for Computational Linguistics
Mohammad Raza, Sumit Gulwani, and Natasa Milic-Frayling
Publication details
Date: 1 July 2015
Type: Inproceeding
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
Julien Valentin, Matthias Nießner, Jamie Shotton, Andrew Fitzgibbon, Shahram Izadi, and Philip Torr

Recent advances in camera relocalization use predictions from a regression forest to guide the camera pose optimization procedure. In these methods, each tree associates one pixel with a point in the scene’s 3D world coordinate frame. In previous work, these predictions were point estimates and the subsequent camera pose optimization implicitly assumed an isotropic distribution of these estimates. In this paper, we train a regression forest to predict mixtures of anisotropic 3D Gaussians and show...

Publication details
Date: 1 June 2015
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Aditya V. Nori, Sherjil Ozair, Sriram K. Rajamani, and Deepak Vijaykeerthy

We show how to automatically synthesize probabilistic programs from real-world datasets. Such a synthesis is feasible due to a combination of two techniques: (1) We borrow the idea of “sketching” from synthesis of deterministic programs, and allow the programmer to write a skeleton program with “holes”. Sketches enable the programmer to communicate domain-specific intuition about the structure of the desired program and prune the search space, and (2) we design an efficient Markov Chain Monte Carlo...

Publication details
Date: 1 June 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Sameh Khamis, Jonathan Taylor, Jamie Shotton, Cem Keskin, Shahram Izadi, and Andrew Fitzgibbon

We describe how to learn a compact and efficient model of the surface deformation of human hands. The model is built from a set of noisy depth images of a diverse set of subjects performing different poses with their hands. We represent the observed surface using Loop subdivision of a control mesh that is deformed by our learned parametric shape and pose model. The model simultaneously accounts for variation in subject-specific shape and subject-agnostic pose. Specifically, hand shape is...

Publication details
Date: 1 June 2015
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Hao Fang, Saurabh Gupta, Forrest Iandola, Rupesh Srivastava, Li Deng, Piotr Dollar, Jianfeng Gao, Xiaodong He, Margaret Mitchell, John Platt, Lawrence Zitnick, and Geoffrey Zweig

This paper presents a novel approach for automatically generating image descriptions: visual detectors, language models, and multimodal similarity models learnt directly from a dataset of image captions. We use multiple instance learning to train visual detectors for words that commonly occur in captions, including many different parts of speech such as nouns, verbs, and adjectives. The word detector outputs serve as conditional inputs to a maximum-entropy language model. The language model learns from...

Publication details
Date: 1 June 2015
Type: Article
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Alessandro Sordoni, Michel Galley, Michael Auli, Chris Brockett, Yangfeng Ji, Meg Mitchell, Jian-Yun Nie, Jianfeng Gao, and Bill Dolan
Publication details
Date: 1 June 2015
Type: Inproceeding
Publisher: Conference of the North American Chapter of the Association for Computational Linguistics – Human Language Technologies (NAACL-HLT 2015)
Young-Bum Kim, Minwoo Jeong, Karl Stratos, and Ruhi Sarikaya

In this paper, we apply a weakly-supervised learning approach for slot tagging using conditional random fields by exploiting web search click logs. We extend the constrained lattice training of Tackstrom et al. (2013) to ¨ non-linear conditional random fields in which latent variables mediate between observations and labels. When combined with a novel initialization scheme that leverages unlabeled data, we show that our method gives significant improvement over strong supervised and weakly-supervised...

Publication details
Date: 1 June 2015
Type: Inproceeding
Publisher: ACL – Association for Computational Linguistics
Jialu Liu, Jingbo Shang, Chi Wang, Xiang Ren, and Jiawei Han

Text data are ubiquitous and play an essential role in big data applications. However, text data are mostly unstructured. Transforming unstructured text into structured units (e.g., semantically meaningful phrases) will substantially reduce semantic ambiguity and enhance the power and efficiency at manipulating such data using database technology. Thus mining quality phrases is a critical research problem in the field of databases. In this paper, we propose a new framework that extracts quality...

Publication details
Date: 1 June 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Hyon Lim and Sudipta N. Sinha

In this paper, we propose a novel method to recover the 3D trajectory of a moving person from a monocular camera mounted on a quadrotor micro aerial vehicle (MAV). The key contribution is an integrated approach that simultaneously performs visual odometry (VO) and persistent tracking of a person automatically detected in the scene. All computation pertaining to VO, detection and tracking runs onboard the MAV from a front-facing monocular RGB camera. Given the gravity direction from an inertial sensor...

Publication details
Date: 27 May 2015
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Yiwei Chen and Katja Hofmann

Online learning to rank holds great promise for learning personalized search result rankings. First algorithms have been proposed, namely absolute feedback approaches, based on contextual bandits learning; and relative feedback approaches, based on gradient methods and inferred preferences between complete result rankings. Both types of approaches have shown promise, but they have not previously been compared to each other. It is therefore unclear which type of...

Publication details
Date: 20 May 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Kuansan Wang

Human is the only species on earth that has mastered the technologies in writing and printing to capture ephemeral thoughts and scientific discoveries. The capabilities to pass along knowledge, not only geographically but also generationally, have formed the bedrock of our civilizations. We are in the midst of a silent revolution driven by the technological advancements: no longer are computers just a fixture of our physical world but have they been so deeply woven into our daily routines that they are...

Publication details
Date: 18 May 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Huan Sun, Hao Ma, Wen-tau Yih, Chen-Tse Tsai, Jingjing Liu, and Ming-Wei Chang

Most recent question answering (QA) systems query large-scale knowledge bases (KBs) to answer a question, after parsing and transforming natural language questions to KBs-executable forms (e.g., logical forms). As a well-known fact, KBs are far from complete, so that information required to answer questions may not always exist in KBs. In this paper, we develop a new QA system that mines answers directly from the Web, and meanwhile employs KBs as a significant auxiliary to further boost the QA...

Publication details
Date: 1 May 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
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