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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
Youshan Miao, Wentao Han, Kaiwei Li, Ming Wu, Fan Yang, Lidong Zhou, Vijayan Prabhakaran, Enhong Chen, and Wenguang Chen

Temporal graphs that capture graph changes over time are attracting increasing interest from research communities, for functions such as understanding temporal characteristics of social interactions on a time-evolving social graph. ImmortalGraph is a storage and execution engine designed and optimized specifically for temporal graphs. Locality is at the center of ImmortalGraph’s design: temporal graphs are carefully laid out in both persistent storage and memory, taking into account data locality in...

Publication details
Date: 1 December 2015
Type: Article
Publisher: ACM – Association for Computing Machinery
Video details
Date: 5 November 2015
Duration: 00:03:15
Publisher: Microsoft
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
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
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
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
Abdullah-Al Mamun, Iyswarya Narayanan, Di Wang, Anand Sivasubramaniam, and Hosam K. Fathy
Publication details
Date: 1 October 2015
Type: Article
Publisher: ASME
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
Bhanu Vattikonda, Vacha Dave, Saikat Guha, and Alex C. Scoeren
Publication details
Date: 1 October 2015
Type: Inproceeding
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
Schedule for the weekly Station Q seminars.
Event details
Date: 1 September–31 December 2015
Location: Station Q
Type: Other
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
Dilek Hakkani-Tur, Yun-Cheng Ju, Geoffrey Zweig, and Gokhan Tur

Spoken language understanding (SLU) in today’s conversational systems focuses on recognizing a set of domains, intents, and associated arguments, that are determined by application developers. User requests that are not covered by these are usually directed to search engines, and may remain unhandled. We propose a method that aims to find common user intents amongst these uncovered, out-of-domain utterances, with the goal of supporting future phases of dialog system design. Our approach relies on...

Publication details
Date: 1 September 2015
Type: Inproceeding
Publisher: Interspeech 2015 Conference
Yoli Shavit, Boyan Yordanov, Sara-Jane Dunn, Christoph M. Wintersteiger, Youssef Hamadi, and Hillel Kugler

A fundamental question in biology is how cells change into specific cell types with unique roles throughout development. This process can be viewed as a program prescribing the system dynamics, governed by a network of genetic interactions. Recent experimental evidence suggests that these networks are not fixed but rather change their topology as cells develop. Currently, there are limited tools for the construction and analysis of such self-modifying biological programs. We introduce Switching Gene...

Publication details
Date: 1 September 2015
Type: Inproceeding
Publisher: Springer
TJ Tsai and Andreas Stolcke

This paper proposes a robust and efficient way to temporally align a set of unsynchronized meeting recordings, such as might be collected by participants’ cell phones. We propose an adaptive audio fingerprint which is learned on-the-fly in a completely unsupervised manner to adapt to the characteristics of a given set of unaligned recordings. The design of the adaptive audio fingerprint is formulated as a series of optimization problems which can be solved very efficiently using eigenvector routines. We...

Publication details
Date: 1 September 2015
Type: Inproceeding
Publisher: ISCA - International Speech Communication Association
Liwen Xu, Xiaohong Hao, Nicholas D. Lane, Xin Liu, and Thomas Moscibroda

Mobile crowdsourcing is a powerful tool for collecting data of various types. The primary bottleneck in such systems is the high burden placed on the user who must manually collect sensor data or respond in-situ to simple queries (e.g., experience sampling studies). In this work, we present Compressive CrowdSensing (CCS) – a framework that enables compressive sensing techniques to be applied to mobile crowdsourcing scenarios. CCS enables each user to provide significantly reduced amounts of manually...

Publication details
Date: 1 September 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Rui Ding, Qiang Wang, Yingnong Dang, Qiang Fu, Haidong Zhang, and Dongmei Zhang

Fast and scalable analysis techniques are becoming increasingly important in the era of big data, because they are the enabling techniques to create real-time and interactive experiences in data analysis. Time series are widely available in diverse application areas. Due to the large number of time series instances (e.g., millions) and the high dimensionality of each time series instance (e.g., thousands), it is challenging to conduct clustering on largescale time series, and it is even more challenging...

Publication details
Date: 1 September 2015
Type: Proceedings
Publisher: VLDB – Very Large Data Bases
Publication details
Date: 1 September 2015
Type: Inproceeding
Publisher: Springer
Suman Ravuri and Andreas Stolcke

Utterance classification is a critical pre-processing step for many speech understanding and dialog systems. In multi-user settings, one needs to first identify if an utterance is even directed at the system, followed by another level of classification to determine the intent of the user’s input. In this work, we propose RNN and LSTM models for both these tasks. We show how both models outperform baselines based on ngram-based language models (LMs), feedforward neural network LMs, and boosting...

Publication details
Date: 1 September 2015
Type: Inproceeding
Publisher: ISCA - International Speech Communication Association
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