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Ji He, Jianshu Chen, Xiaodong He, Jianfeng Gao, Lihong Li, Li Deng, and Mari Ostendorf
Publication details
Date: 1 August 2016
Type: Inproceeding
Publisher: ACL – Association for Computational Linguistics
Wen-tau Yih, Matthew Richardson, Christopher Meek, Ming-Wei Chang, and Jina Suh
Publication details
Date: 1 August 2016
Type: Inproceeding
Publisher: ACL – Association for Computational Linguistics
Konstantina Christakopoulou, Filip Radlinski, and Katja Hofmann

People often ask others for restaurant recommendations as a way to discover new dining experiences. This makes restaurant recommendation an exciting scenario for recommender systems and has led to substantial research in this area. However, most such systems behave very differently from a human when asked for a recommendation. The goal of this paper is to begin to reduce this gap.

In particular, humans can quickly establish preferences when asked to make a recommendation for someone they do not...

Publication details
Date: 1 August 2016
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Xiuwen Yi, Yu Zheng, Junbo Zhang, and Tianrui Li

Many sensors have been deployed in the physical world, generating massive geo-tagged time series data. In reality, we usually lose readings of sensors at some unexpected moments because of sensor or communication errors. Those missing rea­dings do not only affect real-time monitoring but also com­promise the performance of further data analysis. In this paper, we propose a spatio-temporal multi-view-based learning (ST-MVL) method to collec­tively fill missing readings in a collection of...

Publication details
Date: 1 July 2016
Type: Inproceeding
Publisher: AAAI - Association for the Advancement of Artificial Intelligence
Yang Song, Ali Elkahky, and Xiaodong He

Modeling temporal behavior in recommendation systems is an important and challenging problem. Its challenges come from the fact that temporal modeling increases the cost of parameter estimation and inference, while requires large amount of data to reliably learn the model with additional time dimensions. Therefore, it is hard to model temporal behavior in large scale real-world recommendation applications.

In this work, we propose a new deep neural network based architecture that models the...

Publication details
Date: 1 July 2016
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Matthew Johnson, Katja Hofmann, Tim Hutton, and David Bignell

We present Project Malmo – an AI experimentation platform built on top of the popular computer game Minecraft, and designed to support fundamental research in artificial intelligence. As the AI research community pushes for artificial general intelligence (AGI), experimentation platforms are needed that support the development of flexible agents that learn to solve diverse tasks in complex environments. Minecraft is an ideal foundation for such a platform, as it exposes agents to complex 3D worlds,...

Publication details
Date: 1 July 2016
Type: Inproceeding
Publisher: AAAI - Association for the Advancement of Artificial Intelligence
Ye Liu, Yu Zheng, Yuxuan Liang, Shuming Liu, and David S. Rosenblum

Urban water quality is of great importance to our daily lives. Prediction of urban water quality help
control water pollution and protect human health. In this work, we forecast the water quality of a
station over the next few hours, using a multitask multi-view learning method to fuse multiple
datasets from different domains. In particular, our learning model comprises two alignments. The
first alignment is the spaio-temporal view alignment, which combines local spatial and...

Publication details
Date: 1 July 2016
Type: Inproceeding
Publisher: AAAI - Association for the Advancement of Artificial Intelligence
Publication details
Date: 1 July 2016
Type: Inproceeding
Mingsong Dou, Sameh Khamis, Yury Degtyarev, Philip Davidson, Sean Fanello, Adarsh Kowdle, Sergio Orts Escolano, Christoph Rhemann, David Kim, Jonathan Taylor, Pushmeet Kohli, Vladimir Tankovich, and Shahram Izadi
Publication details
Date: 1 July 2016
Type: Inproceeding
Publisher: SIGGRAPH
Masrour Zoghi, Tomáš Tunys, Lihong Li, Damien Jose, Junyan Chen, Chun Ming Chin, and Maarten de Rijke
Publication details
Date: 1 July 2016
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Anshumali Srivastava, Arnd Christian König, and Misha Bilenko

Obtaining frequency information of data streams, in limited space, is a well-recognized problem in literature. A number of recent practical applications (such as those in computational advertising) require temporally-aware solutions: obtaining historical count statistics for both time-points as well as time-ranges. In these scenarios, accuracy of estimates is typically more important for recent instances than for older ones; we call this desirable property as ``Time Adaptiveness". With this...

Publication details
Date: 26 June 2016
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Jun Xu, Tao Mei, Ting Yao, and Yong Rui

While there has been increasing interest in the task of describing video with natural language, current computer vision algorithms are still severely limited in terms of the variability and complexity of the videos and their associated language that they can recognize. This is in part due to the simplicity of current benchmarks, which mostly focus on specific fine-grained domains with limited videos and simple descriptions. While researchers have provided several benchmark datasets for image...

Publication details
Date: 1 June 2016
Type: Inproceeding
Publisher: IEEE International Conference on Computer Vision and Pattern Recognition (CVPR)
Sean Fanello, Christoph Rhemann, Vladimir Tankovich, Adarsh Kowdle, Sergio Orts Escolano, David Kim, and Shahram Izadi

Structured light sensors are popular due to their robustness to untextured scenes and multipath. These systems triangulate depth by solving a correspondence problem between each camera and projector pixel. This is often framed as a local stereo matching task, correlating patches of pixels in the observed and reference image. However, this is computationally intensive, leading to reduced depth accuracy and framerate. We contribute an algorithm for solving this correspondence problem efficiently, without...

Publication details
Date: 1 June 2016
Type: Inproceeding
Publisher: CVPR
Awards: Oral
Jina Suh, Jerry Zhu, and Saleema Amershi

Mixed-initiative classifier training, where the human teacher can choose which items to label or to label items chosen by the computer, has enjoyed empirical success but without a rigorous statistical learning theoretical justification. We analyze the label complexity of a simple mixed-initiative training mechanism using teaching dimension and active learning. We show that mixed-initiative training is advantageous compared to either computer-initiated (represented by active learning) or human-initiated...

Publication details
Date: 1 June 2016
Type: Inproceeding
S. Shankar, D. Robertson, Y. Ioannou, A. Criminisi, and R. Cipolla
Publication details
Date: 1 June 2016
Type: Inproceeding
Yingwei Pan, Tao Mei, Ting Yao, Houqiang Li, and Yong Rui

Automatically describing video content with natural language is a fundamental challenge of computer vision. Recurrent Neural Networks (RNNs), which models sequence dynamics, has attracted increasing attention on visual interpretation. However, most existing approaches generate a word locally with the given previous words and the visual content, while the relationship between sentence semantics and visual content is not holistically exploited. As a result, the generated sentences may be contextually...

Publication details
Date: 1 June 2016
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Milan Vojnovic and Seyoung Yun

We consider the maximum likelihood parameter estimation problem for a generalized Thurstone choice model, where choices are from comparison sets of two or more items. We provide tight characterizations of the mean square error, as well as necessary and sufficient conditions for correct classification when each item belongs to one of two classes. These results provide insights into how the estimation accuracy depends on the choice of a generalized Thurstone choice model and the structure of comparison...

Publication details
Date: 1 June 2016
Type: Inproceeding
Kenneth Tran, Xiaodong He, Lei Zhang, Jian Sun, Cornelia Carapcea, Chris Thrasher, Chris Buehler, and Chris Sienkiewicz

We present an image caption system that addresses new challenges of automatically describing images in the wild. The challenges include high quality caption quality with respect to human judgments, out-of-domain data handling, and low latency required in many applications. Built on top of a state-of-the-art framework, we developed a deep vision model that detects a broad range of visual concepts, an entity recognition model that identifies celebrities and landmarks, and a confidence model for the...

Publication details
Date: 1 June 2016
Type: Article
Shenlong Wang, Sean Fanello, Christoph Rhemann, Shahram Izadi, and Pushmeet Kohli

This paper proposes a novel extremely efficient, fully-parallelizable, task-specific algorithm for the computation of global point-wise correspondences in images and videos. Our algorithm, the Global Patch Collider, is based on detecting unique collisions between image points using a collection of learned tree structures that act as conditional hash functions. In contrast to conventional approaches that rely on pairwise distance computation, our algorithm isolates distinctive pixel pairs that hit the...

Publication details
Date: 1 June 2016
Type: Inproceeding
Publisher: CVPR
Awards: Oral
Publication details
Date: 1 June 2016
Type: Inproceeding
Publisher: JMLR: Workshop and Conference Proceedings
Nasrin Mostafazadeh, Nathanael Chambers, Xiaodong He, Devi Parikh, Dhruv Batra, Lucy Vanderwende, Pushmeet Kohli, and James Allen
Publication details
Date: 1 June 2016
Type: Inproceeding
Publisher: ACL – Association for Computational Linguistics
P. Kontschieder, M. Fiterau, A. Criminisi, and S. Rota Bulo'
Publication details
Date: 1 June 2016
Type: Inproceeding
Publication details
Date: 1 June 2016
Type: Inproceeding
Publisher: JMLR: Workshop and Conference Proceedings
Yuval Marton and Kristina Toutanova

We present E-TIPSY, a search query corpus annotated with named Entities, Term Importance, POS tags, and SYntactic parses. This corpus contains crowdsourced (gold) annotations of the three most important terms in each query. In addition, it contains automatically produced annotations of named entities, part-of-speech tags, and syntactic parses for the same queries. This corpus comes in two formats: (1) Sober Subset: annotations that two or more crowd workers agreed upon, and (2) Full Glass: all...

Publication details
Date: 24 May 2016
Type: Inproceeding
Publisher: ELRA
Ayelet Ben-Sasson, Dan Pelleg, and Elad Yom-Tov

The growing diagnosis and public awareness of Autism Spectrum Disorders (ASD) leads more parents to seek answers to their suspicions for ASD in their child on Internet forums.

This study describes an analysis of the quality of content of 371 answers on Yahoo Answers (YA), a social question and answer forum, to parents querying whether their child has ASD. We contrasted the perceived quality of answers by clinicians with that of parents. The study tested the feasibility of automatically assisting...

Publication details
Date: 18 May 2016
Type: Inproceeding
Publisher: AAAI - Association for the Advancement of Artificial Intelligence
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