Towards Supporting Visual Question and Answering Applications

[1]  Heesoo Myeong,et al.  Tensor-Based High-Order Semantic Relation Transfer for Semantic Scene Segmentation , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[2]  Eugene Agichtein,et al.  Predicting information seeker satisfaction in community question answering , 2008, SIGIR '08.

[3]  Marc Teboulle,et al.  A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..

[4]  Joachim M. Buhmann,et al.  Weakly supervised semantic segmentation with a multi-image model , 2011, 2011 International Conference on Computer Vision.

[5]  Michael I. Jordan,et al.  Loopy Belief Propagation for Approximate Inference: An Empirical Study , 1999, UAI.

[6]  Jiawei Han,et al.  Linear Discriminant Dimensionality Reduction , 2011, ECML/PKDD.

[7]  Pushmeet Kohli,et al.  Robust Higher Order Potentials for Enforcing Label Consistency , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[8]  Idan Szpektor,et al.  Learning from the past: answering new questions with past answers , 2012, WWW.

[9]  Richard E. Ladner,et al.  Tactile graphics with a voice: using QR codes to access text in tactile graphics , 2014, ASSETS.

[10]  Tim Ken Mackey,et al.  Establishing a Link Between Prescription Drug Abuse and Illicit Online Pharmacies: Analysis of Twitter Data , 2015, Journal of medical Internet research.

[11]  R. Tibshirani,et al.  A LASSO FOR HIERARCHICAL INTERACTIONS. , 2012, Annals of statistics.

[12]  Johan Braeckman,et al.  Individual Differences in Reproductive Strategy are Related to Views about Recreational Drug Use in Belgium, The Netherlands, and Japan , 2013, Human Nature.

[13]  Antonio Torralba,et al.  Nonparametric scene parsing: Label transfer via dense scene alignment , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[14]  Xirong Li,et al.  Adaptive Tag Selection for Image Annotation , 2014, PCM.

[15]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[16]  Michael D. Barnes,et al.  Tweaking and Tweeting: Exploring Twitter for Nonmedical Use of a Psychostimulant Drug (Adderall) Among College Students , 2013, Journal of medical Internet research.

[17]  Ronan Collobert,et al.  From image-level to pixel-level labeling with Convolutional Networks , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[18]  J. Platt Sequential Minimal Optimization : A Fast Algorithm for Training Support Vector Machines , 1998 .

[19]  Giovanni Fusco,et al.  The Tactile Graphics Helper: Providing Audio Clarification for Tactile Graphics Using Machine Vision , 2015, ASSETS.

[20]  William Stafford Noble,et al.  Support vector machine , 2013 .

[21]  Yen-Yu Lin,et al.  Multiple Structured-Instance Learning for Semantic Segmentation with Uncertain Training Data , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[22]  David W. Hosmer,et al.  Applied Logistic Regression , 1991 .

[23]  W. Bruce Croft,et al.  A framework to predict the quality of answers with non-textual features , 2006, SIGIR.

[24]  Joachim M. Buhmann,et al.  Weakly supervised structured output learning for semantic segmentation , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[25]  Robin Mermelstein,et al.  Gender-Specific Relationships Between Depressive Symptoms, Marijuana Use, Parental Communication and Risky Sexual Behavior in Adolescence , 2013, Journal of youth and adolescence.

[26]  W. Chapman,et al.  Using Twitter to Examine Smoking Behavior and Perceptions of Emerging Tobacco Products , 2013, Journal of medical Internet research.

[27]  Sheng Zeng,et al.  Weakly supervised semantic segmentation for social images , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[28]  Marc A Zimmerman,et al.  Permissive norms and young adults' alcohol and marijuana use: the role of online communities. , 2012, Journal of studies on alcohol and drugs.

[29]  Pedro Jussieu de Rezende,et al.  A data reduction and organization approach for efficient image annotation , 2013, SAC '13.

[30]  Luc Van Gool,et al.  Active MAP Inference in CRFs for Efficient Semantic Segmentation , 2013, 2013 IEEE International Conference on Computer Vision.

[31]  Jianfei Cai,et al.  Compact Representation for Image Classification: To Choose or to Compress? , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[32]  Antonio Criminisi,et al.  TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context , 2007, International Journal of Computer Vision.

[33]  Ravi Kumar,et al.  Great Question! Question Quality in Community Q&A , 2014, ICWSM.

[34]  Melissa J. Krauss,et al.  Characterizing the Followers and Tweets of a Marijuana-Focused Twitter Handle , 2014, Journal of medical Internet research.

[35]  Danielle E. Ramo,et al.  Broad Reach and Targeted Recruitment Using Facebook for an Online Survey of Young Adult Substance Use , 2012, Journal of medical Internet research.

[36]  Jure Leskovec,et al.  Discovering value from community activity on focused question answering sites: a case study of stack overflow , 2012, KDD.

[37]  L. Bernstein,et al.  Population‐based case‐control study of recreational drug use and testis cancer risk confirms an association between marijuana use and nonseminoma risk , 2012, Cancer.

[38]  Jieping Ye,et al.  A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems , 2013, ICML.

[39]  J. Borwein,et al.  Two-Point Step Size Gradient Methods , 1988 .

[40]  Johan A. K. Suykens,et al.  Least Squares Support Vector Machine Classifiers , 1999, Neural Processing Letters.

[41]  S. J. Press,et al.  Choosing between Logistic Regression and Discriminant Analysis , 1978 .

[42]  Jitendra Malik,et al.  Semantic segmentation using regions and parts , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[43]  Alton Yeow-Kuan Chua,et al.  Selection of the Best Answer in CQA Services , 2010, 2010 Seventh International Conference on Information Technology: New Generations.

[44]  Yuxin Peng,et al.  Weakly-Supervised Image Parsing via Constructing Semantic Graphs and Hypergraphs , 2014, ACM Multimedia.

[45]  Pascal Fua,et al.  SLIC Superpixels Compared to State-of-the-Art Superpixel Methods , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[46]  Baoxin Li,et al.  Finding needles of interested tweets in the haystack of Twitter network , 2016, 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

[47]  Pável Calado,et al.  Exploiting user feedback to learn to rank answers in q&a forums: a case study with stack overflow , 2013, SIGIR.

[48]  Joachim M. Buhmann,et al.  Towards weakly supervised semantic segmentation by means of multiple instance and multitask learning , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[49]  Aaron Smith,et al.  Social Media & Mobile Internet Use among Teens and Young Adults. Millennials. , 2010 .

[50]  James Fan,et al.  Learning to rank for robust question answering , 2012, CIKM.

[51]  Feng Xu,et al.  Detecting high-quality posts in community question answering sites , 2015, Inf. Sci..

[52]  Jiasen Lu,et al.  VQA: Visual Question Answering , 2015, ICCV.

[53]  Jing Liu,et al.  Weakly-Supervised Dual Clustering for Image Semantic Segmentation , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[54]  Baoxin Li,et al.  Towards Predicting the Best Answers in Community-based Question-Answering Services , 2013, ICWSM.

[55]  Christine Lee Recruitment through Social Networking Sites: Are Substance Use Patterns Comparable to Traditional Recruitment Methods? , 2014 .

[56]  Kilian Q. Weinberger,et al.  Fast Image Tagging , 2013, ICML.

[57]  Pnina Fichman,et al.  A comparative assessment of answer quality on four question answering sites , 2011, J. Inf. Sci..

[58]  Sharma Chakravarthy,et al.  Answer Quality Prediction in Q/A Social Networks by Leveraging Temporal Features , 2013, Int. J. Next Gener. Comput..

[59]  Lada A. Adamic,et al.  Knowledge sharing and yahoo answers: everyone knows something , 2008, WWW.

[60]  Emile H. L. Aarts,et al.  Simulated annealing and Boltzmann machines - a stochastic approach to combinatorial optimization and neural computing , 1990, Wiley-Interscience series in discrete mathematics and optimization.

[61]  Yuxin Peng,et al.  Semantic Graph Construction for Weakly-Supervised Image Parsing , 2014, AAAI.

[62]  Svetlana Lazebnik,et al.  Finding Things: Image Parsing with Regions and Per-Exemplar Detectors , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[63]  Mihai Surdeanu,et al.  Learning to Rank Answers to Non-Factoid Questions from Web Collections , 2011, CL.

[64]  H. Neighbors,et al.  Racial/Ethnic differences in smoking, drinking, and illicit drug use among American high school seniors, 1976-89. , 1991, American journal of public health.

[65]  Mihai Surdeanu,et al.  Learning to Rank Answers on Large Online QA Collections , 2008, ACL.

[66]  Xiao Liu,et al.  Probabilistic Graphlet Cut: Exploiting Spatial Structure Cue for Weakly Supervised Image Segmentation , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[67]  Seunghoon Hong,et al.  Weakly Supervised Semantic Segmentation Using Superpixel Pooling Network , 2017, AAAI.

[68]  Yi Yang,et al.  A Probabilistic Associative Model for Segmenting Weakly Supervised Images , 2014, IEEE Transactions on Image Processing.

[69]  Joachim M. Buhmann,et al.  Active learning for semantic segmentation with expected change , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[70]  Afshin Dehghan,et al.  Improving an Object Detector and Extracting Regions Using Superpixels , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.