Anomaly Detection Using Sparse Structure Learning We / Dynamic Social Networks / Agenor Mafra-Neto ISCA Technologies / IBM / Accessible Set Systems / Rayid Ghani Accenture Technology Labs / Graham Cormode AT&T Labs / Electrical Engineering ESAT-SCD Attentio Company / Yihong Gong NEC Laboratories America / Axel Blumenstock Daimler AG / /
Country
China / France / Turkey / / /
Event
Reorganization / /
Facility
Bing Liu University of Illinois at / Marisa Thoma Institute / Free University / Andrej Taliun Free University / ESAT-SCD Wuhan University of Science / DT09 Abstracts Jinze Liu University of Kentucky Department / Arthur Gretton Max-Planck Institute / Christoph Schlieder University / Computer Science Sichuan University / Yiping Ke The Chinese University / Jaegul Choo College of Computing Georgia Institute / Ran He National Laboratory of Pattern Recognition Institute / Zhijun Yin University of Illinois / Chris Ding University of Texas / Serdar Kozat Koc University / Medical Research University / Randy Goebel University / See-Kiong Ng Institute / Content-Based Social Network Exploration Through Multi-Way Visual Analysis Hans-Peter Kriegel Ludwig-Maximilians University / Yu The Chinese University / Adriana Prado University / Communication Engineering University / Engineering University of Minnesota / Renqiang Min Dept Computer Science University / Engineering Management Chinese University / Haesun Park Georgia Institute / Kamalika Das University of Maryland / Vivekanand Gopalkrishnan Nanyang Technological University / Takeaki Uno National Institute / Paul Davidsson Blekinge Institute / Jiawei Han University of Illinois / Xiaoli Li Institute / Alexander Gray Georgia Institute / Nishant A. Mehta College of Computing Georgia Institute / Lian Liu University of Kentucky Department / CSEE University of Maryland / Stefan Wrobel Fraunhofer IAIS University / Xintao Wu University of North Carolina / Tamas Horvath University / Michael I. Jordan University of California / Eamonn Keogh University of California / Anthony Bonner Dept Computer Science University / Partha Niyogi University of Chicago Department / /
IndustryTerm
road network / kernel perceptron algorithm / data mining algorithms / threshold-based correlative graph mining algorithm / energy / effective algorithm / eigen monitoring algorithms / efficient algorithm / large margin learning algorithms / community mining measure / candidate search sequences / search operations / data mining community / search space / pattern mining / parallel energy minimization using barycenter heuristic / frequent itemset mining algorithms / data mining applications / frequent subgraph mining / Online Learning / real corporate social networks / hierarchical clustering algorithm / itemset mining / space-efficient algorithms / real social network / cluster ensemble algorithms / frequent pattern mining / asynchronous algorithm / privacy preserving social network / web search / parallel algorithm / social network / famous frequent itemset mining / set systems / automation algorithms / text mining / efficient depth-first algorithm / unsupervised algorithm / social media / manufacturing / pattern mining tasks / web content / data mining / grammar mining / regularized learning algorithms / large data streams using devices / /
NaturalFeature
Data Streams Data stream / /
Organization
University of Maryland / Chinese University of Hong Kong / Northwestern University Department of Electrical Engineering / .lmu.de Hong Cheng Department of Systems Engineering / Computer Science University / Iowa State University / University of Alberta / Pattern Recognition Institute of Automation / School of Computer Science / University of Chicago / Rensselaer Polytechnic Institute / Fei Wang School of CIS / George Mason University / Harvard University Department of Computer Science / Hokkaido University / University of Kentucky Department of Computer Science / Shyam Boriah Department / Koc University / Aalborg University / Nishant A. Mehta College / Hanhuai Shan Department of Computer Science / Computer Science Northwestern University / Temple University / University of Illinois / Xiaoli Li Institute for Infocomm Research / Aachen University / Jimeng Sun IBM T.J. Watson Research Center / College of Infor / Katholieke Universiteit Leuven / University of Bonn Fraunhofer IAIS / University of Toronto / Alok Choudhary Department of Electrical Engineering / Bojian Xu Department of Electrical / Mohamed Mokbel Department of Computer Science / See-Kiong Ng Institute / Arturas Mazeika Max-Planck-Institut f¨ / Yan Liu DT09 Abstracts IBM Research T. J. Watson Research Center / Oregon State University / Wuhan University / Nanyang Technological University / Singapore / Elisa Fromont Universite / Content-Based Social Network Exploration Through Multi-Way Visual Analysis Hans-Peter Kriegel Ludwig-Maximilians University Munich / Jaegul Choo College / Tsuyoshi Ide IBM Research Tokyo Research Lab. / Vassilios Verykios Department of Computer / Institute for Biological Cybernetics T¨ / University of North Carolina at Charlotte / Thomas Dietterich School of EECS / University of Maryland / Baltimore County / Temple University Department of Computer and Information Science / Carnegie Mellon University / Smithsonian Center for Astrophysics / University of California / Riverside / Marisa Thoma Institute for Informatics Ludwig-Maximilians-Universit¨ / Michigan State University / University of Antwerp / Partha Niyogi University of Chicago Department / Computer & Communication Engineering University of Thessaly / Chinese Academy of Sciences / University of Texas at Arlington / Xingwei Yang Department of Computer / University of California / Berkeley / Tufts University / Graduate School / Harvard University Harvard / Christoph Schlieder University / Florida International University / Georgia Institute of Technology / Computer Science Sichuan University / Chengdu / National Aeronautics and Space Administration / Andrej Taliun Free University of Bolzen-Bolzano / Thomas Seidl RWTH Aachen University / Nanyang Technological University / University of Minnesota / William S. Cleveland Purdue University Department / Hillol Kargupta Department / /
Person
Semi-Supervised Learning Algorithm / Slobodan Vucetic / Oksana Yakhnenko / Max-Min Modularity / Tao Li / Wagner Meira JR. / Celine Robardet / Rong Jin / Large Margin Linear Classi / Kirk Borne Computational / Carla Brodley / Chris Giannella / Yan Liu / Jaime Carbonell / Mohamed Mokbel / Jie Wang / Stefan Wrobel Fraunhofer / Dan R. Preston / Hiroki Arimura / Dragoljub Pokrajac / Luc De Raedt Katholieke Universiteit / Tsuyoshi Ide / Bryan Kisiel / Thomas Seidl / Xiaoyue Wang / Hong Cheng / Kanishka Bhaduri / Siegfried Nijssen / Bart De Moor / Wei-Keng Liao / Shi Yu / Markus Mueller / Jun Zhang / Xin Jin / Raj Bhatnagar Universtiy / Bao-Gang Hu / Xiao-Tong Yuan / Waseem Ahmad / Paul Davidsson / Yun Chi / Michail Vlachos / Ralph Krieger / Yves Moreau / Raghu Ramakrishnan / Yiping Ke / Wesley Gri / James Cheng Nanyang / Alexander Gray / Arthur Gretton / Hisashi Kashima / Mario Boley Fraunhofer / Elisa Fromont / Adriano Veloso / Rui Kuang / Barry L. Drake / Alex Smola / Wolfgang Glanzel / Yang Carnegie / William S. Cleveland / Faris Alqadah / Shixia Liu / Andrej Taliun / Philip Yu / Ira Assent / Alok Choudhary / / /
Position
General / representative / president / Cao / /
Product
SDI iP1 Speakers / DensEst / KL / /
ProgrammingLanguage
R / /
ProvinceOrState
California / Alberta / Texas / Baltimore County / Minnesota / Computer Science University of Maryland Baltimore County / Maryland / North Carolina / /
PublishedMedium
Machine Learning / /
RadioStation
CORE / /
Technology
efficient algorithms / eigen monitoring algorithms / base FIM algorithms / online large margin learning algorithms / efficient h-LDA algorithm / effective algorithm / frequent itemset mining algorithms / FIM algorithm / Machine Learning / hierarchical clustering algorithm / efficient algorithm / space-efficient algorithms / Data Mining / simulation / kernel perceptron algorithm / threshold-based correlative graph mining algorithm / gene expression / efficient depth-first algorithm / Jingrui He Machine Learning Department Carnegie Mellon University jingruih@cs.cmu.edu Jaime Carbonell Language Technologies / cluster ensemble algorithms / regularized learning algorithms / embarrassingly parallel algorithm / automation algorithms / adaptive kernel K-means clustering algorithm / FIM algorithms / data mining algorithms / MIDS algorithm / Existing cluster ensemble algorithms / 34 DT09 Abstracts Eigen Monitoring Algorithms / /
DT09 Abstracts IP1 A Geometric Perspective on Machine Learning and Data Mining Increasingly, we face machine learning problems in very