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KDD 2016 - San Francisco   

22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), San Francisco 2016

KDD 2016, a premier interdisciplinary conference, brings together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics, and big data.


Event sections

KDD 2016 Workshops  

Opening Ceremony

[syn]  1782 views, 16:13  
flagOpening CeremonyOpening Ceremony
Balaji Krishnapuram, Mohak Shah, Shipeng Yu Balaji Krishnapuram, Mohak Shah, Shipeng Yu
[syn]  3202 views, 1:07:05  
flagAward CeremonyAward Ceremony
Jian Pei, Wei Wang, et al. Jian Pei, Wei Wang, Jiawei Han, Vijay Narayanan, Markus Weimer, Ron Bekkerman, Faisal Farooq, Evangelos Simoudis, Rajesh Parekh, Usama Fayyad, Dou Shen, Rastogi Rajeev, Alex Smola, Charu Aggarwal, Bing Liu

Keynote Talks

Plenary Panel

votesvotesvotesvotesvotes [syn]  10151 views, 1:46:19   Panel Talk
flagIs Deep Learning the New 42?Is Deep Learning the New 42?
Andrei Broder, Jennifer Neville, et al. Andrei Broder, Jennifer Neville, Jitendra Malik, Isabelle Guyon, Nando de Freitas, Pedro Domingos
comments1 comment 

Applied Data Science Invited Talks

The Applied Data Science Invited Talks provide a venue for leading experts in the world of applied data mining and knowledge discovery. These invited talks feature highly influential speakers who have directly contributed to successful data mining applications in their respective fields. The talks and discussions focus on innovative and leading-edge, large-scale industry or government applications of data mining in areas such as finance, health-care, bio-informatics, public policy, infrastructure, telecommunications, social media and computational advertising.


[syn]  2431 views, 2:11:24   Tutorial
flagLifelong Machine Learning and Computer Reading the WebLifelong Machine Learning and Computer Reading the Web
Zhiyuan (Brett) Chen, Estevam R. Hruschka, Bing Liu Zhiyuan (Brett) Chen, Estevam R. Hruschka, Bing Liu
[syn]  2374 views, 2:52:26   Tutorial
flagIoT Big Data Stream MiningIoT Big Data Stream Mining
Albert Bifet, João Gama, Latifur Khan Albert Bifet, João Gama, Latifur Khan

Hands-On Tutorials

[syn]  3699 views, 1:51:39   Hands-On Tutorial
flagBuilding Recommender Systems using Photon MLBuilding Recommender Systems using Photon ML
Deepak Agarwal, Paul Ogilvie, et al. Deepak Agarwal, Paul Ogilvie, Xianxing Zhang, Josh Fleming, Alex Shelkovnykov, Bee-Chung Chen
[syn]  2249 views, 3:16:32   Hands-On Tutorial
flagIntroduction to Spark 2.0Introduction to Spark 2.0
Matei Zaharia, Doug Bateman, et al. Matei Zaharia, Doug Bateman, Michael Armbrust, Reynold Xin
[syn]  3368 views, 2:46:16   Hands-On Tutorial
flagScalable R on SparkScalable R on Spark
Mengyue Zhao, Hang Zhang, et al. Mengyue Zhao, Hang Zhang, Vanja Paunić, Srini Kumar, Mario Inchiosa, Robert Horton, Debraj GuhaThakurta, John-Mark Agosta

Applied Data Science Session: Social Good - I

Applied Data Science Session: Recommendations and Ranking

Applied Data Science Session: Social Networks and Social Media

Applied Data Science Session: Machine Learning Algorithms

Applied Data Science Session: Systems and Experimentation

Applied Data Science Session: E-Commerce

Research Session: Graphs and Rich Data

Research Session: Graphs and Social Networks - I

Research Session: Graphs and Social Networks - II

Research Session: Clustering

Research Session: Unsupervised Learning and Anomaly Detection

Research Session: Supervised Learning

Research Session: User-Behavior Modeling

Research Session: Large-Scale Data Mining

Research Session: Streams and Temporal Evolution - I

Research Session: Streams and Temporal Evolution - II

Research Session: Deep Learning and Embedding

Research Session: Recommender System

Research Session: Sequence Mining

Research Session: Optimization

Networking Session: Data Science of China @ KDD 2016

The proliferation of big data has fostered unprecedented opportunities in China, where talents, data, universities, industries and markets have been ready to make a new level of success for data science. The purpose of this event is to collectively showcase the KDD progress in both academia and industry of China as well the research that has been done by Chinese around the world. This event will help you network with Chinese professionals working on KDD, exploring collaboration opportunities and the KDD industries in China. This event is organized by SIGKDD China Chapter, following the successful event held at KDD 2015 in Sydney.

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