ACM SIGKDD Conference on Knowledge Discovery and Data Mining (ACM SIGKDD KDD)*

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The ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) is a premier interdisciplinary conference, brings together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics, and big data.

Conference History:

27th ACM SIGKDD KDD 2021, August 14-18, 2021, Singapore

26th ACM SIGKDD KDD 2020, August 23-27, 2020, San Diego, CA, USA Virtual venue
Pre-conference Workshops (Aug 24): AdKDD 2020; 16th International Workshop on Mining and Learning with Graphs; International Workshop on Knowledge Graph: Mining Knowledge Graph for Deep Insights; Machine Learning in Finance; The Fourth International Workshop on Automation in Machine Learning; The Second International Workshop on Deep Learning on Graphs: Methods and Applications (KDD-DLG’20); 6th Workshop on Mining and Learning from Time Series; epiDAMIK: Epidemiology meets Data Mining and Knowledge discovery; Knowledge Graphs and E-Commerce; 2nd International Workshop on Deep Learning Practice for High-Dimensional Sparse Data with KDD 2020; Second Workshop on Adversarial Learning Methods for Machine Learning and Data Mining; MLHat: Deployable Machine Learning for Security Defense; 1st KDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems (DeepSpatial); KiML 2020: First International Workshop on Knowledge-infused Mining and Learning for Social Impact (Advancing Decision Making in Health, Crisis Response, and Finance); The Second International Workshop on Intelligent Information Feed (KDDFeed);…
Pre-conference Lecture-style Tutorials (Aug 23): …

Note: The conference was scheduled for August 22-27, 2020

25th ACM SIGKDD KDD 2019, August 4-8, 2019, Anchorage, AK, USA
Workshops: 8th International Workshop on Parallel and Distributed Computing for Large-Scale Machine Learning and Big Data Analytics; 1st International Workshop on Intelligent Information Feed; Deep Learning on Graphs: Methods and Applications (DLG’19); Deep Reinforcement Learning for Knowledge Discovery; 3rd International Workshop on Automation in Machine Learning; Applied data science in Healthcare: bridging the gap between data and knowledge; Epidemiology meets Data Mining and Knowledge discovery (epiDAMIK); Learning and Mining for Cyber Security (LEMINCS); From Data Integration to Knowledge Graphs: Challenges and Experiences; 4th International Workshop on Fashion and KDD (AI for fashion); Data Collection, Curation, and Labeling for Mining and Learning; Adversarial Learning Methods for Machine Learning and Data Mining; 5th Workshop on Mining and Learning from Time Series; 1st International Workshop on Deep Learning Practice for High-Dimensional Sparse Data with KDD; AdKDD 2019 Workshop; 15th International Workshop on Mining and Learning with Graphs (MLG); Deep Learning for Education (DL4Ed)
Lecture-Style Tutorials: Deep Bayesian Mining, Learning and Understanding; Optimize the Wisdom of the Crowd: Inference, Learning, and Teaching; Interpretable knowledge Discovery Reinforced by Visual Methods; Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned; Recent Progress in Zeroth Order Optimization and Its Applications to Adversarial Robustness in Data Mining and Machine Learning; Learning From Networks: Algorithms, Theory, & Applications; Statistical Mechanics Methods for Discovering Knowledge from Production-Scale Neural Networks; Data Integration and Machine Learning: A Natural Synergy; Deep Reinforcement Learning with Applications in Transportation
Hands-on Tutorials: Put Deep Learning to Work: A Practical Introduction using Amazon Web Services; Democratizing & Accelerating AI through Automated Machine Learning; Introduction to computer vision and realtime deep learning-based object detection; Deep Learning for NLP with TensorFlow; Deep Learning at Scale on Databricks; Deep learning for time series forecasting; Building and Productionizing Machine Learning With Kubernetes: A Tutorial For Data Scientists; Learning Graph Neural Networks with Deep Graph Library; From Graph to Knowledge Graph: Mining Large-scale Heterogeneous Networks Using Spark

24th ACM SIGKDD KDD 2018, August 19-23, 2018, London, United Kingdom

23th ACM SIGKDD KDD 2017, August 13-17, 2017, Halifax, NS, Canada

22th ACM SIGKDD KDD 2016, August 13-17, 2016, San Francisco, CA, USA

21th ACM SIGKDD KDD 2015, August 10-13, 2015, Sydney, Australia

20th ACM SIGKDD KDD 2014, August 24-27, 2014, New York, NY, USA

19th ACM SIGKDD KDD 2013, August 11-14, 2013, Chicago, IL, USA

18th ACM SIGKDD KDD 2012, August 12-16, 2012, Beijing, China

17th ACM SIGKDD KDD 2011, August 21-24, 2011, San Diego, CA, USA

16th ACM SIGKDD KDD 2010, July 25-28, 2010, Washington, DC, USA

15th ACM SIGKDD KDD 2009, June 28 – July 1, 2009, Paris, France

14th ACM SIGKDD KDD 2008, August 24-27, 2008, Las Vegas, NV, USA

13th ACM SIGKDD KDD 2007, August 12-15, 2007, San Jose, CA, USA

12th ACM SIGKDD KDD 2006, August 20-23, 2006, Philadelphia, PA, USA

11th ACM SIGKDD KDD 2005, August 21-24, 2005, Chicago, IL, USA

10th ACM SIGKDD KDD 2004, August 22-25, 2004, Seattle, WA, USA

9th ACM SIGKDD KDD 2003, August 24-27, 2003, Washington, DC, USA

8th ACM SIGKDD KDD 2002, July 23-26, 2002, Edmonton, Alberta, Canada

7th ACM SIGKDD KDD 2001, August 26-29, 2001, San Francisco, CA, USA

6th ACM SIGKDD KDD 2000, August 20-23, 2000, Boston, MA, USA

5th ACM SIGKDD KDD 1999, August 15-18, 1999, San Diego, CA, USA

4th KDD 1998, August 27-31, 1998, New York, NY, USA

3rd KDD 1997, August 14-17, 1997, Newport Beach, CA

2nd KDD 1996, August 4-8, 1996, Portland, OR

1st KDD 1995, August 20-21, 1995, Montreal, Canada

KDD Workshop 1994, Seattle, WA, July 31-Aug 1, 1994

KDD Workshop 1993, Washington, DC, July 11-12, 1993

KDD Workshop 1991, Anaheim, CA, July 14-15, 1991

KDD Workshop 1989, Detroit, MI, August 20, 1989

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