KDD 2020 Recognizes Winning Teams of 24th Annual KDD Cup
SAN DIEGO, Sept. 29, 2020
Across Four Competition Tracks, KDD Cup 2020 Tackled E-Commerce, Generative Adversarial Networks, Automatic Graph Representation Learning, Automated Machine Learning, Mobility-on-Demand (MoD) Platforms and Reinforcement Learning
SAN DIEGO, Sept. 29, 2020 /PRNewswire/ -- KDD 2020, the premier interdisciplinary conference in data science, recognized over sixty winning teams in this year's KDD Cup competition, which took place virtually Aug. 23-27, 2020. As one of the first competitions of its kind, the KDD Cup is known for solving industry challenges by crowdsourcing participation, while also providing a platform for aspiring and experienced data scientists alike to build their professional profiles and network with leading professionals in the field.
"In 2020, KDD Cup coordinated an unprecedented four parallel competition tracks to offer data scientists the opportunity to tackle emerging disciplines like adversarial learning and deep learning," said Iryna Skrypnyk, co-chair of KDD Cup 2020 and director of AI and machine learning at EVERSANA. "Given the number of participating teams from around the globe, winners in this year's competition were separated by the slimmest of margins. The 2020 KDD Cup ultimately awarded over sixty teams as each solutions brought interesting findings in methodologies and architectures."
This year's competition was supported by contributions of data sets and track challenges from Alibaba, BienData, DiDi Chuxing, and 4Paradigm with sponsorship from ChaLearn, Duke University, Google, Stanford University, Tsinghua University, and the University of Illinois at Urbana-Champaign. Over 4,500 teams registered for the KDD Cup and competition winners were selected by an entirely automated process. KDD Cup 2020 winners include:
- KDD Cup Track 1: Regular Machine Learning Competition – Challenges for Modern E-Commerce Platform
- KDD Cup Track 2: Regular Machine Learning Competition – Adversarial Attacks and Defense on Academic Graphs
- KDD Cup Track 3: Automated Machine Learning Competition – AutoML for Graph Representation Learning
- KDD Cup Track 4: Reinforcement Learning Competition – Learning to Dispatch and Reposition on a Mobility-on-Demand Platform
In addition to Skrypnyk, KDD Cup 2020 was co-chaired by Jie Tang, professor of Computer Science at Tsinghua University, and Jieping Ye, vice president of research at Didi Chuxing and associate professor of Computer Science at the University of Michigan. Claudia Perlich, senior data scientist at Two Sigma, served as an advisor to the committee.
The 25th Annual KDD Cup will take place in conjunction with KDD 2021 on Aug. 14-18, 2021 in Singapore. Companies interested in sponsoring a competition track are encouraged to submit proposals that meet the following requirements: a novel and motivated goal, an interesting challenge and a broad outreach for the data science community, a rigid and fair setup, a challenging yet manageable task, and domain accessibility to the general public. Submissions that address a broad societal or business impact are preferred. For additional information on this year's cup and winners, reach out to firstname.lastname@example.org. For information on the 2021 KDD Cup's call for proposals, please contact: email@example.com.
About ACM SIGKDD:
ACM is the premier global professional organization for researchers and professionals dedicated to the advancement of the science and practice of knowledge discovery and data mining. SIGKDD is ACM's Special Interest Group on Knowledge Discovery and Data Mining. The annual KDD International Conference on Knowledge Discovery and Data Mining is the premier interdisciplinary conference for data mining, data science and analytics.
For more information on KDD, please visit: https://www.kdd.org/.
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SOURCE ACM SIGKDD