Datasets and Benchmarks
Dataset and Benchmark Track 2
Joaquin Vanschoren · Serena Yeung
Moderator : Frank R Hutter
The Datasets and Benchmarks track serves as a novel venue for high-quality publications, talks, and posters on highly valuable machine learning datasets and benchmarks, as well as a forum for discussions on how to improve dataset development. Datasets and benchmarks are crucial for the development of machine learning methods, but also require their own publishing and reviewing guidelines. For instance, datasets can often not be reviewed in a double-blind fashion, and hence full anonymization will not be required. On the other hand, they do require additional specific checks, such as a proper description of how the data was collected, whether they show intrinsic bias, and whether they will remain accessible.
Schedule
Wed 8:00 a.m. - 8:10 a.m.
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A Large-Scale Database for Graph Representation Learning
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Oral
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SlidesLive Video |
Scott Freitas · Yuxiao Dong · Joshua Neil · Duen Horng Chau 🔗 |
Wed 8:10 a.m. - 8:20 a.m.
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WRENCH: A Comprehensive Benchmark for Weak Supervision
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Oral
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SlidesLive Video |
Jieyu Zhang · Yue Yu · · Yujing Wang · Yaming Yang · Mao Yang · Alexander Ratner 🔗 |
Wed 8:20 a.m. - 8:30 a.m.
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ATOM3D: Tasks on Molecules in Three Dimensions
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Oral
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SlidesLive Video |
13 presentersRaphael Townshend · Martin Vögele · Patricia Suriana · Alex Derry · Alexander Powers · Yianni Laloudakis · Sidhika Balachandar · Bowen Jing · Brandon Anderson · Stephan Eismann · Risi Kondor · Russ Altman · Ron Dror |
Wed 8:30 a.m. - 8:40 a.m.
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Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Research
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Oral
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SlidesLive Video |
Bernard Koch · Emily Denton · Alex Hanna · Jacob G Foster 🔗 |
Wed 8:40 a.m. - 9:00 a.m.
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Joint Q&A
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Q&A
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SlidesLive Video |
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