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ICML 2021 Workshop: Self-Supervised Learning for Reasoning and Perceptions
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ICML 2021 Workshop: Self-Supervised Learning for Reasoning and Perception ICML 2021 Workshop: Self-Supervised Learning for Reasoning and Perception Home Call for Submissions Schedule Speakers Organizers Program Committee Accepted Papers Join our workshop via Zoom: https://us02web.zoom.us/j/81362317971?pwd=WWdOWHF1VUdrRGdtZjJSME1sdGtjZz09 For poster sessions : posters can be viewed here . If interested in a poster, you can click the corresponding Zoom link. The authors are presenting their poster in their Zoom. Online Workshop, July 24 (Saturday), 2021 Self-supervised learning (SSL) is an unsupervised approach for representation learning without relying on human-provided labels. It creates auxiliary tasks on unlabeled input data and learns representations by solving these tasks. SSL has demonstrated great success on images (e.g., MoCo, PIRL, SimCLR) and texts (e.g., BERT) and has shown promising results in other data modalities, including graphs, time-series...
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