Deep learning has dramatically improved the state-of-the-art in many different artificial intelligent tasks like object detection, speech recognition, machine translation, but many challenges remain. This workshop aims to bring together researchers to discuss some of the more controversial topics in deep learning today, especially in unsupervised learning, to brainstorm about new solutions. Specifically, we focus on the following and related topics:

  • Unsupervised feature learning based on deep learning
  • Deep clustering algorithms
  • Inference and optimization
  • Network architectures of deep unsupervised learning
  • Theoretical foundations of deep unsupervised learning
  • Applications of deep unsupervised learning
  • Through invited talks, presentations, and posters by the participants, this workshop will showcase the latest advances in deep unsupervised learning and address questions that are at the centre of current deep unsupervised learning research.



Zhao Kang, Yazhou Ren, Zenglin Xu

Invited Speakers:



We invite both presentations and posters with new insights and experiences about above topics. Please contact for any questions.