Call for papers Manifold Learning from Euclid to Riemann ICPR Workshop
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We are organizing the Manifold Learning from Euclid to Riemann Workshop In Conjunction with the 25th International Conference On Pattern Recognition, Milan, Italy 10 – 15 January 2021
We encourage discussions on recent advances, ongoing developments, and novel applications of manifold learning, optimization, feature representations and deep learning techniques. We are soliciting original contributions that address a wide range of theoretical and practical issues including, but not limited to:
Theoretical Advances related to manifold learning such as
· Dimensionality Reduction (e.g., Locally Linear Embedding, Laplacian Eigenmaps and etc.)
· Clustering (e.g., discriminative clustering)
· Kernel methods
· Metric Learning
· Time series on non-linear manifolds
· Transfert learning on non-linear manifolds
· Generative Models on non-linear manifolds
· Subspace Methods (e.g., Subspace clustering)
· Advanced Optimization Techniques (constrained and non-convex optimization techniques on non-linear manifolds)
· Mathematical Models for learning sequences
· Mathematical Models for learning Shapes
· Deep learning and non-linear manifolds
· Low-rank factorization methods
Applications:
· Biometrics
· Image/video recognition
· Action/activity recognition
· Facial expressions recognition
· Learning and scene understanding
· Medical imaging
· Robotics
· Other related topics not listed above
Special Issue: We will also invite selected papers for submission to a special issue on
Learning with Manifolds in computer vision in IMAGE AND VISION COMPUTING Journal. https://www.journals.elsevier.com/image-and-vision-computing/call-for-papers/special-issue-on-learning-with-manifolds-in-computer-vision
Important Dates
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Workshop submission deadline: October 10th
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Workshop author notification: November 10th
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Camera-ready submission: November 15th
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Finalized workshop program: December 1st