In total 22 abstracts were accepted for presentation at the workshop.
Some authors opted to have their abstracts published at this website.
Mukul Bhutani, Pratik Jawanpuria, Hiroyuki Kasai, and Bamdev Mishra
Low-rank geometric mean metric learning
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Zois Boukouvalas, Jialun Zhou, Mark Fuge, and Salem Said
MGGD Parameter Estimation on the Space of SPD Matrices
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Pierre-Yves Gousenbourger, Estelle Massart, and P.-A. Absil
Data fitting on manifolds with blended cubic splines
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William H. Guss and Ruslan Salakhutdinov
Towards a Theory of Neural Topology: The Homology of Rectified Units
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Jianshu Li, Fang Zhao, Jiashi Feng, Sujoy Roy, Shuicheng Yan, and Terence Sim
Landmark Free Face Attribute Prediction --
Geometric Transformation Learning in Face Attribute Prediction
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Lars Lundberg, Håkan Lennerstad, Eva Garcia-Martin, Niklas Lavesson, and Veselka Boeva
Hyperplane Folding – a Way to Increase the Margin in
Support Vector Machines
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Cyrus Mostajeran and Rodolphe Sepulchre
Homogeneous Cone Fields: Affine-Invariant Orders
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Finding geodesics on uncertain manifolds
Tao Yang and Søren Hauberg
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Jialun Zhou and Salem Said
Efficient recursive estimates in a Riemannian manifold
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Geometric Universality of Adversarial Examples in Deep Learning
Haosheng Zou, Hang Su, Tianyu Pang, and Jun Zhu
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Applications of the f-divergence to variational inference
Sabin Roman and Alexandra Peşte
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Shuffling for incremental gradient descent to compute the Riemannian barycenter
Estelle Massart, Julien M. Hendrickx, and P.-A. Absil
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Common subspace extraction using a Grassmannian minimum enclosing ball approach
Emilie Renard, Kyle A. Gallivan, and P.-A. Absil
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