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Poster
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Mon 18:30
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Unsupervised Transformation Learning via Convex Relaxations
Tatsunori Hashimoto · Percy Liang · John Duchi
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Poster
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Tue 18:30
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Group Additive Structure Identification for Kernel Nonparametric Regression
Chao Pan · Michael Zhu
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Poster
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Tue 18:30
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Practical Data-Dependent Metric Compression with Provable Guarantees
Piotr Indyk · Ilya Razenshteyn · Tal Wagner
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Poster
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Mon 18:30
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Kernel Feature Selection via Conditional Covariance Minimization
Jianbo Chen · Mitchell Stern · Martin J Wainwright · Michael Jordan
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Poster
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Mon 18:30
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Deep Subspace Clustering Networks
Pan Ji · Tong Zhang · Hongdong Li · Mathieu Salzmann · Ian Reid
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Poster
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Mon 18:30
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Improved Graph Laplacian via Geometric Self-Consistency
Dominique Perrault-Joncas · Marina Meila · James McQueen
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Poster
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Mon 18:30
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Principles of Riemannian Geometry in Neural Networks
Michael Hauser · Asok Ray
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Poster
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Mon 18:30
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Learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued data
Stéphanie ALLASSONNIERE · Juliette Chevallier · Stephane Oudard
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Poster
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Mon 18:30
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Gaussian process based nonlinear latent structure discovery in multivariate spike train data
Anqi Wu · Nicholas Roy · Stephen Keeley · Jonathan Pillow
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Workshop
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Fri 9:00
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A Data-Driven Sparse-Learning Approach to Model Reduction in Chemical Reaction Networks
FARSHAD HARIRCHI
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Workshop
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Sat 14:45
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Learning Texture Manifolds with the Periodic Spatial GAN by Nikolay Jetchev , Zalando
Roland Vollgraf
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Workshop
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Sat 8:30
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Topological Data Analisys with GUDHI and scalable manifold learning and clustering with megaman
Vincent Rouvreau · Marina Meila
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