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Poster
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Wed 16:30
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Inverse M-Kernels for Linear Universal Approximators of Non-Negative Functions
Hideaki Kim
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Poster
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Thu 16:30
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Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines
Edward Milsom · Ben Anson · Laurence Aitchison
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Workshop
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Toward Understanding How the Data Affects Neural Collapse: A Kernel-Based Approach
Vignesh Kothapalli · Tom Tirer
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Workshop
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Emergence in non-neural models: grokking modular arithmetic via average gradient outer product
Neil Mallinar · Daniel Beaglehole · Libin Zhu · Adityanarayanan Radhakrishnan · Parthe Pandit · Misha Belkin
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Poster
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Wed 11:00
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Supervised Kernel Thinning
Albert Gong · Kyuseong Choi · Raaz Dwivedi
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Poster
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Thu 16:30
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Efficient Convex Algorithms for Universal Kernel Learning
Aleksandr Talitckii · Brendon Colbert · Matthew Peet
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Poster
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Fri 16:30
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A Kernel Perspective on Distillation-based Collaborative Learning
Sejun Park · Kihun Hong · Ganguk Hwang
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Poster
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Wed 16:30
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The Minimax Rate of HSIC Estimation for Translation-Invariant Kernels
Florian Kalinke · Zoltan Szabo
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Poster
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Wed 16:30
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Learning to Embed Distributions via Maximum Kernel Entropy
Oleksii Kachaiev · Stefano Recanatesi
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Poster
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Fri 11:00
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Dense Associative Memory Through the Lens of Random Features
Benjamin Hoover · Duen Horng Chau · Hendrik Strobelt · Parikshit Ram · Dmitry Krotov
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Poster
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Thu 11:00
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Entrywise error bounds for low-rank approximations of kernel matrices
Alexander Modell
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Poster
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Fri 16:30
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Statistical and Geometrical properties of the Kernel Kullback-Leibler divergence
Anna Korba · Francis Bach · Clémentine CHAZAL
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