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Poster
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Tue 9:00
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Approximate Euclidean lengths and distances beyond Johnson-Lindenstrauss
Aleksandros Sobczyk · Mathieu Luisier
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Poster
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Wed 9:00
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Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations
Alexander Immer · Tycho van der Ouderaa · Gunnar Rätsch · Vincent Fortuin · Mark van der Wilk
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Poster
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Wed 14:00
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A Single-timescale Analysis for Stochastic Approximation with Multiple Coupled Sequences
Han Shen · Tianyi Chen
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Poster
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Chromatic Correlation Clustering, Revisited
Qing Xiu · Kai Han · Jing Tang · Shuang Cui · He Huang
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Poster
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Tue 9:00
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Instance-Dependent Near-Optimal Policy Identification in Linear MDPs via Online Experiment Design
Andrew Wagenmaker · Kevin Jamieson
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Poster
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Thu 14:00
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Efficient Dataset Distillation using Random Feature Approximation
Noel Loo · Ramin Hasani · Alexander Amini · Daniela Rus
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Poster
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Wed 9:00
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Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap
Luca Pesce · Bruno Loureiro · Florent Krzakala · Lenka Zdeborová
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Poster
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Tue 14:00
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Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post Hoc Explanations
Tessa Han · Suraj Srinivas · Himabindu Lakkaraju
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Poster
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Thu 9:00
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Theoretically Provable Spiking Neural Networks
Shao-Qun Zhang · Zhi-Hua Zhou
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Poster
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Thu 9:00
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Recruitment Strategies That Take a Chance
Gregory Kehne · Ariel Procaccia · Jingyan Wang
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Poster
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Tue 14:00
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Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources
Peter Lippmann · Enrique Fita Sanmartín · Fred Hamprecht
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Poster
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Thu 9:00
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On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC)
Washim Mondal · Mridul Agarwal · Vaneet Aggarwal · Satish Ukkusuri
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