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Workshop
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Towards A Scalable Solution for Compositional Multi-Group Fair Classification
James Atwood · Tina Tian · Ben Packer · Meghana Deodhar · Jilin Chen · Alex Beutel · Flavien Prost · Ahmad Beirami
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Workshop
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PIAT: Parameter Interpolation based Adversarial Training for Image Classification
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Workshop
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A Simple and Yet Fairly Effective Defense for Graph Neural Networks
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Workshop
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PIAT: Parameter Interpolation based Adversarial Training for Image Classification
Kun He · Xin Liu · Yichen Yang · Zhou Qin · Weigao Wen · Hui Xue' · John Hopcroft
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Workshop
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Characterizing the Optimal 0−1 Loss for Multi-class Classification with a Test-time Attacker
Sophie Dai · Wenxin Ding · Arjun Nitin Bhagoji · Daniel Cullina · Ben Zhao · Heather Zheng · Prateek Mittal
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Workshop
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Neural Collapse in the Intermediate Hidden Layers of Classification Neural Networks
Liam Parker
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Workshop
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Active learning for time instant classification
Nauman Ahad · Namrata Nadagouda · Eva Dyer · Mark Davenport
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Workshop
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Fri 14:10
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An Exact Kernel Equivalence for Finite Classification Models
Brian Bell · Michael Geyer · David Glickenstein · Amanda Fernandez · Juston Moore
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Workshop
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Using Synthetic Data for Data Augmentation to Improve Classification Accuracy
Yongchao Zhou · Hshmat Sahak · Jimmy Ba
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Workshop
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Training on Thin Air: Improve Image Classification with Generated Data
Yongchao Zhou · Hshmat Sahak · Jimmy Ba
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Workshop
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Point Cloud Classification with ModelNet40: What is left?
Jarne Van den Herrewegen · Tom Tourwé · Francis Wyffels
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Workshop
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Decoupled Graph Label Denoising for Robust Semi-Supervised Node Classification
Kaize Ding · Yancheng Wang · Huan Liu
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