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cs.LG2024
On Reductions and Representations of Learning Problems in Euclidean Spaces
Bogdan Chornomaz, Shay Moran, Tom Waknine
Many practical prediction algorithms represent inputs in Euclidean space and replace the discrete 0/1 classification loss with a real-valued surrogate loss, effectively reducing cl…
cs.DM2024
Dual VC Dimension Obstructs Sample Compression by Embeddings
Zachary Chase, Bogdan Chornomaz, Steve Hanneke +2
This work studies embedding of arbitrary VC classes in well-behaved VC classes, focusing particularly on extremal classes. Our main result expresses an impossibility: such embeddin…