With chain-of-thought supervision, the PAC sample complexity is roughly d divided by the CoT information, which can be much larger than the target error epsilon.
Some Local Measures of Complexity of Convex Hulls and Generalization Bounds
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
We investigate measures of complexity of function classes based on continuity moduli of Gaussian and Rademacher processes. For Gaussian processes, we obtain bounds on the continuity modulus on the convex hull of a function class in terms of the same quantity for the class itself. We also obtain new bounds on generalization error in terms of localized Rademacher complexities. This allows us to prove new results about generalization performance for convex hulls in terms of characteristics of the base class. As a byproduct, we obtain a simple proof of some of the known bounds on the entropy of convex hulls.
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2025 1verdicts
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CoT Information: Improved Sample Complexity under Chain-of-Thought Supervision
With chain-of-thought supervision, the PAC sample complexity is roughly d divided by the CoT information, which can be much larger than the target error epsilon.