Pages that link to "Item:Q1314506"
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The following pages link to Bounds on the sample complexity of Bayesian learning using information theory and the VC dimension (Q1314506):
Displaying 16 items.
- Rigorous learning curve bounds from statistical mechanics (Q676243) (← links)
- VC dimension and inner product space induced by Bayesian networks (Q962917) (← links)
- QG/GA: a stochastic search for Progol (Q1009231) (← links)
- Sample size lower bounds in PAC learning by Algorithmic Complexity Theory (Q1274920) (← links)
- Sphere packing numbers for subsets of the Boolean \(n\)-cube with bounded Vapnik-Chervonenkis dimension (Q1345876) (← links)
- Characterizing rational versus exponential learning curves (Q1370864) (← links)
- Mutual information, metric entropy and cumulative relative entropy risk (Q1383090) (← links)
- Sample complexity of model-based search (Q1567400) (← links)
- Bayesian predictiveness, exchangeability and sufficientness in bacterial taxonomy (Q1602623) (← links)
- Query by committee, linear separation and random walks. (Q1603591) (← links)
- Bounds on the minimax rate for estimating a prior over a VC class from independent learning tasks (Q1704568) (← links)
- Learning from a population of hypotheses (Q1900976) (← links)
- Entropy bounds on Bayesian learning (Q2468506) (← links)
- Learning a priori constrained weighted majority votes (Q2512901) (← links)
- MetaBayes: Bayesian Meta-Interpretative Learning Using Higher-Order Stochastic Refinement (Q2943874) (← links)
- Improved bounds on the sample complexity of learning (Q5943102) (← links)
