Pages that link to "Item:Q1916527"
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The following pages link to General bounds on the number of examples needed for learning probabilistic concepts (Q1916527):
Displaying 11 items.
- Learning distributions by their density levels: A paradigm for learning without a teacher (Q1370866) (← links)
- Strong minimax lower bounds for learning (Q1383192) (← links)
- On the value of partial information for learning from examples (Q1383444) (← links)
- A general lower bound on the number of examples needed for learning (Q1823011) (← links)
- Improved lower bounds for learning from noisy examples: An information-theoretic approach (Q1854425) (← links)
- Some connections between learning and optimization (Q1885804) (← links)
- Efficient algorithms for learning functions with bounded variation (Q1887165) (← links)
- PAC-learning in the presence of one-sided classification~noise (Q2254605) (← links)
- Exact lower bounds for the agnostic probably-approximately-correct (PAC) machine learning model (Q2328061) (← links)
- (Q4614114) (← links)
- (Q4633018) (← links)
