Complexity of Teaching by a Restricted Number of Examples

17 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Machine Teaching for Bayesian Learners in the Exponential Family (2013, background): “Our framework allows for probabilistic, noisy learners with infinite hypothesis space, arbitrary loss functions, and the notion of teaching effort.”
Teacher Improves Learning by Selecting a Training Subset (2018, background): “The theoretical study of machine teaching has focused on the teaching dimension, i.e. the minimum training set size needed to exactly teach a target concept θ ∗ [20, 38, 46, 18, 29, 45, 16, 44, 48, 9, 3, 4, 21, 31, 8, 7, 25, 5, 36, 23, 10].”
How Do Humans Teach: On Curriculum Learning and Teaching Dimension (2011, methodology): “The first thread, developed by the computational learning theory community, is exemplified by the “teaching dimension” model [9] and its extensions [12, 10, 1, 2, 11, 13, 18].”
The Teaching Dimension of Linear Learners (2015, background): “ Work Teaching dimension as a learning-theoretic quantity has attracted a long history of research. It was proposed independently in [13, 23]. Subsequent theoretical developments can be found in e.g. [26, 7, 2, 3, 14, 18, 6, 5, 17, 4, 22, 9, 12]. Most of them assume little extra knowledge on the lea”