Learning Program Embeddings to Propagate Feedback on Student Code
Cites background from "Learning Program Embeddings to Prop..."
... Syntax + State Student Feedback Distributed Student Feedback...
Cites methods from "Learning Program Embeddings to Prop..."
...Piech et al. (2015) proposed a neural network based approach to find program representations and used them for automatically propagating instructor feedback to students in a massive course....
...Learning rates are set using Adagrad (Duchi et al., 2011)....
"Learning Program Embeddings to Prop..." refers methods in this paper
...We use random search (Bergstra & Bengio, 2012) to optimize over hyperparameters (e.g, regularization parameters, matrix dimensions, and minibatch size)....
"Learning Program Embeddings to Prop..." refers background or methods in this paper
...The programs for these assignments operate in maze worlds where an agent can move, turn, and test for conditions of its current location....
...Our models are related to recent work from the NLP and deep learning communities on recursive neural networks, particularly for modeling semantics in sentences or symbolic expressions (Socher et al., 2013; 2011; Zaremba et al., 2014; Bowman, 2013)....
...…on recursive neural networks (called the NPM-RNN model) in which we parametrize a matrix MA in this new model with an RNN whose architecture follows the abstract syntax tree (similar to the way in which RNN architectures might take the form of a parse tree in an NLP setting (Socher et al., 2013))....