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Found 9 papers, 4 papers with code
Transfer Learning in Conversational Analysis through Reusing Preprocessing Data as Supervisors
Conversational analysis systems are trained using noisy human labels and often require heavy preprocessing during multi-modal feature extraction.
ast2vec: Utilizing Recursive Neural Encodings of Python Programs
Educational datamining involves the application of datamining techniques to student activity.
MONAH: Multi-Modal Narratives for Humans to analyze conversations
In conversational analyses, humans manually weave multimodal information into the transcripts, which is significantly time-consuming.
Reusing Preprocessing Data as Auxiliary Supervision in Conversational Analysis
Using noisy labels in single-task learning increases the risk of over-fitting.
Recursive Tree Grammar Autoencoders
Machine learning on trees has been mostly focused on trees as input to algorithms.
DETECT: A Hierarchical Clustering Algorithm for Behavioural Trends in Temporal Educational Data
Techniques for clustering student behaviour offer many opportunities to improve educational outcomes by providing insight into student learning.
Tree Echo State Autoencoders with Grammars
Tree data occurs in many forms, such as computer programs, chemical molecules, or natural language.
Detecting depression in dyadic conversations with multimodal narratives and visualizations
We demonstrate the ability of our system to take in a wide range of multimodal information and automatically generated a prediction score for the depression state of the individual.
A Survey of Automated Programming Hint Generation -- The HINTS Framework
Using this insight, it presents a simple framework for describing such techniques, the Hint Iteration by Narrow-down and Transformation Steps (HINTS) framework, and it surveys recent work in the context of this framework.
