Discovered public repositories for hongyusu in the GitHub catalog.
http://hongyusu.github.io/Dissertation/ Doctoral thesis titled 'Multilabel classification through structured output learning - methods and applications'. The thesis summarizes the research carried out during 2011.1 to 2014.12 in Helsinki Institute for Information Technology HIIT, Department of Computer Science in Aalto University. Some of the research has been done in Department of Computer in University of Helsinki during the year 2011.
The repository contains codes and some experimental data for Structured Prediction of Network Response (SPIN) algorithm, which appears in International Conference on Machine Learning (ICML 2014). The algorithm assumes a network structure as prior (e.g. Facebook) and a set of actions (e.g. posts or messages) performed on the network. Given a new action, the algorithm predicts the response network, a DAG, that indicates activated nodes and activation order.
The repository contains codes and some experimental data for Random Tree Approximation (RTA) algorithm, which appears in Advances in Neural Information Processing System (NIPS 2014). The algorithm is designed for multilabel classification when the output graph is not known apriori. It performs Max-margin Learning on a collection of random spanning trees sample from a complete graph connecting multiple labels. RTA also lays the foundation of performing inference on any unknown graph structures.
Codes for multilabel classification with random output graph ensemble, appears in ACML 2013. The package contains codes for average-max-marginal aggregation (AMM) and maximal-average-marginal aggregation (MAM).
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