Tom Arjannikov

According to our database, Tom Arjannikov authored at least 12 papers between 2013 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Positive unlabeled learning applications in music and healthcare.

Tom Arjannikov

PhD thesis, 2021

An Empirical Investigation of PU Learning for Predicting Length of Stay.

Tom Arjannikov, George Tzanetakis

Proceedings of the 9th IEEE International Conference on Healthcare Informatics, 2021

Cold-Start Hospital Length of Stay Prediction Using Positive-Unlabeled Learning.

Tom Arjannikov, George Tzanetakis

Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics, 2021

2020

Corrections to "A Social Crowdsourcing Community Case Study: Interaction Patterns, Evolution, and Factors That Affect Them".

Khobaib Zaamout, Tom Arjannikov, Ken Barker

IEEE Trans. Comput. Soc. Syst., 2020

A Social Crowdsourcing Community Case Study: Interaction Patterns, Evolution, and Factors That Affect Them.

Khobaib Zaamout, Tom Arjannikov, Ken Barker

IEEE Trans. Comput. Soc. Syst., 2020

2017

Histogram-Based Asymmetric Relabeling for Learning from Only Positive and Unlabeled Data.

Tom Arjannikov, George Tzanetakis

Proceedings of the 16th IEEE International Conference on Machine Learning and Applications, 2017

Using Markov Chains to Model Sensor Network Reliability.

Tom Arjannikov, Simon Diemert, Sudhakar Ganti, Chloe Lampman, Edward C. Wiebe

Proceedings of the 12th International Conference on Availability, Reliability and Security, Reggio Calabria, Italy, August 29, 2017

2016

Do Nested Dichotomies Help in Automatic Music Genre Classification? An Empirical Study.

Tom Arjannikov, John Z. Zhang

Proceedings of the 2016 International Computer Music Conference, 2016

Bi-Modal Deep Boltzmann Machine Based Musical Emotion Classification.

Moyuan Huang, Wenge Rong, Tom Arjannikov, Nan Jiang, Zhang Xiong

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016

2015

An Empirical Study on Structured Dichotomies in Music Genre Classification.

Tom Arjannikov, John Z. Zhang

Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

2014

An Association-based Approach to Genre Classification in Music.

Tom Arjannikov, John Z. Zhang

Proceedings of the 15th International Society for Music Information Retrieval Conference, 2014

2013

Verifying Music Tag Annotation Via Association Analysis.

Tom Arjannikov, Chris Sanden, John Z. Zhang

Proceedings of the 14th International Society for Music Information Retrieval Conference, 2013