Verifying Music Tag Annotation Via Association Analysis. - Tom Arjannikov; Chris Sanden; John Z. Zhang (ISMIR, 2013)

An Association-based Approach to Genre Classification in Music. - Tom Arjannikov; John Z. Zhang (ISMIR, 2014)

An Empirical Study on Structured Dichotomies in Music Genre Classification. - Tom Arjannikov; John Z. Zhang (ICMLA, 2015)

Bi-Modal Deep Boltzmann Machine Based Musical Emotion Classification. - Moyuan Huang; Wenge Rong; Tom Arjannikov; Nan Jiang 010; Zhang Xiong 001 (ICANN (2), 2016)

Do Nested Dichotomies Help in Automatic Music Genre Classification? An Empirical Study. - Tom Arjannikov; John Z. Zhang (ICMC, 2016)

Using Markov Chains to Model Sensor Network Reliability. - Tom Arjannikov; Simon Diemert; Sudhakar Ganti; Chloe Lampman; Edward C. Wiebe (ARES, 2017)

Histogram-Based Asymmetric Relabeling for Learning from Only Positive and Unlabeled Data. - Tom Arjannikov; George Tzanetakis (ICMLA, 2017)

A Social Crowdsourcing Community Case Study: Interaction Patterns, Evolution, and Factors That Affect Them. - Khobaib Zaamout; Tom Arjannikov; Ken Barker 001 (IEEE Trans. Comput. Soc. Syst., 2020)

Corrections to "A Social Crowdsourcing Community Case Study: Interaction Patterns, Evolution, and Factors That Affect Them". - Khobaib Zaamout; Tom Arjannikov; Ken Barker 001 (IEEE Trans. Comput. Soc. Syst., 2020)

Cold-Start Hospital Length of Stay Prediction Using Positive-Unlabeled Learning. - Tom Arjannikov; George Tzanetakis (BHI, 2021)

An Empirical Investigation of PU Learning for Predicting Length of Stay. - Tom Arjannikov; George Tzanetakis (ICHI, 2021)

Positive unlabeled learning applications in music and healthcare. - Tom Arjannikov (2021)