Biblio
] Filters: Author is Dmitry Bogdanov [Clear All Filters]
(2019). The MTG-Jamendo Dataset for Automatic Music Tagging.
Machine Learning for Music Discovery Workshop, International Conference on Machine Learning (ICML 2019). Abstract
(2019). The AcousticBrainz Genre Dataset: Multi-Source, Multi-Level, Multi-Label, and Large-Scale.
20th International Society for Music Information Retrieval Conference (ISMIR 2019). Abstract
(2019). Skip prediction using boosting trees based on acoustic features of tracks in sessions.
WSDM Cup Workshop 2019. Abstract
(2018). MediaEval 2018 AcousticBrainz Genre Task: A baseline combining deep feature embeddings across datasets.
MediaEval 2018 Workshop.
(2018). The MediaEval 2018 AcousticBrainz Genre Task: Content-based Music Genre Recognition from Multiple Sources.
MediaEval 2018 Workshop. Abstract
(2018). Automatic playlist continuation using a hybrid recommender system combining features from text and audio.
Workshop on the RecSys Challenge 2018. Abstract
(2018). Using offline metrics and user behavior analysis to combine multiple systems for music recommendation.
RecSys 2018 Workshop on Offline Evaluation of Recommender Systems. Abstract
(2017). Freesound Datasets: A Platform for the Creation of Open Audio Datasets.
18th International Society for Music Information Retrieval Conference. Abstract
(2017). Quantifying music trends and facts using editorial metadata from the Discogs database.
18th International Society for Music Information Retrieval Conference (ISMIR 2017). 89-95. Abstract
(2017). Acoustic scene classification by ensembling gradient boosting machine and convolutional neural networks.
Workshop on Detection and Classification of Acoustic Scenes and Events. Abstract
(2017). The MediaEval 2017 AcousticBrainz Genre Task: Content-based Music Genre Recognition from Multiple Sources.
MediaEval 2017 Workshop. Abstract
(2016). Cross-collection evaluation for music classification tasks.
17th International Society for Music Information Retrieval Conference (ISMIR 2016). Abstract
(2016). Mining metadata from the web for AcousticBrainz.
3rd International Digital Libraries for Musicology workshop. 53-56. Abstract
(2015). AcousticBrainz: a community platform for gathering music information obtained from audio.
16th International Society for Music Information Retrieval Conference (ISMIR 2015). 786-792. Abstract
(2015). Music Recommender Systems.
Recommender Systems Handbook. 453-492. Abstract
(2015). Taming wild horses with Essentia Music Extractor.
International Society for Music Information Retrieval Conference (ISMIR 2015). Late Breaking Demo. Abstract
(2014). What is the Effect of Audio Quality on the Robustness of MFCCs and Chroma Features?.
15th International Society for Music Information Retrieval Conference. 573-578. Abstract
(2014). ESSENTIA: an open source library for audio analysis.
ACM SIGMM Records. 6(1), Abstract
(2013). ESSENTIA: an Open-Source Library for Sound and Music Analysis.
ACM International Conference on Multimedia (MM'13). 855-858. Abstract
(2013). From music similarity to music recommendation: Computational approaches based on audio features and metadata.
Department of Information and Communication Technologies. 227.
(2013). ESSENTIA: an Audio Analysis Library for Music Information Retrieval.
International Society for Music Information Retrieval Conference (ISMIR'13). 493-498. Abstract
(2013). Semantic audio content-based music recommendation and visualization based on user preference examples.
Information Processing & Management. 49(1), 13-33. Abstract
(2012). Taking Advantage of Editorial Metadata to Recommend Music.
9th International Symposium on Computer Music Modeling and Retrieval (CMMR). 618-632. Abstract
(2012). Music Retagging Using Label Propagation and Robust Principal Component Analysis.
21st International World Wide Web Conference (WWW 2012): 4th International Workshop on Advances in Music Information Research (AdMIRe 2012). Abstract
