deep learning

Time-series momentum portfolios with deep multi-task learning

Congratulations to Joel Ong on publishing our paper on using multi-task deep learning for porfolio construction in Expert Systems with Applications. The paper presents a new way to leverage time series momentum in a deep learning setting. Read a Twitter thread explaining the basics here.

Congrats to Abigail on finishing her PhD on deep learning for underwater communication

Abigail Leon has successfully defended her PhD today with main supervisor Prof. Yuen Chau and myself as co-supervisor. Abigail has successfully explored how deep learning techniques can be used to denoise en demodulate complex underwater acoustic communication signals, and has performed some sea-trials to gather data for this. Since the PhD is under an NDA with Thales, we cannot post it, however, check out some of Abigail's papers here (more to come after the review process ends).

New paper on Multimodal Deep Models for Predicting Affective Responses Evoked by Movies

Together with my PhD student Thao and Prof. Gemma Roig (MIT/Frankfurt University), a new paper was published on "Multimodal Deep Models for Predicting Affective Responses Evoked by Movies" in the Proceedings of the 2nd International Workshop on Computer Vision for Physiological Measurement as part of ICCV. Seoul, South Korea. 2019. A preprint is available here.

Editorial for Springer's Deep Learning for Music and Audio special issue

Prof. Ching-Hua Chuan and I recently edited a Special Issue for Springer's Neural Computing and Applications (IF: 4.213). The idea for the issue came out of the 1st International Workshop on Deep Learning for Music that we organized in Anchorage, US, as part of IJCNN in 2017. We received a nice collection of very interesting articles from scholars all over the world. The issue is set to come out soon (stay tuned).

Call for Papers: Special Issue on Deep Learning for Music and Audio in Springer’s Neural Computing and Applications

Special Issue on Deep Learning for Music and Audio
in Springer's Neural Computing and Applications (Impact factor: 2.50)

Submission deadline: December 17th

Description and covered topics

First workshop on deep learning and music in Anchorage (Proceedings available online)

This week (May 18-19th), I co-organized the workshop on deep learning for music with Prof. Ching-Hua Chuan in Anchorage, Alaska. The workshop was part of the International Joint Conference on Neural Networks (IJCNN) and featured invited speakers from Google Brain, A*STAR and Pandora.

Over 50 people participated in the workshop and there were some really interesting discussions on this exciting new field. The full Proceedings can be found online, and include: