Recent Trend
Recent research highlights a surge in applying artificial intelligence, particularly deep learning models like transformers and graph neural networks, to analyze diverse data types, including conversations, satellite communications, time series, and images. Current efforts focus on improving model interpretability, addressing biases, and enhancing the efficiency of algorithms for tasks such as forecasting, trend identification, and knowledge extraction. This work is significant for advancing various fields, from improving business decision-making through conversation analysis to optimizing resource allocation in satellite communication and enhancing personalized education through data mining.
Papers
Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies
Kieran Wood, Samuel Kessler, Stephen J. Roberts, Stefan Zohren
A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead
Kamila Zaman, Alberto Marchisio, Muhammad Abdullah Hanif, Muhammad Shafique
Semi-automated extraction of research topics and trends from NCI funding in radiological sciences from 2000-2020
Mark Nguyen, Peter Beidler, Joseph Tsai, August Anderson, Daniel Chen, Paul Kinahan, John Kang
Inertial Navigation Meets Deep Learning: A Survey of Current Trends and Future Directions
Nadav Cohen, Itzik Klein
Recent Developments in Recommender Systems: A Survey
Yang Li, Kangbo Liu, Ranjan Satapathy, Suhang Wang, Erik Cambria