题目： What’s the insight of self-paced learning
报告人： 孟德宇 博士 西安交通大学
摘要： Self-paced learning (SPL) is a recently proposed learning regime inspired by the learning process of humans and animals that gradually incorporates easy to more complex samples into training. While several easy SPL implementation strategies have been proposed, it is still short of a general paradigm for guiding the construction of rational SPL learning regimes targeting specific applications. To resolve this problem, we provide an axiom for insightfully formulating the underlying principles of self-paced learning. This axiomatic understanding not only involves the previous SPL learning schemes as its special cases, but also can be utilized to extend a series of new SPL implementation regimes based on certain application aims. In the recent two years, we have constructed several SPL realizations, including SPaR, SPLD, SPCL, SPMF, based on this axiom, and achieved the best performance in several known benchmark datasets, e.g., Web Query, Hollywood2, and Olympic Sports. Especially, this paradigm has been integrated into the system developed by CMU Informedia team, and achieved the leading performance in challenging semantic query (SQ)/000Ex tasks of the TRECVID MED/MER competition organized by NIST in 2014.