Machine Learning and Optimization Problems: Applications and Exploration

This technical salon, hosted by Meitu Technology, focuses on the application and exploration of machine learning and optimization problems. Meitu, a mobile internet company with billions of users, has applied AI and optimization algorithms across various scenarios to enhance data objectives and user experience. With the rapid advancement of deep learning in visual domains, the company is rethinking the "deepening" of information retrieval.

The event features three main topics:

1. Meitu's Personalized Deep Ranking Model : This presentation introduces how to optimize deep ranking models to build low-latency personalized services. The model is both "deep" and "fast," capable of understanding user behavior patterns while ensuring efficient inference and avoiding unreasonable response delays.

2. Meitu's Video Clustering Practice : This topic discusses how Meitu uses user click and playback behaviors to cluster video content, breaking the limitations of visual content understanding and discovering non-manually summarized classification knowledge to enhance personalized recommendations.

3. Application of Data Structures in Optimization Problems : This presentation explores how data structures can accelerate the solution process in optimization problems, using two commercial cases to introduce common optimization problems and solutions, and proposing new objective functions from an economic perspective.

The event also includes an agenda with registration, three technical sessions with Q&A, and networking opportunities. It is scheduled for June 9, 2018, in Xiamen, targeting mid-to-senior R&D and algorithm engineers from various enterprises.