Towards Similarity Graphs Constructed by Deep Reinforcement Learning

Understand

Similarity graphs are an active research direction for the nearest neighbor search (NNS) problem.

• New algorithms for similarity graph construction are continuously being proposed and analyzed by both theoreticians and practitioners.
• However, existing construction algorithms are mostly based on heuristics and do not explicitly maximize the target performance measure, i.e., search recall.
• Therefore, at the moment it is not clear whether the performance of similarity graphs has plateaued or more effective graphs can be constructed with more theoretically grounded methods.