Kirill Shevkunov

Relevance-Based Embeddings: Lightweight Candidate Selection via Heavy Ranker Calls

In many machine learning applications, the most relevant items for a query should be efficiently extracted. The relevance function is usually an expensive similarity model making the exhaustive search infeasible. A typical solution is to train another model that separately embeds queries and items t…