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LLMs can drive significant gains in ad systems, not just as rankers or retrievers, but as complementary predictors that forecast likely advertisers from user profiles.
Neural networks can turbocharge classical optimization for high-dimensional matrix estimation, achieving faster convergence without sacrificing theoretical guarantees.
