Ad-papers

Why we included this project

If you work on ad targeting, click-through rate prediction, or recommendations, this list is worth bookmarking. The papers are sorted into folders by subfield, like optimization, factorization machines, embeddings, deep learning CTR models, and bidding strategy, so you can skip to the part you care about. Each entry is a direct PDF with a one-line note on why the paper matters, which cuts down the time spent hunting for the right reading. The author also drops stale or off-topic papers and links to separate lists for RTB and recommender systems, making it a practical starting point for anyone new to computational advertising.