Folding: Why Good Models Sometimes Make Spurious Recommendations. - Doris Xin; Nicolas Mayoraz; Hubert Pham; Karthik Lakshmanan; John R. Anderson (RecSys, 2017)

Efficient Training on Very Large Corpora via Gramian Estimation. - Walid Krichene; Nicolas Mayoraz; Steffen Rendle; Li Zhang 001; Xinyang Yi; Lichan Hong; Ed H. Chi; John R. Anderson (ICLR (Poster), 2019)

Scaling Up Collaborative Filtering Data Sets through Randomized Fractal Expansions. - Francois Belletti; Karthik Lakshmanan; Walid Krichene; Nicolas Mayoraz; Yi-Fan Chen; John R. Anderson; Taylor Robie; Tayo Oguntebi; Dan Shirron; Amit Bleiwess (CoRR, 2019)

Rankmax: An Adaptive Projection Alternative to the Softmax Function. - Weiwei Kong; Walid Krichene; Nicolas Mayoraz; Steffen Rendle; Li Zhang 001 (NeurIPS, 2020)

Demonstrating Principled Uncertainty Modeling for Recommender Ecosystems with RecSim NG. - Martin Mladenov; Chih-Wei Hsu; Vihan Jain; Eugene Ie; Christopher Colby; Nicolas Mayoraz; Hubert Pham; Dustin Tran; Ivan Vendrov; Craig Boutilier (RecSys, 2020)

RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems. - Martin Mladenov; Chih-Wei Hsu; Vihan Jain; Eugene Ie; Christopher Colby; Nicolas Mayoraz; Hubert Pham; Dustin Tran; Ivan Vendrov; Craig Boutilier (CoRR, 2021)

Training Differentially Private Ad Prediction Models With Semi-Sensitive Features. - Lynn Chua; Qiliang Cui; Badih Ghazi; Charlie Harrison; Pritish Kamath; Walid Krichene; Ravi Kumar 001; Pasin Manurangsi; Nicolas Mayoraz; Hema Venkata Krishna Giri Narra; Steffen Rendle; Amer Sinha; et al. (AdKDD@KDD, 2024)

Private Learning with Public Features. - Walid Krichene; Nicolas Mayoraz; Steffen Rendle; Shuang Song 001; Abhradeep Thakurta; Li Zhang 001 (AISTATS, 2024)

Successive Halving with Learning Curve Prediction via Latent Kronecker Gaussian Processes. - Jihao Andreas Lin; Nicolas Mayoraz; Steffen Rendle; Dima Kuzmin; Emil Praun; Berivan Isik (CoRR, 2025)