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The Common-directions Method for Regularized Empirical Risk Minimization.

, , and . J. Mach. Learn. Res., (2019)

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Novel Models and Ensemble Techniques to Discriminate Favorite Items from Unrated Ones for Personalized Music Recommendation., , , , , , , , , and 15 other author(s). KDD Cup, volume 18 of JMLR Proceedings, page 101-135. JMLR.org, (2012)Taming the One-Epoch Phenomenon in Online Recommendation System by Two-stage Contrastive ID Pre-training., , , and . RecSys, page 838-840. ACM, (2024)Limited-memory Common-directions Method for Distributed Optimization and its Application on Empirical Risk Minimization., , , and . SDM, page 732-740. SIAM, (2017)Limited-memory common-directions method for large-scale optimization: convergence, parallelization, and distributed optimization., , and . Math. Program. Comput., 14 (3): 543-591 (2022)SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver, , , and . (2019)cite arxiv:1905.12149Comment: Accepted at ICML'19. The code can be found at https://github.com/locuslab/satnet.TransAct: Transformer-based Realtime User Action Model for Recommendation at Pinterest., , , , , , , , , and . KDD, page 5249-5259. ACM, (2023)Learning and Reasoning with Fast Semidefinite Programming and Mixing Methods.. Carnegie Mellon University, USA, (2022)Polynomial Optimization Methods for Matrix Factorization., , and . AAAI, page 2710-2717. AAAI Press, (2017)Outlier-Efficient Hopfield Layers for Large Transformer-Based Models., , , , , , and . ICML, OpenReview.net, (2024)A Linear Ensemble of Individual and Blended Models for Music Rating Prediction., , , , , , , , , and 15 other author(s). KDD Cup, volume 18 of JMLR Proceedings, page 21-60. JMLR.org, (2012)