Abstract: Matrix factorization is a fundamental characterization model in machine learning and is usually solved using mathematical decomposition reconstruction loss. However, matrix factorization is ...
Abstract: This article presents a powerful algorithmic framework for big data optimization, called the block successive upper-bound minimization (BSUM). The BSUM includes as special cases many ...
PANOPLY is a platform for applying state-of-the-art statistical and machine learning algorithms to transform multi-omic data from cancer samples into biologically meaningful and interpretable results.
AMD and Intel have now published a full technical specification for ACE — AI Compute Extensions — the most significant overhaul to x86 AI compute in the architecture's history, co-authored by eight ...
A production-shaped recommender: stage 1 retrieves candidates with matrix-factorization embeddings, stage 2 re-ranks them with a LightGBM model on richer features. Evaluated offline with Recall@k / ...
BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
Buy-in-Bulk Active Learning. Liu Yang and Jaime Carbonell. Advances in Neural Information Processing Systems 26 (NIPS), 2013. Liu Yang, Avrim Blum and Jaime Carbonell. Learnability of DNF with ...
Department of Chemistry, School of Natural Science, Ulsan National Institute of Science and Technology (UNIST), 50 UNIST-gil, Ulsan 44919, Republic of Korea Article Views are the COUNTER-compliant sum ...
ICML, Fast $ (1+\varepsilon)$-Approximation Algorithms for Binary Matrix Factorization Full version on arXiv with Ameya Velingker, Maximilian Votsch, and Samson Zhou ICML, Sharper Bounds for $\ell_p$ ...
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