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Proceedings of The IEEE : Vol. 104, No. 1, January 2016

By Et.all E. Gabrilovich V. Tresp K. Murphy M. Nickel


1. A Review of Relation Machine Learning for Knowledge Graphs / M. Nickel, et al. 2. Learning to Hash for Indexing Big Data - A Survey / J. Wang, et al. 3. Implementing Randomized Matrix Algorithms in Parallel and Distributed Environments / J. Yang, et al. 4. Foundational Principles for Large-Scale Inference : Illustrations Through Correlation Mining / A. O. Hero, et al. 5. Resource Allocation for Statistical Estimation / Q. Berthet, et al. 6. Magging: Maximin Aggregation for Inhomogeneous Large-Scale Data / P. Buhlmann, et al. 7. Learning Reductions That Really Work / Beygelimer, et al. 8. Taking the Human Out of the Loop: A Review of Bayesian Optimization / B. Shahriari, et al. 9. Machine Learning in Genomic Medicine: A Review of Computational Problems and Data Sets / M. K. K. Leung, et al

Publisher: IEEE (Institute of Electrical and Electronics Engineers)
Year: 2016
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Provided by: Open Library
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