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MLIC: A MaxSAT-Based Framework for Learning Interpretable Classification Rules.

, and . CP, volume 11008 of Lecture Notes in Computer Science, page 312-327. Springer, (2018)

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Networking sensors using belief propagation., , and . Allerton, page 384-391. IEEE, (2008)Approximating the Spectral Sums of Large-scale Matrices using Chebyshev Approximations., , , and . CoRR, (2016)MLIC: A MaxSAT-Based Framework for Learning Interpretable Classification Rules., and . CP, volume 11008 of Lecture Notes in Computer Science, page 312-327. Springer, (2018)Iterative log thresholding., and . ICASSP, page 7198-7202. IEEE, (2014)Efficient Learning of Interpretable Classification Rules., , and . CoRR, (2022)Convex Total Least Squares., and . CoRR, (2014)Introduction to the Issue on Financial Signal Processing and Machine Learning for Electronic Trading., , , , and . IEEE J. Sel. Top. Signal Process., 10 (6): 979-981 (2016)Classification Rules in Relaxed Logical Form., , and . ECAI, volume 325 of Frontiers in Artificial Intelligence and Applications, page 2489-2496. IOS Press, (2020)Approximating Spectral Sums of Large-Scale Matrices using Stochastic Chebyshev Approximations., , , and . SIAM J. Sci. Comput., (2017)Large-scale log-determinant computation through stochastic Chebyshev expansions., , and . ICML, volume 37 of JMLR Workshop and Conference Proceedings, page 908-917. JMLR.org, (2015)