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ORCIDDmitry Malioutov
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2020 – today
- 2022
[j4]Bishwamittra Ghosh
, Dmitry Malioutov, Kuldeep S. Meel:
Efficient Learning of Interpretable Classification Rules. J. Artif. Intell. Res. 74: 1823-1863 (2022)- [i5]Bishwamittra Ghosh, Dmitry Malioutov, Kuldeep S. Meel:
Efficient Learning of Interpretable Classification Rules. CoRR abs/2205.06936 (2022) - 2020
- [c12]Bishwamittra Ghosh, Dmitry Malioutov, Kuldeep S. Meel:
Classification Rules in Relaxed Logical Form. ECAI 2020: 2489-2496
2010 – 2019
- 2018
- [c11]Dmitry Malioutov, Kuldeep S. Meel:
MLIC: A MaxSAT-Based Framework for Learning Interpretable Classification Rules. CP 2018: 312-327 - [i4]Dmitry Malioutov, Kuldeep S. Meel:
MLIC: A MaxSAT-Based framework for learning interpretable classification rules. CoRR abs/1812.01843 (2018) - 2017
- [j3]Raimo Bakis, Daniel P. Connors, Parijat Dube, Pavan Kapanipathi, Abhishek Kumar, Dmitry Malioutov, Chitra Venkatramani:
Performance of natural language classifiers in a question-answering system. IBM J. Res. Dev. 61(4-5): 14:1-14:10 (2017) - [j2]Insu Han, Dmitry Malioutov, Haim Avron, Jinwoo Shin:
Approximating Spectral Sums of Large-Scale Matrices using Stochastic Chebyshev Approximations. SIAM J. Sci. Comput. 39(4) (2017) - 2016
- [j1]Ali N. Akansu, Dmitry Malioutov, Daniel P. Palomar, Emmanuelle Jay, Danilo P. Mandic:
Introduction to the Issue on Financial Signal Processing and Machine Learning for Electronic Trading. IEEE J. Sel. Top. Signal Process. 10(6): 979-981 (2016) - [c10]Ian En-Hsu Yen, Dmitry Malioutov, Abhishek Kumar:
Scalable Exemplar Clustering and Facility Location via Augmented Block Coordinate Descent with Column Generation. AISTATS 2016: 1260-1269 - [c9]Dmitry Malioutov, Abhishek Kumar, Ian En-Hsu Yen:
Large-scale Submodular Greedy Exemplar Selection with Structured Similarity Matrices. UAI 2016 - [i3]Insu Han, Dmitry Malioutov, Haim Avron, Jinwoo Shin:
Approximating the Spectral Sums of Large-scale Matrices using Chebyshev Approximations. CoRR abs/1606.00942 (2016) - 2015
- [c8]Insu Han, Dmitry Malioutov, Jinwoo Shin:
Large-scale log-determinant computation through stochastic Chebyshev expansions. ICML 2015: 908-917 - [i2]Insu Han, Dmitry Malioutov, Jinwoo Shin:
Large-scale Log-determinant Computation through Stochastic Chebyshev Expansions. CoRR abs/1503.06394 (2015) - 2014
- [c7]Dmitry Malioutov, Aleksandr Y. Aravkin:
Iterative log thresholding. ICASSP 2014: 7198-7202 - [c6]Dmitry Malioutov, Nikolai Slavov:
Convex Total Least Squares. ICML 2014: 109-117 - [i1]Dmitry Malioutov, Nikolai Slavov:
Convex Total Least Squares. CoRR abs/1406.0189 (2014) - 2013
- [c5]Christos Boutsidis, Dmitry Malioutov:
Equity factor analysis via column subset selection. GlobalSIP 2013: 1131 - [c4]Dmitry Malioutov:
Beyond PCA for modeling financial time-series. GlobalSIP 2013: 1140
2000 – 2009
- 2008
- [c3]Sujay Sanghavi, Dmitry Malioutov, Alan S. Willsky:
Networking sensors using belief propagation. Allerton 2008: 384-391 - 2006
- [c2]Emin Martinian, Anthony Vetro, Jonathan S. Yedidia, João Ascenso, Ashish Khisti, Dmitry Malioutov:
Hybrid Distributed Video Coding Using SCA Codes. MMSP 2006: 258-261 - 2004
- [c1]Johnny Chen, Ashish Khisti, Dmitry Malioutov, Jonathan S. Yedidia:
Distributed source coding using serially-concatenated-accumulate codes. ITW 2004: 209-214
Coauthor Index
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