Distributed source coding using serially-concatenated-accumulate codes. - Johnny Chen; Ashish Khisti; Dmitry Malioutov; Jonathan S. Yedidia (ITW, 2004)

Hybrid Distributed Video Coding Using SCA Codes. - Emin Martinian; Anthony Vetro; Jonathan S. Yedidia; João Ascenso; Ashish Khisti; Dmitry Malioutov (MMSP, 2006)

Networking sensors using belief propagation. - Sujay Sanghavi; Dmitry Malioutov; Alan S. Willsky (Allerton, 2008)

Equity factor analysis via column subset selection. - Christos Boutsidis; Dmitry Malioutov (GlobalSIP, 2013)

Beyond PCA for modeling financial time-series. - Dmitry Malioutov (GlobalSIP, 2013)

Iterative log thresholding. - Dmitry Malioutov; Aleksandr Y. Aravkin (ICASSP, 2014)

Convex Total Least Squares. - Dmitry Malioutov; Nikolai Slavov (ICML, 2014)

Large-scale log-determinant computation through stochastic Chebyshev expansions. - Insu Han; Dmitry Malioutov; Jinwoo Shin (ICML, 2015)

Scalable Exemplar Clustering and Facility Location via Augmented Block Coordinate Descent with Column Generation. - Ian En-Hsu Yen; Dmitry Malioutov; Abhishek Kumar 001 (AISTATS, 2016)

Large-scale Submodular Greedy Exemplar Selection with Structured Similarity Matrices. - Dmitry Malioutov; Abhishek Kumar 001; Ian En-Hsu Yen (UAI, 2016)

Approximating the Spectral Sums of Large-scale Matrices using Chebyshev Approximations. - Insu Han; Dmitry Malioutov; Haim Avron; Jinwoo Shin (CoRR, 2016)

Introduction to the Issue on Financial Signal Processing and Machine Learning for Electronic Trading. - Ali N. Akansu; Dmitry Malioutov; Daniel P. Palomar; Emmanuelle Jay; Danilo P. Mandic (IEEE J. Sel. Top. Signal Process., 2016)

Performance of natural language classifiers in a question-answering system. - Raimo Bakis; Daniel P. Connors; Parijat Dube; Pavan Kapanipathi; Abhishek Kumar 001; Dmitry Malioutov; Chitra Venkatramani (IBM J. Res. Dev., 2017)

Approximating Spectral Sums of Large-Scale Matrices using Stochastic Chebyshev Approximations. - Insu Han; Dmitry Malioutov; Haim Avron; Jinwoo Shin (SIAM J. Sci. Comput., 2017)

MLIC: A MaxSAT-Based Framework for Learning Interpretable Classification Rules. - Dmitry Malioutov; Kuldeep S. Meel (CP, 2018)

Classification Rules in Relaxed Logical Form. - Bishwamittra Ghosh; Dmitry Malioutov; Kuldeep S. Meel (ECAI, 2020)

Efficient Learning of Interpretable Classification Rules. - Bishwamittra Ghosh; Dmitry Malioutov; Kuldeep S. Meel (J. Artif. Intell. Res., 2022)