Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Dmitry Malioutov"'
Machine learning has become omnipresent with applications in various safety-critical domains such as medical, law, and transportation. In these domains, high-stake decisions provided by machine learning necessitate researchers to design interpretable
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1fd09b98cdd4e7ca25922ab19f801f46
http://arxiv.org/abs/2205.06936
http://arxiv.org/abs/2205.06936
Publikováno v:
SIAM Journal on Scientific Computing. 39:A1558-A1585
Computation of the trace of a matrix function plays an important role in many scientific computing applications, including applications in machine learning, computational physics (e.g., lattice qua...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a8c5f6b151a7d7233fb5ac46a7dffe48
https://doi.org/10.1137/16m1078148
https://doi.org/10.1137/16m1078148
Autor:
Kuldeep S. Meel, Dmitry Malioutov
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319983332
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9e231588b69fd3150a01c6e19e6ec800
https://doi.org/10.1007/978-3-319-98334-9_49
https://doi.org/10.1007/978-3-319-98334-9_49
Introduction to the Issue on Financial Signal Processing and Machine Learning for Electronic Trading
Publikováno v:
IEEE Journal of Selected Topics in Signal Processing. 10:979-981
The twelve papers in this special issue presents relevant research contributions from the disciplines of finance, mathematics, data science and engineering to facilitate scientific cross-fertilization. It will also serve the signal processing communi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f8fe98553d64cdf48c2ca779b5ca0b56
https://doi.org/10.1109/jstsp.2016.2594458
https://doi.org/10.1109/jstsp.2016.2594458
Autor:
Kuldeep S. Meel, Dmitry Malioutov
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319983332
The wide adoption of machine learning approaches in the industry, government, medicine and science has renewed the interest in interpretable machine learning: many decisions are too important to be delegated to black-box techniques such as deep neura
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77d4950de9f53b9abb1075575aedff57
https://doi.org/10.1007/978-3-319-98334-9_21
https://doi.org/10.1007/978-3-319-98334-9_21
Autor:
Bogdan Budnik, Dmitry Malioutov, Steven A. Carr, Tianchi Chen, Edoardo M. Airoldi, Nikolai Slavov, Jacob D. Jaffe
Many proteoforms–arising from alternative splicing, post-translational modifications (PTM), or paralogous genes–have distinct biological functions, such as histone PTM proteoforms. However, their quantification by existing bottom-up mass-spectrom
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1721ab81fb63f5b6afd7f9622cbb5b17
Publikováno v:
Studies in Big Data ISBN: 9783319540238
An important problem in the context of supervised machine learning is designing systems which are interpretable by humans. In domains such as law, medicine, and finance that deal with human lives, delegating the decision to a black-box machine-learni
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fc005be71a6e37f6eb8435b7675c251e
https://doi.org/10.1007/978-3-319-54024-5_5
https://doi.org/10.1007/978-3-319-54024-5_5
Publikováno v:
MLSP
This paper develops a novel optimization framework for learning accurate and sparse two-level Boolean rules for classification, both in Conjunctive Normal Form (CNF, i.e. AND-of-ORs) and in Disjunctive Normal Form (DNF, i.e. OR-of-ANDs). In contrast
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec5f5fa2b0be33aac3bdc5f5d287c353
https://doi.org/10.1109/mlsp.2016.7738856
https://doi.org/10.1109/mlsp.2016.7738856
Publikováno v:
Financial Signal Processing and Machine Learning
This chapter overview the connections between support vector machines (SVM) and conditional value at risk (CVaR) minimization and suggests further interactions beyond their similarity in appearance. It introduces several SVM formulations, whose relat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7eb81528f444a7a75f9046842306982b
https://doi.org/10.1002/9781118745540.ch10
https://doi.org/10.1002/9781118745540.ch10
Publikováno v:
Financial Signal Processing and Machine Learning
Mean-reverting assets, namely assets whose price oscillates predictably around a long-term mean, provide investors with an ideal investment opportunity. Statistical arbitrage strategies attempt to find portfolios that exhibit mean reversion. This cha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::04131745bd1db5b73daaf22938e8826f
https://doi.org/10.1002/9781118745540.ch3
https://doi.org/10.1002/9781118745540.ch3