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MSOLab – Modelling, Simulation & Optimization Laboratory MSOLab Modelling, Simulation & Optimization Laboratory Menu Home Research Groups Projects Publications Resources Events & News Contact The Modeling, Simulation and Optimization Laboratory (MSOLab) is one of four research laboratories in the School of Information and Technology. It was founded in 2013 and is a community of theoretical computer scientists with interests in algorithms, complexity, simulation, high-performance computing, modeling, machine learning, semantics, security, logic, and databases. The mainspring of research in MSO Laboratory is the study of theories which underlie, or should in future underlie, the analysis and design of computing systems. Our work has a core of theoretical research and a practical component which explores application and implementation of the theory. Several research groups exist within MSOLab: Algorithms and Optimization, High-Performance Computing, Data Science. News IEEE World Congress on Computational Intelligence August 16, 2018 Team from MSO Lab has 3 papers accepted at IEEE World Congress on Computational Intelligence (WCCI). We also participated WCCI2018… CONTINUE READING Seminar “The cocktail party effect: An old problem begging for a new solution” March 30, 2018 Thời gian: 14.00 ngày 29/3/2018 Địa điểm: phòng seminar tầng 9 (MICA) Người trình bày: Prof. Pierre Divenyi, Stanford University Title: The… CONTINUE READING Seminar: “Ergonomic Aspects of Autonomous Driving” March 26, 2018 Ergonomic Aspects of Autonomous Driving Studying Human Behavior in Urban Traffic Using Linked Driving Simulation Thời gian: 14.30 ngày thứ… CONTINUE READING Seminar “Artificial Intelligence and Big Data: the role of machine learning” November 3, 2017 Thời gian: 14.30 ngày thứ 2, 6/11/2017 Địa điểm: phòng 803, nhà B1, Đại học Bách khoa Hà Nội Người… CONTINUE READING Recent publications 45 entries « ‹ 1 of 15 › » 2018 Huynh Thi Thanh Binh Debabrata Samanta, Sayar Ahmad Kuchy Big Data: Theory & Practices Book LAP LAMBERT Academic Publishing, 2018 , ISBN: ISBN 978-620-2-05953-4 . BibTeX @book{binh2018book, title = {Big Data: Theory & Practices}, author = {Huynh Thi Thanh Binh, Debabrata Samanta, Sayar Ahmad Kuchy}, isbn = {ISBN 978-620-2-05953-4}, year = {2018}, date = {2018-08-16}, publisher = {LAP LAMBERT Academic Publishing}, keywords = {}, pubstate = {published}, tppubtype = {book} } Close Do, Phan Thuan; Nghiem, Nguyen Viet Dung ; Nguyen, Ngoc Quang ; Pham, Quang Dung A time-dependent model with speed windows for share-a-ride problems: A case study for Tokyo transportation Journal Article Data Knowl. Eng., 114 , pp. 67–85, 2018 . Links | BibTeX @article{DBLP:journals/dke/DoNNP18b, title = {A time-dependent model with speed windows for share-a-ride problems: A case study for Tokyo transportation}, author = {Phan Thuan Do and Nguyen Viet Dung Nghiem and Ngoc Quang Nguyen and Quang Dung Pham}, url = {https://doi.org/10.1016/j.datak.2017.06.002}, doi = {10.1016/j.datak.2017.06.002}, year = {2018}, date = {2018-01-01}, journal = {Data Knowl. Eng.}, volume = {114}, pages = {67--85}, keywords = {}, pubstate = {published}, tppubtype = {article} } Close https://doi.org/10.1016/j.datak.2017.06.002 doi:10.1016/j.datak.2017.06.002 Close Pham, Dinh Thanh; Dinh, Anh Dung; Tran, Ngoc Tien; Tran, Ba Trung; Huynh, Thi Thanh Binh A Guided Differential Evolutionary Multi-tasking with Powell search method for solving Multi-objective Continuous Optimization Inproceedings Forthcoming Forthcoming. BibTeX @inproceedings{Binh2018MultiTasking, title = {A Guided Differential Evolutionary Multi-tasking with Powell search method for solving Multi-objective Continuous Optimization}, author = {Dinh Thanh Pham and Anh Dung Dinh and Ngoc Tien Tran and Ba Trung Tran and Thi Thanh Binh Huynh}, year = {2018}, date = {2018-01-01}, journal = {World Congress on Computational Intelligence year=2018}, keywords = {}, pubstate = {forthcoming}, tppubtype = {inproceedings} } Close 45 entries « ‹ 1 of 15 › » MSOLab © 2019 SoICT Modelling, Simulation and Optimization Lab ➤
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