Publications

8 / 3,591 publications found.


  •  Laftchiev, E., Yan, Q., Nikovski, D.N., "The Missing Input Problem", IEEE Big Data, DOI: 10.1109/​BigData50022.2020.9378144, December 2020, pp. 1565-1573.
    BibTeX TR2020-172 PDF
    • @inproceedings{Laftchiev2020dec,
    • author = {Laftchiev, Emil and Yan, Qing and Nikovski, Daniel N.},
    • title = {The Missing Input Problem},
    • booktitle = {IEEE Big Data},
    • year = 2020,
    • pages = {1565--1573},
    • month = dec,
    • publisher = {IEEE},
    • doi = {10.1109/BigData50022.2020.9378144},
    • url = {https://www.merl.com/publications/TR2020-172}
    • }
  •  DeRousseau, M.A., Laftchiev, E., Kasprzyk, J.R., Balaji, R., Srubar III, W.V., "Machine Learning Methods for Predicting the Field Compressive Strength of Concrete", Construction And Building Materials, DOI: 10.1016/​j.conbuildmat.2019.08.042, Vol. 228, December 2019.
    BibTeX TR2019-096 PDF
    • @article{DeRousseau2019dec,
    • author = {DeRousseau, Mikaela A. and Laftchiev, Emil and Kasprzyk, Joseph R. and Balaji, Rajagopalan and Srubar III, Wil V.},
    • title = {Machine Learning Methods for Predicting the Field Compressive Strength of Concrete},
    • journal = {Construction And Building Materials},
    • year = 2019,
    • volume = 228,
    • month = dec,
    • doi = {10.1016/j.conbuildmat.2019.08.042},
    • url = {https://www.merl.com/publications/TR2019-096}
    • }
  •  Zhang, W., Jha, D.K., Laftchiev, E., Nikovski, D.N., "Multi-label Prediction in Time Series Data using Deep Neural Networks", International Journal for Prognostics and Health Management Special Issue on Applications of Deep Learning and Emerging Analytics, Vol. 10, pp. 0-12, September 2019.
    BibTeX TR2019-110 PDF
    • @article{Zhang2019sep2,
    • author = {Zhang, Wenyu and Jha, Devesh K. and Laftchiev, Emil and Nikovski, Daniel N.},
    • title = {Multi-label Prediction in Time Series Data using Deep Neural Networks},
    • journal = {International Journal for Prognostics and Health Management Special Issue on Applications of Deep Learning and Emerging Analytics},
    • year = 2019,
    • volume = 10,
    • pages = {0--12},
    • month = sep,
    • note = {Special Issue on Deep Learning and Emerging Analytics},
    • issn = {2153-2648},
    • url = {https://www.merl.com/publications/TR2019-110}
    • }
  •  Natarajan, A., Laftchiev, E., "A Transfer Active Learning Framework to Predict Thermal Comfort", International Journal of Prognostics and Health Management Special Issue on PHM for Human Health & Performance, December 2018.
    BibTeX TR2018-156 PDF
    • @article{Natarajan2018dec,
    • author = {Natarajan, Annamalai and Laftchiev, Emil},
    • title = {A Transfer Active Learning Framework to Predict Thermal Comfort},
    • journal = {International Journal of Prognostics and Health Management Special Issue on PHM for Human Health \& Performance},
    • year = 2018,
    • month = dec,
    • url = {https://www.merl.com/publications/TR2018-156}
    • }
  •  Laftchiev, E., Sun, X., Dau, H.-A., Nikovski, D.N., "Anomaly Detection in Discrete Manufacturing Systems using Event Relationship Tables", International Workshop on Principle of Diagnosis, August 2018.
    BibTeX TR2018-128 PDF
    • @inproceedings{Laftchiev2018aug,
    • author = {Laftchiev, Emil and Sun, Xinmaio and Dau, Hoang-Anh and Nikovski, Daniel N.},
    • title = {Anomaly Detection in Discrete Manufacturing Systems using Event Relationship Tables},
    • booktitle = {International Workshop on Principle of Diagnosis},
    • year = 2018,
    • month = aug,
    • url = {https://www.merl.com/publications/TR2018-128}
    • }
  •  Laftchiev, E., Liu, Y., "Finding Multidimensional Patterns in Multidimensional Time Series", SIGKDD Workshop on Mining and Learning From Time Series, August 2018.
    BibTeX TR2018-044 PDF
    • @inproceedings{Laftchiev2018aug2,
    • author = {Laftchiev, Emil and Liu, Yuchao},
    • title = {Finding Multidimensional Patterns in Multidimensional Time Series},
    • booktitle = {SIGKDD Workshop on Mining and Learning From Time Series},
    • year = 2018,
    • month = aug,
    • url = {https://www.merl.com/publications/TR2018-044}
    • }
  •  Deshmukh, A., Laftchiev, E., "Semi-Supervised Transfer Learning Using Marginal Predictors", IEEE Data Science Workshop, DOI: 10.1109/​DSW.2018.8439908, June 6, 2018, pp. 160-164.
    BibTeX TR2018-040 PDF Software
    • @inproceedings{Deshmukh2018jun,
    • author = {Deshmukh, Aniket and Laftchiev, Emil},
    • title = {Semi-Supervised Transfer Learning Using Marginal Predictors},
    • booktitle = {IEEE Data Science Workshop},
    • year = 2018,
    • pages = {160--164},
    • month = jun,
    • doi = {10.1109/DSW.2018.8439908},
    • url = {https://www.merl.com/publications/TR2018-040}
    • }
  •  Laftchiev, E., Nikovski, D.N., "An IoT System to Estimate Personal Thermal Comfort", IEEE World Forum on Internet of Things (WF- IoT), DOI: 10.1109/​WF-IoT.2016.7845401, December 2016, pp. 672-677.
    BibTeX TR2016-161 PDF
    • @inproceedings{Laftchiev2016dec,
    • author = {Laftchiev, Emil and Nikovski, Daniel N.},
    • title = {An IoT System to Estimate Personal Thermal Comfort},
    • booktitle = {IEEE World Forum on Internet of Things (WF- IoT)},
    • year = 2016,
    • pages = {672--677},
    • month = dec,
    • doi = {10.1109/WF-IoT.2016.7845401},
    • url = {https://www.merl.com/publications/TR2016-161}
    • }