Publications

147 / 3,329 publications found.


  •  Suda, T., Nikovski, D., "Deep Reinforcement Learning for Optimal Sailing Upwind", IEEE International Joint Conference on Neural Networks IJCNN, September 2022.
    BibTeX TR2022-102 PDF
    • @inproceedings{Suda2022sep,
    • author = {Suda, Takumi and Nikovski, Daniel},
    • title = {Deep Reinforcement Learning for Optimal Sailing Upwind},
    • booktitle = {IEEE International Joint Conference on Neural Networks IJCNN},
    • year = 2022,
    • month = sep,
    • url = {https://www.merl.com/publications/TR2022-102}
    • }
  •  Wang, B., Talukder, K., Sakamoto, Y., "Topological Data Analysis for Image-based Machine Learning: Application to Electric Motors", IEEE International Conference on Electrical Machines (ICEM), September 2022.
    BibTeX TR2022-113 PDF
    • @inproceedings{Wang2022sep,
    • author = {Wang, Bingnan and Talukder, Khaled and Sakamoto, Yusuke},
    • title = {Topological Data Analysis for Image-based Machine Learning: Application to Electric Motors},
    • booktitle = {IEEE International Conference on Electrical Machines (ICEM)},
    • year = 2022,
    • month = sep,
    • url = {https://www.merl.com/publications/TR2022-113}
    • }
  •  Zhan, S., Wichern, G., Laughman, C.R., Chong, A., Chakrabarty, A., "Calibrating building simulation models using multi-source datasets and meta-learned Bayesian optimization", Energy and Buildings, DOI: 10.1016/​j.enbuild.2022.112278, Vol. 270, pp. 112278, September 2022.
    BibTeX TR2022-072 PDF
    • @article{Zhan2023jan,
    • author = {Zhan, Sicheng and Wichern, Gordon and Laughman, Christopher R. and Chong, Adrian and Chakrabarty, Ankush},
    • title = {Calibrating building simulation models using multi-source datasets and meta-learned Bayesian optimization},
    • journal = {Energy and Buildings},
    • year = 2022,
    • volume = 270,
    • pages = 112278,
    • month = sep,
    • doi = {10.1016/j.enbuild.2022.112278},
    • url = {https://www.merl.com/publications/TR2022-072}
    • }
  •  Liu, Bryan, Koike-Akino, Toshiaki, Wang, Ye, Kim, Kyeong Jin, Brand, Matthew E., Aeron, Shuchin, Parsons, Kieran, "Data Privacy and Protection on Deep Leakage from Gradients by Layer-Wise Pruning", Tech. Rep. TR2022-081, Mitsubishi Electric Research Laboratories, Cambridge, MA, August 2022.
    BibTeX TR2022-081 PDF
    • @techreport{MERL_TR2022-081,
    • author = {Liu, Bryan; Koike-Akino, Toshiaki; Wang, Ye; Kim, Kyeong Jin; Brand, Matthew E.; Aeron, Shuchin; Parsons, Kieran},
    • title = {Data Privacy and Protection on Deep Leakage from Gradients by Layer-Wise Pruning},
    • institution = {MERL - Mitsubishi Electric Research Laboratories},
    • address = {Cambridge, MA 02139},
    • number = {TR2022-081},
    • month = aug,
    • year = 2022,
    • url = {https://www.merl.com/publications/TR2022-081/}
    • }
  •  Kojima, K., Jung, M., Koike-Akino, T., Wang, Y., Brand, M.E., Parsons, K., "Deep Transfer Learning for Nanophotonic Device Design", Conference on Lasers and Electro-Optics (CLEO) Pasific Rim, July 2022.
    BibTeX TR2022-107 PDF
    • @inproceedings{Kojima2022jul,
    • author = {Kojima, Keisuke and Jung, Minwoo and Koike-Akino, Toshiaki and Wang, Ye and Brand, Matthew E. and Parsons, Kieran},
    • title = {Deep Transfer Learning for Nanophotonic Device Design},
    • booktitle = {Conference on Lasers and Electro-Optics (CLEO) Pasific Rim},
    • year = 2022,
    • month = jul,
    • url = {https://www.merl.com/publications/TR2022-107}
    • }
  •  Rambhatla, S., Jones, M.J., Chellappa, R., "An Empirical Analysis of Boosting Deep Networks", International Joint Conference on Neural Networks (IJCNN), July 2022.
    BibTeX TR2022-075 PDF Presentation
    • @inproceedings{Rambhatla2022jul,
    • author = {Rambhatla, Sai and Jones, Michael J. and Chellappa, Rama},
    • title = {An Empirical Analysis of Boosting Deep Networks},
    • booktitle = {International Joint Conference on Neural Networks (IJCNN)},
    • year = 2022,
    • month = jul,
    • url = {https://www.merl.com/publications/TR2022-075}
    • }
  •  Shirsat, A., Sun, H., Kim, K.J., Guo, J., Nikovski, D.N., "ConvEDNet: A Convolutional Energy Disaggregation Network Using Continuous Point-On-Wave Measurements", IEEE PES General Meeting, July 2022.
    BibTeX TR2022-101 PDF
    • @inproceedings{Shirsat2022jul,
    • author = {Shirsat, Ashwin and Sun, Hongbo and Kim, Kyeong Jin and Guo, Jianlin and Nikovski, Daniel N.},
    • title = {ConvEDNet: A Convolutional Energy Disaggregation Network Using Continuous Point-On-Wave Measurements},
    • booktitle = {IEEE PES General Meeting},
    • year = 2022,
    • month = jul,
    • url = {https://www.merl.com/publications/TR2022-101}
    • }
  •  Demir, A., Koike-Akino, T., Wang, Y., Erdogmus, D., "EEG-GAT: Graph Attention Networks for Classification of Electroencephalogram (EEG) Signals", International Conference of the IEEE Engineering in Medicine & Biology Society (EMBS), DOI: 10.1109/​EMBC48229.2022.9871984, July 2022.
    BibTeX TR2022-097 PDF
    • @inproceedings{Demir2022jul,
    • author = {Demir, Andac and Koike-Akino, Toshiaki and Wang, Ye and Erdogmus, Deniz},
    • title = {EEG-GAT: Graph Attention Networks for Classification of Electroencephalogram (EEG) Signals},
    • booktitle = {International Conference of the IEEE Engineering in Medicine & Biology Society (EMBS)},
    • year = 2022,
    • month = jul,
    • publisher = {IEEE},
    • doi = {10.1109/EMBC48229.2022.9871984},
    • issn = {2694-0604},
    • isbn = {978-1-7281-2782-8},
    • url = {https://www.merl.com/publications/TR2022-097}
    • }
  •  Cao, W., Benosman, M., Zhang, X., Ma, R., "Domain Knowledge-Infused Deep Learning for Automated Analog/Radio-Frequency Circuit Parameter Optimization", ACM/IEEE Design Automation Conference, July 2022.
    BibTeX TR2022-096 PDF
    • @inproceedings{Cao2022jul,
    • author = {Cao, Weidong and Benosman, Mouhacine and Zhang, Xuan and Ma, Rui},
    • title = {Domain Knowledge-Infused Deep Learning for Automated Analog/Radio-Frequency Circuit Parameter Optimization},
    • booktitle = {ACM/IEEE Design Automation Conference},
    • year = 2022,
    • month = jul,
    • url = {https://www.merl.com/publications/TR2022-096}
    • }
  •  Kodama, T., Koike-Akino, T., Millar, D.S., Kojima, K., Parsons, K., "DNN-assisted phase distance tuned PSK modulation for PAM4-to-QPSK format conversion gateway node", Optics Express, DOI: 10.1364/​OE.449812, Vol. 30, No. 7, pp. 10866-10876, June 2022.
    BibTeX TR2022-091 PDF
    • @article{Kodama2022jun,
    • author = {Kodama, Takahiro and Koike-Akino, Toshiaki and Millar, David S. and Kojima, Keisuke and Parsons, Kieran},
    • title = {DNN-assisted phase distance tuned PSK modulation for PAM4-to-QPSK format conversion gateway node},
    • journal = {Optics Express},
    • year = 2022,
    • volume = 30,
    • number = 7,
    • pages = {10866--10876},
    • month = jun,
    • doi = {10.1364/OE.449812},
    • url = {https://www.merl.com/publications/TR2022-091}
    • }
  •  Chatterjee, M., Ahuja, N., Cherian, A., "Quantifying Predictive Uncertainty for Stochastic Video Synthesis from Audio", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2022.
    BibTeX TR2022-082 PDF
    • @inproceedings{Chatterjee2022jun,
    • author = {Chatterjee, Moitreya and Ahuja, Narendra and Cherian, Anoop},
    • title = {Quantifying Predictive Uncertainty for Stochastic Video Synthesis from Audio},
    • booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    • year = 2022,
    • month = jun,
    • url = {https://www.merl.com/publications/TR2022-082}
    • }
  •  Liu, B., Koike-Akino, T., Wang, Y., Kim, K.J., Brand, M.E., Aeron, S., Parsons, K., "Data Privacy and Protection on Deep Leakage from Gradients by Layer-Wise Pruning", IEEE Information Theory and Applications Workshop (ITA), June 2022.
    BibTeX TR2022-080 PDF Presentation
    • @inproceedings{Liu2022jun2,
    • author = {Liu, Bryan and Koike-Akino, Toshiaki and Wang, Ye and Kim, Kyeong Jin and Brand, Matthew E. and Aeron, Shuchin and Parsons, Kieran},
    • title = {Data Privacy and Protection on Deep Leakage from Gradients by Layer-Wise Pruning},
    • booktitle = {IEEE Information Theory and Applications Workshop (ITA)},
    • year = 2022,
    • month = jun,
    • url = {https://www.merl.com/publications/TR2022-080}
    • }
  •  Liu, B., Koike-Akino, T., Wang, Y., Kim, K.J., Brand, M.E., Aeron, S., Parsons, K., "Data Privacy and Protection on Deep Leakage from Gradients by Layer-Wise Pruning", IEEE Information Theory and Applications Workshop (ITA), June 2022.
    BibTeX TR2022-080 PDF Presentation
    • @inproceedings{Liu2022jun,
    • author = {Liu, Bryan and Koike-Akino, Toshiaki and Wang, Ye and Kim, Kyeong Jin and Brand, Matthew E. and Aeron, Shuchin and Parsons, Kieran},
    • title = {Data Privacy and Protection on Deep Leakage from Gradients by Layer-Wise Pruning},
    • booktitle = {IEEE Information Theory and Applications Workshop (ITA)},
    • year = 2022,
    • month = jun,
    • url = {https://www.merl.com/publications/TR2022-080}
    • }
  •  Sun, Y., Benosman, M., Ma, R., "GaN Distributed RF Power Amplifier Automation Design with Deep Reinforcement Learning", International Conference on Artificial Intelligence Circuits and Systems (AICAS), June 2022.
    BibTeX TR2022-074 PDF
    • @inproceedings{Sun2022jun,
    • author = {Sun, Yuxiang and Benosman, Mouhacine and Ma, Rui},
    • title = {GaN Distributed RF Power Amplifier Automation Design with Deep Reinforcement Learning},
    • booktitle = {International Conference on Artificial Intelligence Circuits and Systems (AICAS)},
    • year = 2022,
    • month = jun,
    • url = {https://www.merl.com/publications/TR2022-074}
    • }
  •  Koike-Akino, T., Pu, W., Wang, Y., "Quantum Transfer Learning for Wi-Fi Sensing", IEEE International Conference on Communications (ICC), DOI: 10.1109/​ICC45855.2022.9839011, May 2022.
    BibTeX TR2022-044 PDF Video Presentation
    • @inproceedings{Koike-Akino2022may2,
    • author = {Koike-Akino, Toshiaki and Pu, Wang and Wang, Ye},
    • title = {Quantum Transfer Learning for Wi-Fi Sensing},
    • booktitle = {IEEE International Conference on Communications (ICC)},
    • year = 2022,
    • month = may,
    • doi = {10.1109/ICC45855.2022.9839011},
    • issn = {1938-1883},
    • isbn = {978-1-5386-8347-7},
    • url = {https://www.merl.com/publications/TR2022-044}
    • }
  •  Koike-Akino, T., Kojima, K., Wang, Y., "AutoML Hyperparameter Tuning of Generative DNN Architecture for Nanophotonic Device Design", Conference on Lasers and Electro-Optics (CLEO), DOI: 10.1364/​CLEO_AT.2022.JW3A.44, May 2022.
    BibTeX TR2022-046 PDF Presentation
    • @inproceedings{Koike-Akino2022may3,
    • author = {Koike-Akino, Toshiaki and Kojima, Keisuke and Wang, Ye},
    • title = {AutoML Hyperparameter Tuning of Generative DNN Architecture for Nanophotonic Device Design},
    • booktitle = {Conference on Lasers and Electro-Optics (CLEO)},
    • year = 2022,
    • month = may,
    • publisher = {Optica},
    • doi = {10.1364/CLEO_AT.2022.JW3A.44},
    • isbn = {978-1-957171-05-0},
    • url = {https://www.merl.com/publications/TR2022-046}
    • }
  •  Cauligi, A., Chakrabarty, A., Di Cairano, S., Quirynen, R., "PRISM: Recurrent Neural Networks and Presolve Methods for Fast Mixed-integer Optimal Control", Learning for Dynamics and Control Conference (L4DC), April 2022, pp. 34-46.
    BibTeX TR2022-039 PDF
    • @inproceedings{Cauligi2022apr,
    • author = {Cauligi, Abhishek and Chakrabarty, Ankush and Di Cairano, Stefano and Quirynen, Rien},
    • title = {PRISM: Recurrent Neural Networks and Presolve Methods for Fast Mixed-integer Optimal Control},
    • booktitle = {Learning for Dynamics and Control Conference (L4DC)},
    • year = 2022,
    • pages = {34--46},
    • month = apr,
    • publisher = {Proceedings of Machine Learning Research (PMLR)},
    • url = {https://www.merl.com/publications/TR2022-039}
    • }
  •  Cao, W., Benosman, M., Zhang, X., Ma, R., "Domain Knowledge-Based Automated Analog Circuit Design with Deep Reinforcement Learning", AAAI Conference on Artificial Intelligence, February 2022.
    BibTeX TR2022-017 PDF
    • @inproceedings{Cao2022feb,
    • author = {Cao, Weidong and Benosman, Mouhacine and Zhang, Xuan and Ma, Rui},
    • title = {Domain Knowledge-Based Automated Analog Circuit Design with Deep Reinforcement Learning},
    • booktitle = {AAAI Conference on Artificial Intelligence},
    • year = 2022,
    • month = feb,
    • url = {https://www.merl.com/publications/TR2022-017}
    • }
  •  Chakrabarty, A., Danielson, C., Bortoff, S.A., Laughman, C.R., "Accelerating self-optimization control of refrigerant cycles with Bayesian optimization and adaptive moment estimation", Applied Thermal Engineering, DOI: 10.1016/​j.applthermaleng.2021.117335, Vol. 197, pp. 117335, February 2022.
    BibTeX TR2022-010 PDF
    • @article{Chakrabarty2022feb,
    • author = {Chakrabarty, Ankush and Danielson, Claus and Bortoff, Scott A. and Laughman, Christopher R.},
    • title = {Accelerating self-optimization control of refrigerant cycles with Bayesian optimization and adaptive moment estimation},
    • journal = {Applied Thermal Engineering},
    • year = 2022,
    • volume = 197,
    • pages = 117335,
    • month = feb,
    • doi = {10.1016/j.applthermaleng.2021.117335},
    • url = {https://www.merl.com/publications/TR2022-010}
    • }
  •  Lohit, S., Jones, M.J., "Model Compression Using Optimal Transport", IEEE Winter Conference on Applications of Computer Vision (WACV), January 2022.
    BibTeX TR2022-006 PDF Presentation
    • @inproceedings{Lohit2022jan,
    • author = {Lohit, Suhas and Jones, Michael J.},
    • title = {Model Compression Using Optimal Transport},
    • booktitle = {IEEE Winter Conference on Applications of Computer Vision (WACV)},
    • year = 2022,
    • month = jan,
    • publisher = {CVF OpenAccess},
    • url = {https://www.merl.com/publications/TR2022-006}
    • }
  •  Wang, Z.-Q., Wichern, G., Le Roux, J., "Convolutive Prediction for Monaural Speech Dereverberation and Noisy-Reverberant Speaker Separation", IEEE/ACM Transactions on Audio, Speech, and Language Processing, DOI: 10.1109/​TASLP.2021.3129363, Vol. 29, pp. 3476-3490, December 2021.
    BibTeX TR2021-144 PDF
    • @article{Wang2021dec,
    • author = {Wang, Zhong-Qiu and Wichern, Gordon and Le Roux, Jonathan},
    • title = {Convolutive Prediction for Monaural Speech Dereverberation and Noisy-Reverberant Speaker Separation},
    • journal = {IEEE/ACM Transactions on Audio, Speech, and Language Processing},
    • year = 2021,
    • volume = 29,
    • pages = {3476--3490},
    • month = dec,
    • doi = {10.1109/TASLP.2021.3129363},
    • url = {https://www.merl.com/publications/TR2021-144}
    • }
  •  Kojima, K., Tang, Y., Wang, Y., Koike-Akino, T., "Machine Learning for design and optimization of photonic devices" in Machine Learning for Future Fiber Optic Communication Systems (Elsevier Book), November 2021.
    BibTeX TR2021-142 PDF
    • @incollection{Kojima2021nov,
    • author = {Kojima, Keisuke and Tang, Yingheng and Wang, Ye and Koike-Akino, Toshiaki},
    • title = {Machine Learning for design and optimization of photonic devices},
    • booktitle = {Machine Learning for Future Fiber Optic Communication Systems (Elsevier Book)},
    • year = 2021,
    • month = nov,
    • url = {https://www.merl.com/publications/TR2021-142}
    • }
  •  Demir, A., Koike-Akino, T., Wang, Y., Erdogmus, D., Haruna, M., "EEG-GNN: Graph Neural Networks for Classification of Electroencephalogram (EEG) Signals", International IEEE EMBS Conference on Neural Engineering, DOI: 10.1109/​EMBC46164.2021.9630194, October 2021.
    BibTeX TR2021-136 PDF Video Presentation
    • @inproceedings{Demir2021oct,
    • author = {Demir, Andac and Koike-Akino, Toshiaki and Wang, Ye and Erdogmus, Deniz and Haruna, Masaki},
    • title = {EEG-GNN: Graph Neural Networks for Classification of Electroencephalogram (EEG) Signals},
    • booktitle = {International IEEE EMBS Conference on Neural Engineering},
    • year = 2021,
    • month = oct,
    • publisher = {IEEE},
    • doi = {10.1109/EMBC46164.2021.9630194},
    • issn = {2694-0604},
    • isbn = {978-1-7281-1179-7},
    • url = {https://www.merl.com/publications/TR2021-136}
    • }
  •  Li, X., Kojima, K., Brand, M.E., "Predicting Long- and Variable-Distance Coupling Effects in Metasurface Optics", IEEE Photonics Conference (IPC), DOI: 10.1109/​IPC48725.2021.9593086, October 2021, pp. 1-2.
    BibTeX TR2021-140 PDF
    • @inproceedings{Li2021oct,
    • author = {Li, Xinhao and Kojima, Keisuke and Brand, Matthew E.},
    • title = {Predicting Long- and Variable-Distance Coupling Effects in Metasurface Optics},
    • booktitle = {IEEE Photonics Conference (IPC)},
    • year = 2021,
    • pages = {1--2},
    • month = oct,
    • doi = {10.1109/IPC48725.2021.9593086},
    • url = {https://www.merl.com/publications/TR2021-140}
    • }
  •  Chakrabarty, A., Quirynen, R., Romeres, D., Di Cairano, S., "Learning Disagreement Regions with Deep Neural Networks to Reduce Practical Complexity of Mixed-Integer MPC", IEEE International Conference on Systems, Man, and Cybernetics, DOI: 10.1109/​SMC52423.2021.9659186, October 2021, pp. 3238-3244.
    BibTeX TR2021-126 PDF Video
    • @inproceedings{Chakrabarty2021oct,
    • author = {Chakrabarty, Ankush and Quirynen, Rien and Romeres, Diego and Di Cairano, Stefano},
    • title = {Learning Disagreement Regions with Deep Neural Networks to Reduce Practical Complexity of Mixed-Integer MPC},
    • booktitle = {IEEE International Conference on Systems, Man, and Cybernetics},
    • year = 2021,
    • pages = {3238--3244},
    • month = oct,
    • doi = {10.1109/SMC52423.2021.9659186},
    • url = {https://www.merl.com/publications/TR2021-126}
    • }