Publications

88 / 3,808 publications found.


  •  Dong, S., Jha, D.K., Romeres, D., Kim, S., Nikovski, D.N., Rodriguez, A., "Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry", IEEE International Conference on Robotics and Automation (ICRA), DOI: 10.1109/​ICRA48506.2021.9561646, May 2021.
    BibTeX TR2021-052 PDF Video
    • @inproceedings{Dong2021may,
    • author = {Dong, Siyuan and Jha, Devesh K. and Romeres, Diego and Kim, Sangwoon and Nikovski, Daniel N. and Rodriguez, Alberto},
    • title = {{Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry}},
    • booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
    • year = 2021,
    • month = may,
    • publisher = {IEEE},
    • doi = {10.1109/ICRA48506.2021.9561646},
    • issn = {2577-087X},
    • isbn = {978-1-7281-9077-8},
    • url = {https://www.merl.com/publications/TR2021-052}
    • }
  •  Tang, Y., Kojima, K., Koike-Akino, T., Wang, Y., Jha, D.K., Parsons, K., Qi, M., "Nano-Optic Broadband Power Splitter Design via Cycle-Consistent Adversarial Deep Learning", Conference on Lasers and Electro-Optics (CLEO), DOI: 10.1364/​CLEO_SI.2021.SW4E.1, May 2021.
    BibTeX TR2021-045 PDF Presentation
    • @inproceedings{Tang2021may3,
    • author = {Tang, Yingheng and Kojima, Keisuke and Koike-Akino, Toshiaki and Wang, Ye and Jha, Devesh K. and Parsons, Kieran and Qi, Minghao},
    • title = {{Nano-Optic Broadband Power Splitter Design via Cycle-Consistent Adversarial Deep Learning}},
    • booktitle = {Conference on Lasers and Electro-Optics (CLEO)},
    • year = 2021,
    • month = may,
    • doi = {10.1364/CLEO_SI.2021.SW4E.1},
    • url = {https://www.merl.com/publications/TR2021-045}
    • }
  •  Ota, K., Jha, D.K., Romeres, D., van Baar, J., Smith, K., Semistsu, T., Oiki, T., Sullivan, A., Nikovski, D.N., Tenenbaum, J.B., "Data-Efficient Learning for Complex and Real-Time Physical Problem Solving using Augmented Simulation", IEEE Robotics and Automation Letters, DOI: 10.1109/​LRA.2021.3068887, Vol. 6, No. 2, March 2021.
    BibTeX TR2021-032 PDF Video Software
    • @article{Ota2021mar,
    • author = {Ota, Kei and Jha, Devesh K. and Romeres, Diego and {van Baar}, Jeroen and Smith, Kevin and Semistsu, Takayuki and Oiki, Tomoaki and Sullivan, Alan and Nikovski, Daniel N. and Tenenbaum, Joshua B.},
    • title = {{Data-Efficient Learning for Complex and Real-Time Physical Problem Solving using Augmented Simulation}},
    • journal = {IEEE Robotics and Automation Letters},
    • year = 2021,
    • volume = 6,
    • number = 2,
    • month = mar,
    • doi = {10.1109/LRA.2021.3068887},
    • url = {https://www.merl.com/publications/TR2021-032}
    • }
  •  Kojima, K., Tang, Y., Koike-Akino, T., Wang, Y., Jha, D.K., TaherSima, M., Parsons, K., "Application of Deep Learning for Nanophotonic Device Design", SPIE Photonics West, Bahram Jalali and Ken-ichi Kitayama, Eds., DOI: 10.1117/​12.2579104, March 2021.
    BibTeX TR2020-182 PDF Video
    • @inproceedings{Kojima2021mar,
    • author = {Kojima, Keisuke and Tang, Yingheng and Koike-Akino, Toshiaki and Wang, Ye and Jha, Devesh K. and TaherSima, Mohammad and Parsons, Kieran},
    • title = {{Application of Deep Learning for Nanophotonic Device Design}},
    • booktitle = {SPIE Photonics West},
    • year = 2021,
    • editor = {Bahram Jalali and Ken-ichi Kitayama},
    • month = mar,
    • publisher = {SPIE},
    • doi = {10.1117/12.2579104},
    • url = {https://www.merl.com/publications/TR2020-182}
    • }
  •  Ota, K., Jha, D.K., Kanezaki, A., "Training Larger Networks for Deep Reinforcement Learning", arXiv, February 2021.
    BibTeX arXiv
    • @inproceedings{Ota2021feb,
    • author = {Ota, Kei and Jha, Devesh K. and Kanezaki, Asako},
    • title = {{Training Larger Networks for Deep Reinforcement Learning}},
    • booktitle = {arXiv},
    • year = 2021,
    • month = feb,
    • url = {https://arxiv.org/abs/2102.07920}
    • }
  •  Kojima, K., TaherSima, M., Koike-Akino, T., Jha, D.K., Tang, Y., Wang, Y., Parsons, K., "Deep Neural Networks for Inverse Design of Nanophotonic Devices", IEEE Journal of Lightwave Technology, DOI: 10.1109/​JLT.2021.3050083, January 2021.
    BibTeX TR2021-001 PDF
    • @article{Kojima2021jan,
    • author = {Kojima, Keisuke and TaherSima, Mohammad and Koike-Akino, Toshiaki and Jha, Devesh K. and Tang, Yingheng and Wang, Ye and Parsons, Kieran},
    • title = {{Deep Neural Networks for Inverse Design of Nanophotonic Devices}},
    • journal = {IEEE Journal of Lightwave Technology},
    • year = 2021,
    • month = jan,
    • doi = {10.1109/JLT.2021.3050083},
    • issn = {1558-2213},
    • url = {https://www.merl.com/publications/TR2021-001}
    • }
  •  Ota, K., Jha, D.K., Onishi, T., Kanezaki, A., Yoshiyasu, Y., Mariyama, T., Nikovski, D.N., "Deep Reactive Planning in Dynamic Environments", Conference on Robot Learning (CoRL), Kober, Jens and Ramos, Fabio and Tomlin, Calire, Eds., November 2020, pp. 1943-1957.
    BibTeX TR2020-144 PDF Video
    • @inproceedings{Ota2020nov2,
    • author = {Ota, Kei and Jha, Devesh K. and Onishi, Tadashi and Kanezaki, Asako and Yoshiyasu, Yusuke and Mariyama, Toshisada and Nikovski, Daniel N.},
    • title = {{Deep Reactive Planning in Dynamic Environments}},
    • booktitle = {Conference on Robot Learning (CoRL)},
    • year = 2020,
    • editor = {Kober, Jens and Ramos, Fabio and Tomlin, Calire},
    • pages = {1943--1957},
    • month = nov,
    • publisher = {Proceedings of Machine Learning Research},
    • url = {https://www.merl.com/publications/TR2020-144}
    • }
  •  Ota, K., Sasaki, Y., Jha, D., Yoshiyasu, Y., Kanezaki, A., "Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), November 2020.
    BibTeX TR2020-141 PDF Software
    • @inproceedings{Ota2020nov,
    • author = {Ota, Kei and Sasaki, Yoko and Jha, Devesh and Yoshiyasu, Yusuke and Kanezaki, Asako},
    • title = {{Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path}},
    • booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
    • year = 2020,
    • month = nov,
    • url = {https://www.merl.com/publications/TR2020-141}
    • }
  •  Zhang, W., Seto, S., Jha, D.K., "CAZSL: Zero-Shot Regression for Pushing Models by Generalizing Through Context", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), November 2020.
    BibTeX TR2020-140 PDF Software
    • @inproceedings{Zhang2020nov,
    • author = {Zhang, Wenyu and Seto, Skyler and Jha, Devesh K.},
    • title = {{CAZSL: Zero-Shot Regression for Pushing Models by Generalizing Through Context}},
    • booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
    • year = 2020,
    • month = nov,
    • url = {https://www.merl.com/publications/TR2020-140}
    • }
  •  Tang, Y., Kojima, K., Koike-Akino, T., Wang, Y., Wu, P., TaherSima, M., Jha, D.K., Parsons, K., Qi, M., "Generative Deep Learning Model for Inverse Design of Integrated Nanophotonic Devices", Lasers and Photonics Reviews, DOI: 10.1002/​lpor.202000287, Vol. 2020, pp. 2000287, October 2020.
    BibTeX TR2020-135 PDF
    • @article{Tang2020oct,
    • author = {Tang, Yingheng and Kojima, Keisuke and Koike-Akino, Toshiaki and Wang, Ye and Wu, Pengxiang and TaherSima, Mohammad and Jha, Devesh K. and Parsons, Kieran and Qi, Minghao},
    • title = {{Generative Deep Learning Model for Inverse Design of Integrated Nanophotonic Devices}},
    • journal = {Lasers and Photonics Reviews},
    • year = 2020,
    • volume = 2020,
    • pages = 2000287,
    • month = oct,
    • doi = {10.1002/lpor.202000287},
    • url = {https://www.merl.com/publications/TR2020-135}
    • }
  •  Kojima, K., Tang, Y., Koike-Akino, T., Wang, Y., Jha, D.K., Parsons, K., TaherSima, M., Sang, F., Klamkin, J., Qi, M., "Inverse Design of Nanophotonic Devices using Deep Neural Networks", Asia Communications and Photonics Conference (ACP), September 2020, pp. Su1A.1.
    BibTeX TR2020-130 PDF Video
    • @inproceedings{Kojima2020sep,
    • author = {Kojima, Keisuke and Tang, Yingheng and Koike-Akino, Toshiaki and Wang, Ye and Jha, Devesh K. and Parsons, Kieran and TaherSima, Mohammad and Sang, Fengqiao and Klamkin, Jonathan and Qi, Minghao},
    • title = {{Inverse Design of Nanophotonic Devices using Deep Neural Networks}},
    • booktitle = {Asia Communications and Photonics Conference (ACP)},
    • year = 2020,
    • pages = {Su1A.1},
    • month = sep,
    • publisher = {Optical Society of America},
    • isbn = {978-1-943580-82-8},
    • url = {https://www.merl.com/publications/TR2020-130}
    • }
  •  Chakrabarty, A., Jha, D.K., Buzzard, G.T., Wang, Y., Vamvoudakis, K., "Safe Approximate Dynamic Programming via Kernelized Lipschitz Estimation", IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/​TNNLS.2020.2978805, July 2020.
    BibTeX TR2020-108 PDF
    • @article{Chakrabarty2020jul2,
    • author = {Chakrabarty, Ankush and Jha, Devesh K. and Buzzard, Gregery T. and Wang, Yebin and Vamvoudakis, Kyriakos},
    • title = {{Safe Approximate Dynamic Programming via Kernelized Lipschitz Estimation}},
    • journal = {IEEE Transactions on Neural Networks and Learning Systems},
    • year = 2020,
    • month = jul,
    • doi = {10.1109/TNNLS.2020.2978805},
    • url = {https://www.merl.com/publications/TR2020-108}
    • }
  •  Romeres, D., Liu, Y., Jha, D.K., Nikovski, D.N., "Understanding Multi-Modal Perception Using Behavioral Cloning for Peg-In-a-Hole Insertion Tasks", Robotics: Science and Systems, July 2020.
    BibTeX TR2020-110 PDF
    • @inproceedings{Romeres2020jul,
    • author = {Romeres, Diego and Liu, Yifang and Jha, Devesh K. and Nikovski, Daniel N.},
    • title = {{Understanding Multi-Modal Perception Using Behavioral Cloning for Peg-In-a-Hole Insertion Tasks}},
    • booktitle = {Robotics: Science and Systems},
    • year = 2020,
    • month = jul,
    • url = {https://www.merl.com/publications/TR2020-110}
    • }
  •  Ota, K., Oiki, T., Jha, D.K., Mariyama, T., Nikovski, D.N., "Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?", International Conference on Machine Learning (ICML), Daumé III , Hal and Singh, Aarti, Eds., June 2020, pp. 7424-7433.
    BibTeX TR2020-083 PDF Software
    • @inproceedings{Ota2020jun,
    • author = {Ota, Kei and Oiki, Tomoaki and Jha, Devesh K. and Mariyama, Toshisada and Nikovski, Daniel N.},
    • title = {{Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?}},
    • booktitle = {International Conference on Machine Learning (ICML)},
    • year = 2020,
    • editor = {Daumé III , Hal and Singh, Aarti},
    • pages = {7424--7433},
    • month = jun,
    • publisher = {PMLR},
    • url = {https://www.merl.com/publications/TR2020-083}
    • }
  •  Jha, D.K., Kolaric, P., Raghunathan, A., Lewis, F., Benosman, M., Romeres, D., Nikovski, D.N., "Local Policy Optimization for Trajectory-Centric Reinforcement Learning", IEEE International Conference on Robotics and Automation (ICRA), Ayanna Howard, Eds., May 2020, pp. 5094-5100.
    BibTeX TR2020-062 PDF
    • @inproceedings{Jha2020may,
    • author = {Jha, Devesh K. and Kolaric, Patrik and Raghunathan, Arvind and Lewis, Frank and Benosman, Mouhacine and Romeres, Diego and Nikovski, Daniel N.},
    • title = {{Local Policy Optimization for Trajectory-Centric Reinforcement Learning}},
    • booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
    • year = 2020,
    • editor = {Ayanna Howard},
    • pages = {5094--5100},
    • month = may,
    • publisher = {IEEE},
    • isbn = {978-1-7281-7395-5},
    • url = {https://www.merl.com/publications/TR2020-062}
    • }
  •  Romeres, D., Dalla Libera, A., Jha, D.K., Yerazunis, W.S., Nikovski, D.N., "Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements", Robotics and Automation Letters, DOI: 10.1109/​LRA.2020.2977255, Vol. 5, No. 2, pp. 3548-3555, May 2020.
    BibTeX TR2020-063 PDF
    • @article{Romeres2020may,
    • author = {Romeres, Diego and Dalla Libera, Alberto and Jha, Devesh K. and Yerazunis, William S. and Nikovski, Daniel N.},
    • title = {{Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements}},
    • journal = {Robotics and Automation Letters},
    • year = 2020,
    • volume = 5,
    • number = 2,
    • pages = {3548--3555},
    • month = may,
    • doi = {10.1109/LRA.2020.2977255},
    • issn = {2377-3766},
    • url = {https://www.merl.com/publications/TR2020-063}
    • }
  •  Kojima, K., TaherSima, M., Koike-Akino, T., Jha, D.K., Tang, Y., Parsons, K., Sang, F., Klamkin, J., "Deep Neural Networks for Designing Integrated Photonics", Optical Fiber Communication Conference and Exposition (OFC), DOI: 10.1364/​OFC.2020.Th1A.6, March 2020.
    BibTeX TR2020-057 PDF
    • @inproceedings{Kojima2020mar,
    • author = {Kojima, Keisuke and TaherSima, Mohammad and Koike-Akino, Toshiaki and Jha, Devesh K. and Tang, Yingheng and Parsons, Kieran and Sang, Fengqiao and Klamkin, Jonathan},
    • title = {{Deep Neural Networks for Designing Integrated Photonics}},
    • booktitle = {Optical Fiber Communication Conference and Exposition (OFC)},
    • year = 2020,
    • month = mar,
    • publisher = {OSA},
    • doi = {10.1364/OFC.2020.Th1A.6},
    • isbn = {978-1-943580-71-2},
    • url = {https://www.merl.com/publications/TR2020-057}
    • }
  •  Tang, Y., Kojima, K., Koike-Akino, T., Wang, Y., Wu, P., TaherSima, M., Jha, D.K., Parsons, K., Qi, M., "Generative Deep Learning Model for a Multi-level NanoOptic Broadband Power Splitter", Optical Fiber Communication Conference and Exposition (OFC), DOI: 10.1364/​OFC.2020.Th1A.1, March 2020, pp. Th1A.1.
    BibTeX TR2020-025 PDF
    • @inproceedings{Tang2020mar,
    • author = {Tang, Yingheng and Kojima, Keisuke and Koike-Akino, Toshiaki and Wang, Ye and Wu, Pengxiang and TaherSima, Mohammad and Jha, Devesh K. and Parsons, Kieran and Qi, Minghao},
    • title = {{Generative Deep Learning Model for a Multi-level NanoOptic Broadband Power Splitter}},
    • booktitle = {Optical Fiber Communication Conference and Exposition (OFC)},
    • year = 2020,
    • pages = {Th1A.1},
    • month = mar,
    • publisher = {OSA},
    • doi = {10.1364/OFC.2020.Th1A.1},
    • isbn = {978-1-943580-71-2},
    • url = {https://www.merl.com/publications/TR2020-025}
    • }
  •  Jha, D.K., Kolaric, P., Romeres, D., Raghunathan, A., Benosman, M., Nikovski, D.N., "Robust Optimization for Trajectory-Centric Model-based Reinforcement Learning", NeurIPS Workshop on Safety and Robustness in Decision Making, December 2019.
    BibTeX TR2019-156 PDF
    • @inproceedings{Jha2019dec2,
    • author = {Jha, Devesh K. and Kolaric, Patrik and Romeres, Diego and Raghunathan, Arvind and Benosman, Mouhacine and Nikovski, Daniel N.},
    • title = {{Robust Optimization for Trajectory-Centric Model-based Reinforcement Learning}},
    • booktitle = {NeurIPS Workshop on Safety and Robustness in Decision Making},
    • year = 2019,
    • month = dec,
    • url = {https://www.merl.com/publications/TR2019-156}
    • }
  •  Jha, D.K., Raghunathan, A., Romeres, D., "QNTRPO: Including Curvature in TRPO", Optimization Foundations for Reinforcement Learning Workshop at NeurIPS, December 2019.
    BibTeX TR2019-154 PDF Software
    • @inproceedings{Jha2019dec,
    • author = {Jha, Devesh K. and Raghunathan, Arvind and Romeres, Diego},
    • title = {{QNTRPO: Including Curvature in TRPO}},
    • booktitle = {Optimization Foundations for Reinforcement Learning Workshop at NeurIPS},
    • year = 2019,
    • month = dec,
    • url = {https://www.merl.com/publications/TR2019-154}
    • }
  •  Ota, K., Jha, D.K., Oiki, T., Miura, M., Nammoto, T., Nikovski, D., Mariyama, T., "Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), DOI: 10.1109/​IROS40897.2019.8968010, November 2019, pp. 3487-3494.
    BibTeX TR2019-129 PDF
    • @inproceedings{Ota2019nov,
    • author = {Ota, Kei and Jha, Devesh K. and Oiki, Tomohiro and Miura, Mamoru and Nammoto, Takashi and Nikovski, Daniel and Mariyama, Toshisada},
    • title = {{Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning}},
    • booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
    • year = 2019,
    • pages = {3487--3494},
    • month = nov,
    • publisher = {IEEE},
    • doi = {10.1109/IROS40897.2019.8968010},
    • issn = {2153-0866},
    • isbn = {978-1-7281-4004-9},
    • url = {https://www.merl.com/publications/TR2019-129}
    • }
  •  Jha, D.K., Raghunathan, A., Romeres, D., "Quasi-Newton Trust Region Policy Optimization", Conference on Robot Learning (CoRL), Leslie Pack Kaelbling and Danica Kragic and Komei Sugiura, Eds., October 2019, pp. 945-954.
    BibTeX TR2019-120 PDF Software
    • @inproceedings{Jha2019oct,
    • author = {Jha, Devesh K. and Raghunathan, Arvind and Romeres, Diego},
    • title = {{Quasi-Newton Trust Region Policy Optimization}},
    • booktitle = {Conference on Robot Learning (CoRL)},
    • year = 2019,
    • editor = {Leslie Pack Kaelbling and Danica Kragic and Komei Sugiura},
    • pages = {945--954},
    • month = oct,
    • publisher = {Proceedings of Machine Learning Research},
    • url = {https://www.merl.com/publications/TR2019-120}
    • }
  •  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}
    • }
  •  Chakrabarty, A., Jha, D.K., Wang, Y., "Data-Driven Control Policies for Partially Known Systems via Kernelized Lipschitz Learning", American Control Conference (ACC), DOI: 10.23919/​ACC.2019.8815325, July 2019, pp. 4192-4197.
    BibTeX TR2019-047 PDF
    • @inproceedings{Chakrabarty2019jul,
    • author = {Chakrabarty, Ankush and Jha, Devesh K. and Wang, Yebin},
    • title = {{Data-Driven Control Policies for Partially Known Systems via Kernelized Lipschitz Learning}},
    • booktitle = {American Control Conference (ACC)},
    • year = 2019,
    • pages = {4192--4197},
    • month = jul,
    • publisher = {IEEE},
    • doi = {10.23919/ACC.2019.8815325},
    • url = {https://www.merl.com/publications/TR2019-047}
    • }
  •  Romeres, D., Jha, D.K., Dau, H., Yerazunis, W.S., Nikovski, D.N., "Anomaly Detection for Insertion Tasks in Robotic Assembly Using Gaussian Process Models", European Control Conference (ECC), DOI: 10.23919/​ECC.2019.8795698, June 2019, pp. 1017-1022.
    BibTeX TR2019-055 PDF
    • @inproceedings{Romeres2019jun,
    • author = {Romeres, Diego and Jha, Devesh K. and Dau, Hoang and Yerazunis, William S. and Nikovski, Daniel N.},
    • title = {{Anomaly Detection for Insertion Tasks in Robotic Assembly Using Gaussian Process Models}},
    • booktitle = {European Control Conference (ECC)},
    • year = 2019,
    • pages = {1017--1022},
    • month = jun,
    • publisher = {IEEE},
    • doi = {10.23919/ECC.2019.8795698},
    • isbn = {978-3-907144-00-8},
    • url = {https://www.merl.com/publications/TR2019-055}
    • }