Cenk Baykal
Title
Cited by
Cited by
Year
Interactive-rate motion planning for concentric tube robots
LG Torres, C Baykal, R Alterovitz
2014 IEEE International Conference on Robotics and Automation (ICRA), 1915-1921, 2014
442014
Data-dependent coresets for compressing neural networks with applications to generalization bounds
C Baykal*, L Liebenwein*, I Gilitschenski, D Feldman, D Rus
arXiv preprint arXiv:1804.05345, 2018
282018
Optimizing design parameters for sets of concentric tube robots using sampling-based motion planning
C Baykal, LG Torres, R Alterovitz
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015
252015
Provable filter pruning for efficient neural networks
L Liebenwein, C Baykal, H Lang, D Feldman, D Rus
arXiv preprint arXiv:1911.07412, 2019
162019
Asymptotically Optimal Design of Piecewise Cylindrical Robots using Motion Planning.
C Baykal, R Alterovitz
Robotics: Science and Systems 2017, 2017
162017
Asymptotically optimal kinematic design of robots using motion planning
C Baykal, C Bowen, R Alterovitz
Autonomous robots 43 (2), 345-357, 2019
112019
Sampling-based approximation algorithms for reachability analysis with provable guarantees
L Liebenwein*, C Baykal*, I Gilitschenski, S Karaman, D Rus
112018
Participatory route planning
D Wilkie, C Baykal, MC Lin
Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances …, 2014
112014
Resilient multi-agent consensus using wi-fi signals
S Gil, C Baykal, D Rus
IEEE control systems letters 3 (1), 126-131, 2018
92018
Kinematic design optimization of a parallel surgical robot to maximize anatomical visibility via motion planning
A Kuntz, C Bowen, C Baykal, AW Mahoney, PL Anderson, F Maldonado, ...
2018 IEEE International Conference on Robotics and Automation (ICRA), 926-933, 2018
72018
Training support vector machines using coresets
C Baykal, L Liebenwein, W Schwarting
arXiv preprint arXiv:1708.03835, 2017
52017
Persistent surveillance of events with unknown, time-varying statistics
C Baykal, G Rosman, S Claici, D Rus
2017 IEEE International Conference on Robotics and Automation (ICRA), 2682-2689, 2017
42017
SiPPing Neural Networks: Sensitivity-informed Provable Pruning of Neural Networks
C Baykal*, L Liebenwein*, I Gilitschenski, D Feldman, D Rus
arXiv preprint arXiv:1910.05422, 2019
32019
On coresets for support vector machines
M Tukan, C Baykal, D Feldman, D Rus
International Conference on Theory and Applications of Models of Computation …, 2020
22020
Persistent Surveillance of Events with Unknown Rate Statistics
C Baykal, G Rosman, K Kotowick, M Donahue, D Rus
2*2016
Deterministic Coresets for Stochastic Matrices with Applications to Scalable Sparse PageRank
H Lang*, C Baykal*, NA Samra, T Tannous, D Feldman, D Rus
International Conference on Theory and Applications of Models of Computation …, 2019
12019
Detection of AQM on Paths using Machine Learning Methods
C Baykal, W Schwarting, A Wallar
arXiv preprint arXiv:1707.02386, 2017
12017
Small Coresets to Represent Large Training Data for Support Vector Machines
C Baykal, M Tukan, D Feldman, D Rus
2018
Algorithms for persistent autonomy and surveillance
C Baykal
Massachusetts Institute of Technology, 2017
2017
Persistent Surveillance of Stochastic Events with Unknown Statistics
C Baykal
2016
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Articles 1–20