Cenk Baykal
Cenk Baykal
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Cited by
Cited by
Provable filter pruning for efficient neural networks
L Liebenwein*, C Baykal*, H Lang, D Feldman, D Rus
arXiv preprint arXiv:1911.07412, 2019
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
Lost in pruning: The effects of pruning neural networks beyond test accuracy
L Liebenwein, C Baykal, B Carter, D Gifford, D Rus
Proceedings of Machine Learning and Systems 3, 93-138, 2021
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
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
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
Asymptotically Optimal Design of Piecewise Cylindrical Robots using Motion Planning.
C Baykal, R Alterovitz
Robotics: science and systems 2017, 2017
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
Asymptotically optimal kinematic design of robots using motion planning
C Baykal, C Bowen, R Alterovitz
Autonomous robots 43 (2), 345-357, 2019
Sampling-based approximation algorithms for reachability analysis with provable guarantees
L Liebenwein*, C Baykal*, I Gilitschenski, S Karaman, D Rus
Resilient multi-agent consensus using wi-fi signals
S Gil, C Baykal, D Rus
IEEE control systems letters 3 (1), 126-131, 2018
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
Participatory route planning
D Wilkie, C Baykal, MC Lin
Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances …, 2014
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
A theoretical view on sparsely activated networks
C Baykal, N Dikkala, R Panigrahy, C Rashtchian, X Wang
Advances in Neural Information Processing Systems 35, 30071-30084, 2022
Robust active distillation
C Baykal, K Trinh, F Iliopoulos, G Menghani, E Vee
arXiv preprint arXiv:2210.01213, 2022
Graph belief propagation networks
J Jia, C Baykal, VK Potluru, AR Benson
arXiv preprint arXiv:2106.03033, 2021
Weighted distillation with unlabeled examples
F Iliopoulos, V Kontonis, C Baykal, G Menghani, K Trinh, E Vee
Advances in Neural Information Processing Systems 35, 7024-7037, 2022
Training support vector machines using coresets
C Baykal, L Liebenwein, W Schwarting
arXiv preprint arXiv:1708.03835, 2017
Persistent Surveillance of Events with Unknown Rate Statistics
C Baykal, G Rosman, K Kotowick, M Donahue, D Rus
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