Cenk Baykal

According to our database, Cenk Baykal authored at least 31 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

SLaM: Student-Label Mixing for Semi-Supervised Knowledge Distillation.

Vasilis Kontonis, Fotis Iliopoulos, Khoa Trinh, Cenk Baykal, Gaurav Menghani, Erik Vee

CoRR, 2023

The Power of External Memory in Increasing Predictive Model Capacity.

Cenk Baykal, Dylan J. Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang

CoRR, 2023

Alternating Updates for Efficient Transformers.

Cenk Baykal, Dylan J. Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang

CoRR, 2023

SLaM: Student-Label Mixing for Distillation with Unlabeled Examples.

Vasilis Kontonis, Fotis Iliopoulos, Khoa Trinh, Cenk Baykal, Gaurav Menghani, Erik Vee

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Alternating Updates for Efficient Transformers.

Cenk Baykal, Dylan J. Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Robust Active Distillation.

Cenk Baykal, Khoa Trinh, Fotis Iliopoulos, Gaurav Menghani, Erik Vee

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Sensitivity-Informed Provable Pruning of Neural Networks.

Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski, Dan Feldman, Daniela Rus

SIAM J. Math. Data Sci., 2022

Bandit Sampling for Multiplex Networks.

Cenk Baykal, Vamsi K. Potluru, Sameena Shah, Manuela M. Veloso

CoRR, 2022

Weighted Distillation with Unlabeled Examples.

Fotis Iliopoulos, Vasilis Kontonis, Cenk Baykal, Gaurav Menghani, Khoa Trinh, Erik Vee

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Theoretical View on Sparsely Activated Networks.

Cenk Baykal, Nishanth Dikkala, Rina Panigrahy, Cyrus Rashtchian, Xin Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Sampling-based Algorithms for Fast and Deployable AI.

Cenk Baykal

PhD thesis, 2021

On coresets for support vector machines.

Murad Tukan, Cenk Baykal, Dan Feldman, Daniela Rus

Theor. Comput. Sci., 2021

Graph Belief Propagation Networks.

Junteng Jia, Cenk Baykal, Vamsi K. Potluru, Austin R. Benson

CoRR, 2021

Low-Regret Active learning.

Cenk Baykal, Lucas Liebenwein, Dan Feldman, Daniela Rus

CoRR, 2021

Lost in Pruning: The Effects of Pruning Neural Networks beyond Test Accuracy.

Lucas Liebenwein, Cenk Baykal, Brandon Carter, David Gifford, Daniela Rus

Proceedings of Machine Learning and Systems 2021, 2021

2020

Provable Filter Pruning for Efficient Neural Networks.

Lucas Liebenwein, Cenk Baykal, Harry Lang, Dan Feldman, Daniela Rus

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Resilient Multi-Agent Consensus Using Wi-Fi Signals.

Stephanie Gil, Cenk Baykal, Daniela Rus

IEEE Control. Syst. Lett., 2019

SiPPing Neural Networks: Sensitivity-informed Provable Pruning of Neural Networks.

Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski, Dan Feldman, Daniela Rus

CoRR, 2019

Asymptotically optimal kinematic design of robots using motion planning.

Cenk Baykal, Chris Bowen, Ron Alterovitz

Auton. Robots, 2019

Deterministic Coresets for Stochastic Matrices with Applications to Scalable Sparse PageRank.

Harry Lang, Cenk Baykal, Najib Abu Samra, Tony Tannous, Dan Feldman, Daniela Rus

Proceedings of the Theory and Applications of Models of Computation, 2019

Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds.

Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski, Dan Feldman, Daniela Rus

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Sampling-Based Approximation Algorithms for Reachability Analysis with Provable Guarantees.

Lucas Liebenwein, Cenk Baykal, Igor Gilitschenski, Sertac Karaman, Daniela Rus

Proceedings of the Robotics: Science and Systems XIV, 2018

Kinematic Design Optimization of a Parallel Surgical Robot to Maximize Anatomical Visibility via Motion Planning.

Alan Kuntz, Chris Bowen, Cenk Baykal, Arthur W. Mahoney, Patrick L. Anderson, Fabien Maldonado, Robert J. Webster III, Ron Alterovitz

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

2017

Training Support Vector Machines using Coresets.

Cenk Baykal, Lucas Liebenwein, Wilko Schwarting

CoRR, 2017

Detection of AQM on Paths using Machine Learning Methods.

Cenk Baykal, Wilko Schwarting, Alex Wallar

CoRR, 2017

Asymptotically Optimal Design of Piecewise Cylindrical Robots using Motion Planning.

Cenk Baykal, Ron Alterovitz

Proceedings of the Robotics: Science and Systems XIII, 2017

Persistent surveillance of events with unknown, time-varying statistics.

Cenk Baykal, Guy Rosman, Sebastian Claici, Daniela Rus

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

2016

Persistent Surveillance of Events with Unknown Rate Statistics.

Cenk Baykal, Guy Rosman, Kyle Kotowick, Mark Donahue, Daniela Rus

Proceedings of the Algorithmic Foundations of Robotics XII, 2016

2015

Optimizing design parameters for sets of concentric tube robots using sampling-based motion planning.

Cenk Baykal, Luis G. Torres, Ron Alterovitz

Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

2014

Interactive-rate motion planning for concentric tube robots.

Luis G. Torres, Cenk Baykal, Ron Alterovitz

Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

Participatory route planning.

David Wilkie, Cenk Baykal, Ming C. Lin

Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2014