Prof. Volkan Cevher

Research Interests:

  • Machine Learning
  • Optimization
  • Signal Processing
  • Information Theory

Biography

Volkan Cevher received the B.Sc. (valedictorian) in electrical engineering from Bilkent University in Ankara, Turkey, in 1999 and the Ph.D. in electrical and computer engineering from the Georgia Institute of Technology in Atlanta, GA in 2005. He was a Research Scientist with the University of Maryland, College Park from 2006-2007 and also with Rice University in Houston, TX, from 2008-2009. Currently, he is an Associate Professor at the Swiss Federal Institute of Technology Lausanne and a Faculty Fellow in the Electrical and Computer Engineering Department at Rice University. His research interests include signal processing theory, machine learning, convex optimization, and information theory. Dr. Cevher is an ELLIS fellow and was the recipient of the Google Faculty Research Award on Machine Learning in 2018, IEEE Signal Processing Society Best Paper Award in 2016, a Best Paper Award at CAMSAP in 2015, a Best Paper Award at SPARS in 2009, and an ERC CG in 2016 as well as an ERC StG in 2011.

Publications (most recent)

Stable Nonconvex-Nonconcave Training via Linear Interpolation

T. M. Pethick; W. Xie; V. Cevher 

2023-09-21. Thirty-seventh Conference on Neural Information Processing Systems, New Orleans, Louisiana, USA, December 10-16, 2023.

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Semi Bandit Dynamics in Congestion Games: Convergence to Nash Equilibrium and No-Regret Guarantees.

I. Panageas; E. P. Skoulakis; L. Viano; X. Wang; V. Cevher 

2023. 40th International Conference on Machine Learning (ICML), Honolulu, Hawaii, USA, July, 23-29, 2023.

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Benign Overfitting in Deep Neural Networks under Lazy Training

Z. Zhu; F. Liu; G. Chrysos; F. Locatello; V. Cevher 

2023. 40th International Conference on Machine Learning (ICML), Honolulu, Hawaii, USA, July, 23-29, 2023.

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What can online reinforcement learning with function approximation benefitfrom general coverage conditions

F. Liu; L. Viano; V. Cevher 

2023. 40th International Conference on Machine Learning (ICML), Honolulu, Hawaii, USA, July, 23-29, 2023.

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Universal and adaptive methods for robust stochastic optimization

A. Kavis / V. Cevher (Dir.)  

Lausanne, EPFL, 2023. 

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Contact

e-mail address: [email protected]

telephone: 0041 21 6930111

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