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Research Interests:
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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. He was also a Faculty Fellow in the Electrical and Computer Engineering Department at Rice University from 2010-2020. Currently, he is an Associate Professor at the Swiss Federal Institute of Technology Lausanne and an Amazon Scholar. His research interests include machine learning, optimization theory and methods, and automated control. Dr. Cevher is an IEEE Fellow (’24), an ELLIS fellow, and was the recipient of the ICML AdvML Best Paper Award in 2023, Google Faculty Research award in 2018, the 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)
Learning to Remove Cuts in Integer Linear Programming
2024. 41st International Conference on Machine Learning (ICML 2024).Generalization of Scaled Deep ResNets in the Mean-Field Regime
2024. 12th International Conference on Learning Representations (ICLR 2024).Efficient local linearity regularization to overcome catastrophic overfitting
2024. 12th International Conference on Learning Representations (ICLR 2024).Robust NAS under adversarial training: benchmark, theory, and beyond
2024. 12th International Conference on Learning Representations (ICLR 2024).High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization
2024. 12th International Conference on Learning Representations (ICLR 2024).Improving SAM Requires Rethinking its Optimization Formulation
2024. 41st International Conference on Machine Learning (ICML 2024).Revisiting Character-level Adversarial Attacks for Language Models
2024. 41st International Conference on Machine Learning (ICML 2024).Imitation Learning in Discounted Linear MDPs without exploration assumptions
2024. 41st International Conference on Machine Learning (ICML 2024).Efficient Continual Finite-Sum Minimization
2024. 12th International Conference on Learning Representations (ICLR 2024).On the Generalization of Stochastic Gradient Descent with Momentum
Journal Of Machine Learning Research. 2024. Vol. 25, p. 1 – 56.Graph generative deep learning models with an application to circuit topologies
Lausanne, EPFL, 2024.Stable Nonconvex-Nonconcave Training via Linear Interpolation
2023. Thirty-seventh Conference on Neural Information Processing Systems.Regularization of polynomial networks for image recognition
2023. Computer Vision and Pattern Recognition Conference (CVPR).Distributed Extra-Gradient With Optimal Complexity And Communication Guarantees
2023. 11th International Conference on Learning Representations (ICLR).Finding Actual Descent Directions For Adversarial Training
2023. 11th International Conference on Learning Representations (ICLR).Maximum Independent Set: Self-Training through Dynamic Programming
2023. 37th Conference on Neural Information Processing Systems (NeurIPS 2023)..What can online reinforcement learning with function approximation benefitfrom general coverage conditions
2023. 40th International Conference on Machine Learning (ICML).On the Convergence of Encoder-only Shallow Transformers
2023. 37th Annual Conference on Neural Information Processing Systems.Semi Bandit Dynamics in Congestion Games: Convergence to Nash Equilibrium and No-Regret Guarantees.
2023. 40th International Conference on Machine Learning (ICML).When do Minimax-fair Learning and Empirical Risk Minimization Coincide?
2023. 40th International Conference on Machine Learning (ICML), Honolulu, Hawaii, USA, July 23-29, 2023.Access map
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