![]() |
Research Interests:
|
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)
Adaptive Bilevel Optimization
ACM / IMS Journal of Data Science. 2025. DOI : 10.1145/3728478.How Gradient Descent Balances Features: A Dynamical Analysis For Two-Layer Neural Networks
2025. The Thirteenth International Conference on Learning Representations, Singapore, 2025-04-24-2025-04-28.Quantum-Peft: Ultra Parameter-Efficient Fine-Tuning
2025. The Thirteenth International Conference on Learning Representations, Singapore, 2025-04-24-2025-04-28.Certified Robustness Under Bounded Levenshtein Distance
2025. The Thirteenth International Conference on Learning Representations, Singapore, 2025-04-24-2025-04-28.Faster Inference Of Flow-Based Generative Models Via Improved Data-Noise Coupling
2025. The Thirteenth International Conference on Learning Representations, Singapore, 2025-04-24-2025-04-28.Efficient Interpolation Between Extragradient And Proximal Methods For Weak MVIS
2025. The Thirteenth International Conference on Learning Representations, Singapore, 2025-04-24-2025-04-28.Addressing Label Shift In Distributed Learning Via Entropy Regularization
2025. The Thirteenth International Conference on Learning Representations, Singapore, 2025-04-24-2025-04-28.Adversarial Training For Defense Against Label Poisoning Attacks
2025. The Thirteenth International Conference on Learning Representations, Singapore, 2025-04-24-2025-04-28.Hadamard product in deep learning: Introduction, Advances and Challenges
IEEE Transactions on Pattern Analysis and Machine Intelligence. 2025. DOI : 10.1109/TPAMI.2025.3560423.Membership Inference Attacks against Large Vision-Language Models
2024. 38th Annual Conference on Neural Information Processing Systems, Vancouver Convention Center, 2024-12-10 – 2024-12-15.SAMPa: Sharpness-aware Minimization Parallelized
38th Annual Conference on Neural Information Processing Systems, Vancouver, BC, Canada, 2024-12-10 – 2024-12-15.REST: Efficient and Accelerated EEG Seizure Analysis through Residual State Updates
2024. 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, 2024-07-21.Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations
2024. 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, 2024-07-21.Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks
Journal of Machine Learning Research. 2024. Vol. 25.Truly No-Regret Learning in Constrained MDPs
2024. 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, 2024-07-21. p. 36605 – 36653.Mixed Nash for Robust Federated Learning
Transactions on Machine Learning Research. 2024. Vol. 02.Universal Gradient Methods for Stochastic Convex Optimization
2024. 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, 2024-07-21.Generalization of Scaled Deep ResNets in the Mean-Field Regime
2024. 12th International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024.Efficient local linearity regularization to overcome catastrophic overfitting
2024. 12th International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024.On the Generalization of Stochastic Gradient Descent with Momentum
Journal Of Machine Learning Research. 2024. Vol. 25, p. 1 – 56.Access map
Additional links