# Volkan Cevher

#### Associate Professor

volkan.cevher@epfl.ch +41 21 693 11 01 http://lions.epfl.ch

**EPFL STI IEL LIONS **

ELE 233 (Bâtiment ELE)

Station 11

CH-1015 Lausanne

+41 21 693 11 01

+41 21 693 11 74

Office: ELE 233

EPFL > STI > IEL > LIONS

Web site: Web site: https://lions.epfl.ch

### Fields of expertise

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 machine learning, signal processing theory, optimization theory and methods, and information theory. Dr. Cevher is an ELLIS fellow and was the recipient of the 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

### Infoscience publications

#### Selected Publications

**Machine Learning From Distributed, Streaming Data [From the Guest Editors]**;

*Ieee Signal Processing Magazine*. 2020-05-01. DOI : 10.1109/MSP.2020.2972654.

**Optimization for Reinforcement Learning: From a single agent to cooperative agents**;

*Ieee Signal Processing Magazine*. 2020-05-01. DOI : 10.1109/MSP.2020.2976000.

**Lipschitz constant estimation for Neural Networks via sparse polynomial optimization**. 2020-04-26. 8th International Conference on Learning Representations, Addis Ababa, ETHIOPIA, April 26-30, 2020.

**A reflected forward-backward splitting method for monotone inclusions involving Lipschitzian operators**;

*Set-valued and Variational analysis*. 2020-03-19.

**Robust Reinforcement Learning via Adversarial training with Langevin Dynamics**. 2020-02-14.

**Scalable Learning-Based Sampling Optimization For Compressive Dynamic MRI**. 2020. International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 4-8, 2020.

**Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections**;

*Journal of Machine Learning Research*. 2020.

**Personalizable intervention systems to promote healthy behavior change**. Lausanne, EPFL, 2020. DOI : 10.5075/epfl-thesis-10008.

**Scalable Semidefinite Programming**. 2019-12-06.

**Interactive Teaching Algorithms for Inverse Reinforcement Learning**. 2019-08-10. The 28th International Joint Conference on Artificial Intelligence, 2019., Macao, China, August 10-16, 2019.

**Interactive Teaching Algorithms for Inverse Reinforcement Learning**. 2019-08-10. 28th International Joint Conference on Artificial Intelligence, 2019., Macao, China, August 10-16, 2019.

**Chemical machine learning with kernels: The impact of loss functions**;

*International Journal Of Quantum Chemistry*. 2019-05-05. DOI : 10.1002/qua.25872.

**Inertial Three-Operator Splitting Method and Applications**; SIAM Conference on Optimization - OP17, Vancouver, British Columbia, Canada, May 22-25, 2017.

**Ultrasensitive hyperspectral imaging and biodetection enabled by dielectric metasurfaces**;

*Nature Photonics*. 2019-04-01. DOI : 10.1038/s41566-019-0394-6.

**On the convergence of stochastic primal-dual hybrid gradient**. 2019.

**An adaptive primal-dual framework for nonsmooth convex minimization**;

*Mathematical Programming Computation*. 2019. DOI : 10.1007/s12532-019-00173-3.

**Data-driven Measurement Designs for Magnetic Resonance Imaging**. Lausanne, EPFL, 2019. DOI : 10.5075/epfl-thesis-9651.

**Streaming Low-Rank Matrix Approximation With An Application To Scientific Simulation**;

*SIAM Journal on Scientific Computing*. 2019-01-01. DOI : 10.1137/18M1201068.

**Stochastic Frank-Wolfe for Composite Convex Minimization**. 2019. NeurIPS 2019 : Thirty-third Conference on Neural Information Processing Systems, Vancouver, Canada, December 8-14, 2019.

**An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints**. 2019. NeurIPS 2019 : Thirty-third Conference on Neural Information Processing Systems, Vancouver, Canada, December 8-14, 2019.

**Fast and Provable ADMM for Learning with Generative Priors**. 2019. NeurIPS 2019 : Thirty-third Conference on Neural Information Processing Systems, Vancouver, Canada, December 8-14, 2019.

**UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization**. 2019. NeurIPS 2019 : Thirty-third Conference on Neural Information Processing Systems, Vancouver, Canada, December 8-14, 2019.

**Scalable Convex Optimization Methods for Semidefinite Programming**. Lausanne, EPFL, 2019. DOI : 10.5075/epfl-thesis-9598.

**On Certifying Non-Uniform Bounds against Adversarial Attacks**. 2019. 36th International Conference on Machine Learning (ICML)'2019, Long Beach, USA, June 9-15, 2019.

**Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator**. 2019. 36th International Conference on Machine Learning (ICML 2019), Long Beach, USA, June 9-15, 2019.

**Efficient learning of smooth probability functions from Bernoulli tests with guarantees.**. 2019. 36th International Conference on Machine Learning (ICML 2019), Long Beach, USA, June 9-15, 2019.

**A Conditional Gradient-Based Augmented Lagrangian Framework**. 2019. 36th International Conference on Machine Learning (ICML 2019), Long Beach, USA, June 9-15, 2019.

**Almost surely constrained convex optimization**. 2019. 36th International Conference on Machine Learning (ICML 2019), Long Beach, USA, June 9-15, 2019.

**Rethinking Sampling in Parallel MRI: A Data-Driven Approach**. 2019.

**Overlapping Multi-Bandit Best Arm Identification**. 2019. The 2019 IEEE International Symposium on Information Theory (ISIT), Paris, France, July 7-12, 2019. p. 2544-2548. DOI : 10.1109/ISIT.2019.8849327.

**Iterative Classroom Teaching**. 2019. 33rd AAAI Conference on Artificial Intelligence / 31st Innovative Applications of Artificial Intelligence Conference / 9th AAAI Symposium on Educational Advances in Artificial Intelligence, Honolulu, Hawaii, USA, January 27 – February 1, 2019. p. 5684-5692.

**A Learning-Based Framework for Quantized Compressed Sensing**;

*IEEE Signal Processing Letters*. 2019. DOI : 10.1109/LSP.2019.2898350.

**Robust Adaptive Decision Making: Bayesian Optimization and Beyond**. Lausanne, EPFL, 2019. DOI : 10.5075/epfl-thesis-9147.

**An Introductory Guide to Fano's Inequality with Applications in Statistical Estimation**;

*Information-Theoretic Methods in Data Science*; Cambridge University Press, 2019.

**Convergence of the Exponentiated Gradient Method with Armijo Line Search**;

*Journal of Optimization Theory and Applications*. 2018-12-03. DOI : 10.1007/s10957-018-1428-9.

**A Single-Phase, Proximal Path-Following Framework**;

*Mathematics Of Operations Research*. 2018-11-01. DOI : 10.1287/moor.2017.0907.

**Optimal Rates for Spectral Algorithms with Least-Squares Regression over Hilbert Spaces**;

*Applied and Computational Harmonic Analysis*. 2018-10-04. DOI : 10.1016/j.acha.2018.09.009.

**Near-Optimal Noisy Group Testing via Separate Decoding of Items**;

*IEEE Journal of Selected Topics In Signal Processing*. 2018-10-01. DOI : 10.1109/JSTSP.2018.2844818.

**On the linear convergence of the stochastic gradient method with constant step-size**;

*Optimization Letters*. 2018-09-25. DOI : 10.1007/s11590-018-1331-1.

**Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms**. 2018-09-03.

**A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming**. 2018-07-11. the 35th International Conference on Machine Learning (ICML), Stockholm, Sweden, July 10-15, 2018.

**Online Adaptive Methods, Universality and Acceleration**. 2018-07-04. 32nd Conference on Neural Information Processing Systems conference (NIPS 2018), Montreal, Canada, December 3-8, 2018.

**Near-Optimal Noisy Group Testing via Separate Decoding of Items**. 2018-06-17. IEEE International Symposium on Information Theory, Colorado, USA., June 17-22. 2018. p. 2311-2315.

**Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods**. 2018-06-08. 35th International Conference on Machine Learning, Stockholm, Sweden, July 10 -15, 2018.

**Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces**. 2018-03-11. 35th International Conference on Machine Learning (ICML), Stockholm, Sweden, July 10-15, 2018.

**A Smooth Primal-Dual Optimization Framework for Nonsmooth Composite Convex Minimization**;

*SIAM Journal on Optimization*. 2018-01-11. DOI : 10.1137/16M1093094.

**Adversarially Robust Optimization with Gaussian Processes**. 2018-01-01. 32nd Conference on Neural Information Processing Systems (NIPS), Montreal, CANADA, Dec 02-08, 2018.

**Online Adaptive Methods, Universality and Acceleration**. 2018-01-01. 32nd Conference on Neural Information Processing Systems (NIPS), Montreal, CANADA, Dec 02-08, 2018.

**Mirrored Langevin Dynamics**. 2018-01-01. 32nd Conference on Neural Information Processing Systems (NIPS), Montreal, CANADA, Dec 02-08, 2018.

**An area and power efficient on-the-fly LBCS transformation for implantable neuronal signal acquisition systems**. 2018-01-01. 15th ACM International Conference on Computing Frontiers, Ischia, ITALY, May 08-10, 2018. p. 228-231. DOI : 10.1145/3203217.3203260.

**Smoothing Alternating Direction Methods for Fully Nonsmooth Constrained Convex Optimization**;

*Large-Scale and Distributed Optimization*; Springer, 2018.

**Sparse Linear Inversion for Strong Gravitational Lenses Reconstruction, Component Separation from Morphological Component Analysis with Multiple Discrimination Criteria**. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8965.

**Adversarially Robust Optimization with Gaussian Processes**. 2018. Conference on Neural Information Processing Systems (NIPS), Montreal, 2018.

**Finding Mixed Nash Equilibria of Generative Adversarial Networks**. 2018. IEEE International Conference on Machine Learning (ICML)’ 2019, Long Beach, USA, June 9-15, 2019.

**Real-time DCT Learning-based Reconstruction of Neural Signals**. 2018. 26th European Signal Processing Conference (EUSIPCO 2018), Rome, Italy , September 3-7. 2018. DOI : 10.23919/EUSIPCO.2018.8553402.

**Adaptive Learning-Based Compressive Sampling for Low-power Wireless Implants**. 2018. 1st International Symposium on Integrated Circuits and Systems (ISICAS), Taormina, Italy, September 02-03, 2018. p. 3929-3941. DOI : 10.1109/TCSI.2018.2853983.

**An area and power efficient on-the-fly LBCS transformation for implantable neuronal signal acquisition systems**. 2018. ACM International Conference on Computing Frontiers 2018, Ischia, Italy, May 8-10, 2018.

**Learning-Based Hardware Design for Data Acquisition Systems**. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8693.

**Learning without Smoothness and Strong Convexity**. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8765.

**Learning with Structured Sparsity: From Discrete to Convex and Back.**. EPFL, 2018. DOI : 10.5075/epfl-thesis-8516.

**Learning-Based Compressive MRI**;

*IEEE Transactions On Medical Imaging*. 2018. DOI : 10.1109/TMI.2018.2832540.

**Mirrored Langevin Dynamics**. 2018. Thirty-second Conference on Neural Information Processing Systems (NIPS), Montréal.

**Dimension-free Information Concentration via Exp-Concavity**. 2018. Algorithmic Learning Theory (ALT) 2018, Lanzarote, Spain, April 7-9, 2018.

**Robust Maximization of Non-Submodular Objectives**. 2018. International Conference on Artificial Intelligence and Statistics (AISTATS), Lanzarote, Canary Islands, April, 9-11, 2018.

**High Dimensional Bayesian Optimization via Additive Models with Overlapping Groups**. 2018. AISTATS, Lanzarote, Spain, April, 9-11, 2018.

**Stochastic Three-Composite Convex Minimization with a Linear Operator**. 2018. 21st International Conference on Artificial Intelligence and Statistics (AISTATS) 2018,, Lanzarotte, Spain, April 9-11, 2018.

**Let’s be honest: An optimal no-regret framework for zero-sum games**. 2018. 35th International Conference on Machine Learning (ICML), Stockholm, Sweden, July 10-15, 2018.

**Chemical machine learning with kernels: The key impact of loss functions**. 2018.

**An Eight lanes 7Gb/s/pin Source Synchronous Single-Ended RX with Equalization and Far-End Crosstalk Cancellation for Backplane Channels**;

*IEEE Journal of Solid State Circuits*. 2018. DOI : 10.1109/JSSC.2017.2783679.

**A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization**;

*IEEE Transactions on Signal Processing*. 2018. DOI : 10.1109/TSP.2018.2870353.

**Stochastic Forward-Douglas-Rachford Splitting for Monotone Inclusions**;

*Stochastic Forward Douglas-Rachford Splitting Method for Monotone Inclusions*; Springer International Publishing, 2018.

**Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data**. 2017-12-04. 31st Annual Conference on Neural Information Processing Systems (NIPS), Long Beach, California, USA, December 4-9, 2017.

**Practical Sketching Algorithms For Low-Rank Matrix Approximation**;

*Siam Journal On Matrix Analysis And Applications*. 2017. DOI : 10.1137/17M1111590.

**Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach**. 2017. Conference on Neural Information Processing Systems (NIPS), Long Beach.

**Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization**. 2017. 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA, December 4-9, 2017.

**A Distributed Algorithm for Partitioned Robust Submodular Maximization**. 2017. IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

**Phase Transitions in the Pooled Data Problem**. 2017. Conference on Neural Information Processing Systems (NIPS), Long Beach, California, December 2017.

**Efficient and Near-Optimal Noisy Group Testing: An Information-Theoretic Framework**;

*IEEE Journal of Selected Topics in Signal Processing*. 2017.

**Combinatorial Penalties: Which structures are preserved by convex relaxations?**. 2017. 21st International Conference on Artificial Intelligence and Statistics (AISTATS), Lanzarotte, Spain , April 9-11, 2017.

**General Proximal Gradient Method: A Case for Non-Euclidean Norms**. 2017.

**Smoothing technique for nonsmooth composite minimization with linear operator**;

*Preprint*. 2017.

**Robust Submodular Maximization: A Non-Uniform Partitioning Approach**. 2017. The 34th International Conference on Machine Learning (ICML), Sydney, 2017.

**Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization**. 2017. Conference on Learning Theory (COLT)Conference on Learning Theory (COLT), AmsterdamAmsterdam, Netherlands, July 2017July, 7-10, 2017.

**DCT Learning-Based Hardware Design for Neural Signal Acquisition Systems**. 2017. Computing Frontiers Conference 2017, Siena, Italy, May 15-17, 2017. p. 391-394. DOI : 10.1145/3075564.3078890.

**Learning-based subsampling**. US10082551 ; US2017109650 . 2017.

**An Adaptive Sublinear-Time Block Sparse Fourier Transform**. 2017. ACM Symposium on Theory of Computing (STOC), Montreal, June 19-23, 2017.

**Faster Coordinate Descent via Adaptive Importance Sampling**. 2017. 20th International Conference on Artificial Intelligence and Statistics (AISTATS) 2017, Fort Lauderdale, Florida, USA, April 20-22, 2017.

**Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage**. 2017. 20th International Conference on Artificial Intelligence and Statistics (AISTATS2017), Fort Lauderdale, Florida, USA, April 20-22, 2017.

**How little does non-exact recovery help in group testing?**. 2017. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, March 2017. p. 6090-6094.

**A single-phase, proximal path-following framework**;

*Mathematics of Operations Research*. 2017.

**Lower Bounds on Active Learning for Graphical Model Selection**. 2017. The 20th International Conference on Artificial Intelligence and Statistics (AISTATS 2017), Fort Lauderdale, Florida, USA, April 20-22, 2017.

**Limits on Support Recovery With Probabilistic Models: An Information-Theoretic Framework**;

*IEEE Transactions on Information Theory*. 2017. DOI : 10.1109/TIT.2016.2606605.

**An Efficient Streaming Algorithm for the Submodular Cover Problem**. 2016. The Thirtieth Annual Conference on Neural Information Processing Systems (NIPS).

**Stochastic Three-Composite Convex Minimization**. 2016. 30th Conference on Neural Information Processing Systems (NIPS2016), Barcelona, Spain, December 5-10, 2016.

**Randomized Single-View Algorithms for Low-Rank Matrix Approximation**. 2016.

**Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation**. 2016. Conference on Neural Information Processing Systems (NIPS), Barcelona, December 5-10, 2016.

**Efficient Incremental Data Analysis**. Lausanne, EPFL, 2016. DOI : 10.5075/epfl-thesis-7183.

**Convex block-sparse linear regression with expanders - provably**. 2016. The 19th International Conference on Artificial Intelligence and Statistics (AISTATS 2016), Cadiz, Spain, May 7-11, 2016.

**From Massive Parallelization to Quantum Computing: Seven Novel Approaches to Query Optimization**. Lausanne, EPFL, 2016. DOI : 10.5075/epfl-thesis-6995.

**Estimation Error of the Constrained Lasso**. 2016. 54th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, September 27-30, 2016.

### Teaching & PhD

#### Teaching

Electrical and Electronics Engineering