Cevher, Volkan

187 publications

TMLR 2026 Multi-Step Alignment as Markov Games: An Optimistic Online Mirror Descent Approach with Convergence Guarantees Yongtao Wu, Luca Viano, Kimon Antonakopoulos, Yihang Chen, Zhenyu Zhu, Quanquan Gu, Volkan Cevher

TMLR 2025 A Proximal Operator for Inducing 2:4-Sparsity Jonas M. Kübler, Yu-Xiang Wang, Shoham Sabach, Navid Ansari, Matthäus Kleindessner, Kailash Budhathoki, Volkan Cevher, George Karypis

ICML 2025 Accelerating Spectral Clustering Under Fairness Constraints Francesco Tonin, Alex Lambert, Johan Suykens, Volkan Cevher

ICLR 2025 Addressing Label Shift in Distributed Learning via Entropy Regularization Zhiyuan Wu, Changkyu Choi, Xiangcheng Cao, Volkan Cevher, Ali Ramezani-Kebrya

ICLR 2025 Adversarial Training for Defense Against Label Poisoning Attacks Melis Ilayda Bal, Volkan Cevher, Michael Muehlebach

NeurIPS 2025 Ascent Fails to Forget Ioannis Mavrothalassitis, Pol Puigdemont, Noam Itzhak Levi, Volkan Cevher

ICML 2025 Best of Both Worlds: Regret Minimization Versus Minimax Play Adrian Müller, Jon Schneider, Stratis Skoulakis, Luca Viano, Volkan Cevher

ICLR 2025 Certified Robustness Under Bounded Levenshtein Distance Elias Abad Rocamora, Grigorios Chrysos, Volkan Cevher

ICML 2025 Chameleon: A Flexible Data-Mixing Framework for Language Model Pretraining and Finetuning Wanyun Xie, Francesco Tonin, Volkan Cevher

ICLRW 2025 Chameleon: A Flexible Data-Mixing Framework for Language Model Pretraining and Finetuning Wanyun Xie, Francesco Tonin, Volkan Cevher

ICML 2025 Continuous-Time Analysis of Heavy Ball Momentum in Min-Max Games Yi Feng, Kaito Fujii, Stratis Skoulakis, Xiao Wang, Volkan Cevher

ICLR 2025 Efficient Interpolation Between Extragradient and Proximal Methods for Weak MVIs Thomas Pethick, Ioannis Mavrothalassitis, Volkan Cevher

NeurIPS 2025 Efficient Large Language Model Inference with Neural Block Linearization Mete Erdogan, Francesco Tonin, Volkan Cevher

ICLR 2025 Faster Inference of Flow-Based Generative Models via Improved Data-Noise Coupling Aram Davtyan, Leello Tadesse Dadi, Volkan Cevher, Paolo Favaro

ICML 2025 Generalization of Noisy SGD in Unbounded Non-Convex Settings Leello Tadesse Dadi, Volkan Cevher

NeurIPS 2025 Generalized Gradient Norm Clipping & Non-Euclidean $(L_0,L_1)$-Smoothness Thomas Pethick, Wanyun Xie, Mete Erdogan, Kimon Antonakopoulos, Tony Silveti-Falls, Volkan Cevher

ICLR 2025 How Gradient Descent Balances Features: A Dynamical Analysis for Two-Layer Neural Networks Zhenyu Zhu, Fanghui Liu, Volkan Cevher

ICML 2025 IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic Stefano Viel, Luca Viano, Volkan Cevher

ICLRW 2025 Improving Single Noise Level Denoising Samplers with Restricted Gaussian Oracles Leello Tadesse Dadi, Andrej Janchevski, Volkan Cevher

ICML 2025 Layer-Wise Quantization for Quantized Optimistic Dual Averaging Anh Duc Nguyen, Ilia Markov, Zhengqing Wu, Ali Ramezani-Kebrya, Kimon Antonakopoulos, Dan Alistarh, Volkan Cevher

NeurIPS 2025 Learning Equilibria from Data: Provably Efficient Multi-Agent Imitation Learning Till Freihaut, Luca Viano, Volkan Cevher, Matthieu Geist, Giorgia Ramponi

NeurIPS 2025 Linear Attention for Efficient Bidirectional Sequence Modeling Arshia Afzal, Elias Abad Rocamora, Leyla Naz Candogan, Pol Puigdemont, Francesco Tonin, Yongtao Wu, Mahsa Shoaran, Volkan Cevher

ICLR 2025 Quantum-PEFT: Ultra Parameter-Efficient Fine-Tuning Toshiaki Koike-Akino, Francesco Tonin, Yongtao Wu, Frank Zhengqing Wu, Leyla Naz Candogan, Volkan Cevher

NeurIPS 2025 Robustness in Both Domains: CLIP Needs a Robust Text Encoder Elias Abad Rocamora, Christian Schlarmann, Naman Deep Singh, Yongtao Wu, Matthias Hein, Volkan Cevher

TMLR 2025 Single-Pass Detection of Jailbreaking Input in Large Language Models Leyla Naz Candogan, Yongtao Wu, Elias Abad Rocamora, Grigorios Chrysos, Volkan Cevher

ICML 2025 Training Deep Learning Models with Norm-Constrained LMOs Thomas Pethick, Wanyun Xie, Kimon Antonakopoulos, Zhenyu Zhu, Antonio Silveti-Falls, Volkan Cevher

TMLR 2025 νSAM: Memory-Efficient Sharpness-Aware Minimization via Nuclear Norm Constraints Thomas Pethick, Parameswaran Raman, Lenon Minorics, Mingyi Hong, Shoham Sabach, Volkan Cevher

NeurIPS 2024 $\boldsymbol{\mu}\mathbf{P^2}$: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling Moritz Haas, Jin Xu, Volkan Cevher, Leena Chennuru Vankadara

ICLR 2024 Advancing the Lower Bounds: An Accelerated, Stochastic, Second-Order Method with Optimal Adaptation to Inexactness Artem Agafonov, Dmitry Kamzolov, Alexander Gasnikov, Ali Kavis, Kimon Antonakopoulos, Volkan Cevher, Martin Takáč

ICLR 2024 Adversarial Training Should Be Cast as a Non-Zero-Sum Game Alexander Robey, Fabian Latorre, George J. Pappas, Hamed Hassani, Volkan Cevher

ICMLW 2024 Certified Robustness in NLP Under Bounded Levenshtein Distance Elias Abad Rocamora, Grigorios Chrysos, Volkan Cevher

ICLRW 2024 Character-Level Robustness Should Be Revisited Elias Abad Rocamora, Yongtao Wu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

ICMLW 2024 Demonstrations in In-Context Learning for LLMs with Large Label Space Zhan Li, Fanghui Liu, Volkan Cevher, Grigorios Chrysos

ICMLW 2024 Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling Moritz Haas, Jin Xu, Volkan Cevher, Leena Chennuru Vankadara

ICLR 2024 Efficient Continual Finite-Sum Minimization Ioannis Mavrothalassitis, Stratis Skoulakis, Leello Tadesse Dadi, Volkan Cevher

ICLR 2024 Efficient Local Linearity Regularization to Overcome Catastrophic Overfitting Elias Abad Rocamora, Fanghui Liu, Grigorios Chrysos, Pablo M. Olmos, Volkan Cevher

ICLR 2024 Generalization of Scaled Deep ResNets in the Mean-Field Regime Yihang Chen, Fanghui Liu, Yiping Lu, Grigorios Chrysos, Volkan Cevher

ICML 2024 Going Beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations Justin Deschenaux, Igor Krawczuk, Grigorios Chrysos, Volkan Cevher

ICMLW 2024 Hardware-Efficient Quantization for Green Custom Foundation Models Toshiaki Koike-Akino, Chang Meng, Volkan Cevher, Giovanni De Micheli

ICML 2024 High-Dimensional Kernel Methods Under Covariate Shift: Data-Dependent Implicit Regularization Yihang Chen, Fanghui Liu, Taiji Suzuki, Volkan Cevher

NeurIPSW 2024 How Do Students Become Teachers: A Dynamical Analysis for Two-Layer Neural Networks Zhenyu Zhu, Fanghui Liu, Volkan Cevher

NeurIPSW 2024 Imbalance-Regularized LoRA: A Plug-and-Play Method for Improving Fine-Tuning of Foundation Models Zhenyu Zhu, Yongtao Wu, Quanquan Gu, Volkan Cevher

ICML 2024 Imitation Learning in Discounted Linear MDPs Without Exploration Assumptions Luca Viano, Stratis Skoulakis, Volkan Cevher

ICML 2024 Improving SAM Requires Rethinking Its Optimization Formulation Wanyun Xie, Fabian Latorre, Kimon Antonakopoulos, Thomas Pethick, Volkan Cevher

AISTATS 2024 Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate Ruichen Jiang, Parameswaran Raman, Shoham Sabach, Aryan Mokhtari, Mingyi Hong, Volkan Cevher

NeurIPSW 2024 Layer-Wise Quantization for Distributed Variational Inequalities Anh Duc Nguyen, Ilia Markov, Ali Ramezani-Kebrya, Kimon Antonakopoulos, Dan Alistarh, Volkan Cevher

ICML 2024 Learning to Remove Cuts in Integer Linear Programming Pol Puigdemont, Stratis Skoulakis, Grigorios Chrysos, Volkan Cevher

JMLR 2024 Learning with Norm Constrained, Over-Parameterized, Two-Layer Neural Networks Fanghui Liu, Leello Dadi, Volkan Cevher

ICLRW 2024 Leveraging Context in Jailbreaking Attacks Yixin Cheng, Markos Georgopoulos, Volkan Cevher, Grigorios Chrysos

ICML 2024 MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent Kaan Ozkara, Can Karakus, Parameswaran Raman, Mingyi Hong, Shoham Sabach, Branislav Kveton, Volkan Cevher

NeurIPS 2024 Membership Inference Attacks Against Large Vision-Language Models Zhan Li, Yongtao Wu, Yihang Chen, Francesco Tonin, Elias Abad Rocamora, Volkan Cevher

TMLR 2024 Mixed Nash for Robust Federated Learning Wanyun Xie, Thomas Pethick, Ali Ramezani-Kebrya, Volkan Cevher

ICLRW 2024 Multi-Resolution Graph Diffusion Mahdi Karami, Igor Krawczuk, Volkan Cevher

NeurIPSW 2024 Multi-Step Preference Optimization via Two-Player Markov Games Yongtao Wu, Luca Viano, Yihang Chen, Zhenyu Zhu, Quanquan Gu, Volkan Cevher

ICLR 2024 Multilinear Operator Networks Yixin Cheng, Grigorios Chrysos, Markos Georgopoulos, Volkan Cevher

NeurIPS 2024 On Feature Learning in Structured State Space Models Leena Chennuru Vankadara, Jin Xu, Moritz Haas, Volkan Cevher

JMLR 2024 On the Generalization of Stochastic Gradient Descent with Momentum Ali Ramezani-Kebrya, Kimon Antonakopoulos, Volkan Cevher, Ashish Khisti, Ben Liang

ICMLW 2024 Polynomial Convergence of Bandit No-Regret Dynamics in Congestion Games Leello Tadesse Dadi, Ioannis Panageas, Stratis Skoulakis, Luca Viano, Volkan Cevher

ICMLW 2024 Quantum-PEFT: Ultra Parameter-Efficient Fine-Tuning Toshiaki Koike-Akino, Francesco Tonin, Yongtao Wu, Leyla Naz Candogan, Volkan Cevher

ICML 2024 REST: Efficient and Accelerated EEG Seizure Analysis Through Residual State Updates Arshia Afzal, Grigorios Chrysos, Volkan Cevher, Mahsa Shoaran

NeurIPS 2024 Randomized Algorithms and PAC Bounds for Inverse Reinforcement Learning in Continuous Spaces Angeliki Kamoutsi, Peter Schmitt-Förster, Tobias Sutter, Volkan Cevher, John Lygeros

ICML 2024 Revisiting Character-Level Adversarial Attacks for Language Models Elias Abad Rocamora, Yongtao Wu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

ICLR 2024 Robust NAS Under Adversarial Training: Benchmark, Theory, and Beyond Yongtao Wu, Fanghui Liu, Carl-Johann Simon-Gabriel, Grigorios Chrysos, Volkan Cevher

NeurIPS 2024 SAMPa: Sharpness-Aware Minimization Parallelized Wanyun Xie, Thomas Pethick, Volkan Cevher

ICLRW 2024 Single-Pass Detection of Jailbreaking Input in Large Language Models Leyla Naz Candogan, Yongtao Wu, Elias Abad Rocamora, Grigorios Chrysos, Volkan Cevher

ICML 2024 Truly No-Regret Learning in Constrained MDPs Adrian Müller, Pragnya Alatur, Volkan Cevher, Giorgia Ramponi, Niao He

ICMLW 2024 Truly No-Regret Learning in Constrained MDPs Adrian Müller, Pragnya Alatur, Volkan Cevher, Giorgia Ramponi, Niao He

ICML 2024 Universal Gradient Methods for Stochastic Convex Optimization Anton Rodomanov, Ali Kavis, Yongtao Wu, Kimon Antonakopoulos, Volkan Cevher

ICMLW 2023 1-Path-Norm Regularization of Deep Neural Networks Fabian Latorre, Antoine Bonnet, Paul Rolland, Nadav Hallak, Volkan Cevher

ICMLW 2023 Adversarial Training Should Be Cast as a Non-Zero-Sum Game Alexander Robey, Fabian Latorre, George J. Pappas, Hamed Hassani, Volkan Cevher

NeurIPS 2023 Alternation Makes the Adversary Weaker in Two-Player Games Volkan Cevher, Ashok Cutkosky, Ali Kavis, Georgios Piliouras, Stratis Skoulakis, Luca Viano

ICML 2023 Benign Overfitting in Deep Neural Networks Under Lazy Training Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Francesco Locatello, Volkan Cevher

ICLR 2023 DiGress: Discrete Denoising Diffusion for Graph Generation Clement Vignac, Igor Krawczuk, Antoine Siraudin, Bohan Wang, Volkan Cevher, Pascal Frossard

ICLR 2023 Distributed Extra-Gradient with Optimal Complexity and Communication Guarantees Ali Ramezani-Kebrya, Kimon Antonakopoulos, Igor Krawczuk, Justin Deschenaux, Volkan Cevher

NeurIPS 2023 Efficient Online Clustering with Moving Costs Dimitrios Christou, Stratis Skoulakis, Volkan Cevher

NeurIPS 2023 Exponential Lower Bounds for Fictitious Play in Potential Games Ioannis Panageas, Nikolas Patris, Stratis Skoulakis, Volkan Cevher

TMLR 2023 Federated Learning Under Covariate Shifts with Generalization Guarantees Ali Ramezani-Kebrya, Fanghui Liu, Thomas Pethick, Grigorios Chrysos, Volkan Cevher

ICLR 2023 Finding Actual Descent Directions for Adversarial Training Fabian Latorre, Igor Krawczuk, Leello Tadesse Dadi, Thomas Pethick, Volkan Cevher

NeurIPSW 2023 Generalization Guarantees of Deep ResNets in the Mean-Field Regime Yihang Chen, Fanghui Liu, Yiping Lu, Grigorios Chrysos, Volkan Cevher

NeurIPS 2023 Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks Jiayuan Ye, Zhenyu Zhu, Fanghui Liu, Reza Shokri, Volkan Cevher

NeurIPS 2023 Maximum Independent Set: Self-Training Through Dynamic Programming Lorenzo Brusca, Lars C.P.M. Quaedvlieg, Stratis Skoulakis, Grigorios Chrysos, Volkan Cevher

NeurIPS 2023 On the Convergence of Encoder-Only Shallow Transformers Yongtao Wu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

CVPR 2023 Regularization of Polynomial Networks for Image Recognition Grigorios G. Chrysos, Bohan Wang, Jiankang Deng, Volkan Cevher

TMLR 2023 Revisiting Adversarial Training for the Worst-Performing Class Thomas Pethick, Grigorios Chrysos, Volkan Cevher

NeurIPS 2023 Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling Zhenyu Zhu, Francesco Locatello, Volkan Cevher

ICML 2023 Semi Bandit Dynamics in Congestion Games: Convergence to Nash Equilibrium and No-Regret Guarantees. Ioannis Panageas, Stratis Skoulakis, Luca Viano, Xiao Wang, Volkan Cevher

ICLR 2023 Solving Stochastic Weak Minty Variational Inequalities Without Increasing Batch Size Thomas Pethick, Olivier Fercoq, Puya Latafat, Panagiotis Patrinos, Volkan Cevher

NeurIPS 2023 Stable Nonconvex-Nonconcave Training via Linear Interpolation Thomas Pethick, Wanyun Xie, Volkan Cevher

ICML 2023 What Can Online Reinforcement Learning with Function Approximation Benefit from General Coverage Conditions? Fanghui Liu, Luca Viano, Volkan Cevher

ICML 2023 When Do Minimax-Fair Learning and Empirical Risk Minimization Coincide? Harvineet Singh, Matthäus Kleindessner, Volkan Cevher, Rumi Chunara, Chris Russell

AISTATS 2022 Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization Gideon Dresdner, Maria-Luiza Vladarean, Gunnar Rätsch, Francesco Locatello, Volkan Cevher, Alp Yurtsever

ICML 2022 A Natural Actor-Critic Framework for Zero-Sum Markov Games Ahmet Alacaoglu, Luca Viano, Niao He, Volkan Cevher

NeurIPS 2022 Adaptive Stochastic Variance Reduction for Non-Convex Finite-Sum Minimization Ali Kavis, Stratis Skoulakis, Kimon Antonakopoulos, Leello Tadesse Dadi, Volkan Cevher

ICLR 2022 Controlling the Complexity and Lipschitz Constant Improves Polynomial Nets Zhenyu Zhu, Fabian Latorre, Grigorios Chrysos, Volkan Cevher

ICLR 2022 Escaping Limit Cycles: Global Convergence for Constrained Nonconvex-Nonconcave Minimax Problems Thomas Pethick, Puya Latafat, Panos Patrinos, Olivier Fercoq, Volkan Cevher

NeurIPS 2022 Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods Kimon Antonakopoulos, Ali Kavis, Volkan Cevher

NeurIPS 2022 Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: A Polynomial Net Study Yongtao Wu, Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

NeurIPS 2022 Generalization Properties of NAS Under Activation and Skip Connection Search Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

ICLR 2022 High Probability Bounds for a Class of Nonconvex Algorithms with AdaGrad Stepsize Ali Kavis, Kfir Yehuda Levy, Volkan Cevher

NeurIPS 2022 Identifiability and Generalizability from Multiple Experts in Inverse Reinforcement Learning Paul Rolland, Luca Viano, Norman Schürhoff, Boris Nikolov, Volkan Cevher

NeurIPS 2022 No-Regret Learning in Games with Noisy Feedback: Faster Rates and Adaptivity via Learning Rate Separation Yu-Guan Hsieh, Kimon Antonakopoulos, Volkan Cevher, Panayotis Mertikopoulos

NeurIPS 2022 On the Double Descent of Random Features Models Trained with SGD Fanghui Liu, Johan Suykens, Volkan Cevher

NeurIPS 2022 Proximal Point Imitation Learning Luca Viano, Angeliki Kamoutsi, Gergely Neu, Igor Krawczuk, Volkan Cevher

NeurIPS 2022 Robustness in Deep Learning: The Good (width), the Bad (depth), and the Ugly (initialization) Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

ICML 2022 Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models Paul Rolland, Volkan Cevher, Matthäus Kleindessner, Chris Russell, Dominik Janzing, Bernhard Schölkopf, Francesco Locatello

NeurIPS 2022 Sound and Complete Verification of Polynomial Networks Elias Abad Rocamora, Mehmet Fatih Sahin, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

ICLR 2022 The Spectral Bias of Polynomial Neural Networks Moulik Choraria, Leello Tadesse Dadi, Grigorios Chrysos, Julien Mairal, Volkan Cevher

ICML 2022 UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees Kimon Antonakopoulos, Dong Quan Vu, Volkan Cevher, Kfir Levy, Panayotis Mertikopoulos

NeurIPS 2022 Understanding Deep Neural Function Approximation in Reinforcement Learning via $\epsilon$-Greedy Exploration Fanghui Liu, Luca Viano, Volkan Cevher

NeurIPS 2021 A First-Order Primal-Dual Method with Adaptivity to Local Smoothness Maria-Luiza Vladarean, Yura Malitsky, Volkan Cevher

NeurIPS 2021 Convergence of Adaptive Algorithms for Constrained Weakly Convex Optimization Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher

ICML 2021 Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach Nadav Hallak, Panayotis Mertikopoulos, Volkan Cevher

NeurIPS 2021 Robust Inverse Reinforcement Learning Under Transition Dynamics Mismatch Luca Viano, Yu-Ting Huang, Parameswaran Kamalaruban, Adrian Weller, Volkan Cevher

NeurIPS 2021 STORM+: Fully Adaptive SGD with Recursive Momentum for Nonconvex Optimization Kfir Levy, Ali Kavis, Volkan Cevher

NeurIPS 2021 Sifting Through the Noise: Universal First-Order Methods for Stochastic Variational Inequalities Kimon Antonakopoulos, Thomas Pethick, Ali Kavis, Panayotis Mertikopoulos, Volkan Cevher

NeurIPS 2021 Subquadratic Overparameterization for Shallow Neural Networks ChaeHwan Song, Ali Ramezani-Kebrya, Thomas Pethick, Armin Eftekhari, Volkan Cevher

NeurIPS 2021 The Effect of the Intrinsic Dimension on the Generalization of Quadratic Classifiers Fabian Latorre, Leello Tadesse Dadi, Paul Rolland, Volkan Cevher

ICML 2021 The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher

ICML 2020 A New Regret Analysis for Adam-Type Algorithms Ahmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos, Volkan Cevher

ICML 2020 Conditional Gradient Methods for Stochastically Constrained Convex Minimization Maria-Luiza Vladarean, Ahmet Alacaoglu, Ya-Ping Hsieh, Volkan Cevher

JMLR 2020 Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections Junhong Lin, Volkan Cevher

ICML 2020 Double-Loop Unadjusted Langevin Algorithm Paul Rolland, Armin Eftekhari, Ali Kavis, Volkan Cevher

ICML 2020 Efficient Proximal Mapping of the 1-Path-Norm of Shallow Networks Fabian Latorre, Paul Rolland, Nadav Hallak, Volkan Cevher

ICLR 2020 Lipschitz Constant Estimation of Neural Networks via Sparse Polynomial Optimization Fabian Latorre, Paul Rolland, Volkan Cevher

NeurIPS 2020 On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems Panayotis Mertikopoulos, Nadav Hallak, Ali Kavis, Volkan Cevher

JMLR 2020 Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms Junhong Lin, Volkan Cevher

ICML 2020 Random Extrapolation for Primal-Dual Coordinate Descent Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher

NeurIPS 2020 Robust Reinforcement Learning via Adversarial Training with Langevin Dynamics Parameswaran Kamalaruban, Yu-Ting Huang, Ya-Ping Hsieh, Paul Rolland, Cheng Shi, Volkan Cevher

NeurIPSW 2020 Uncertainty-Driven Adaptive Sampling via GANs Thomas Sanchez, Igor Krawczuk, Zhaodong Sun, Volkan Cevher

ICML 2019 A Conditional-Gradient-Based Augmented Lagrangian Framework Alp Yurtsever, Olivier Fercoq, Volkan Cevher

ICML 2019 Almost Surely Constrained Convex Optimization Olivier Fercoq, Ahmet Alacaoglu, Ion Necoara, Volkan Cevher

NeurIPS 2019 An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints Mehmet Fatih Sahin, Armin Eftekhari, Ahmet Alacaoglu, Fabian Latorre, Volkan Cevher

ICML 2019 Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator Alp Yurtsever, Suvrit Sra, Volkan Cevher

ICML 2019 Efficient Learning of Smooth Probability Functions from Bernoulli Tests with Guarantees Paul Rolland, Ali Kavis, Alexander Immer, Adish Singla, Volkan Cevher

NeurIPS 2019 Fast and Provable ADMM for Learning with Generative Priors Fabian Latorre, Armin Eftekhari, Volkan Cevher

ICML 2019 Finding Mixed Nash Equilibria of Generative Adversarial Networks Ya-Ping Hsieh, Chen Liu, Volkan Cevher

IJCAI 2019 Interactive Teaching Algorithms for Inverse Reinforcement Learning Parameswaran Kamalaruban, Rati Devidze, Volkan Cevher, Adish Singla

AAAI 2019 Iterative Classroom Teaching Teresa Yeo, Parameswaran Kamalaruban, Adish Singla, Arpit Merchant, Thibault Asselborn, Louis Faucon, Pierre Dillenbourg, Volkan Cevher

ICML 2019 On Certifying Non-Uniform Bounds Against Adversarial Attacks Chen Liu, Ryota Tomioka, Volkan Cevher

NeurIPS 2019 Stochastic Frank-Wolfe for Composite Convex Minimization Francesco Locatello, Alp Yurtsever, Olivier Fercoq, Volkan Cevher

NeurIPS 2019 UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization Ali Kavis, Kfir Y. Levy, Francis Bach, Volkan Cevher

ICML 2018 A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming Alp Yurtsever, Olivier Fercoq, Francesco Locatello, Volkan Cevher

NeurIPS 2018 Adversarially Robust Optimization with Gaussian Processes Ilija Bogunovic, Jonathan Scarlett, Stefanie Jegelka, Volkan Cevher

AISTATS 2018 Combinatorial Penalties: Which Structures Are Preserved by Convex Relaxations? Marwa El Halabi, Francis R. Bach, Volkan Cevher

ALT 2018 Dimension-Free Information Concentration via Exp-Concavity Ya-ping Hsieh, Volkan Cevher

AISTATS 2018 High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups Paul Rolland, Jonathan Scarlett, Ilija Bogunovic, Volkan Cevher

ICML 2018 Let’s Be Honest: An Optimal No-Regret Framework for Zero-Sum Games Ehsan Asadi Kangarshahi, Ya-Ping Hsieh, Mehmet Fatih Sahin, Volkan Cevher

NeurIPS 2018 Mirrored Langevin Dynamics Ya-Ping Hsieh, Ali Kavis, Paul Rolland, Volkan Cevher

NeurIPS 2018 Online Adaptive Methods, Universality and Acceleration Kfir Y. Levy, Alp Yurtsever, Volkan Cevher

ICML 2018 Optimal Distributed Learning with Multi-Pass Stochastic Gradient Methods Junhong Lin, Volkan Cevher

ICML 2018 Optimal Rates of Sketched-Regularized Algorithms for Least-Squares Regression over Hilbert Spaces Junhong Lin, Volkan Cevher

AISTATS 2018 Robust Maximization of Non-Submodular Objectives Ilija Bogunovic, Junyao Zhao, Volkan Cevher

AISTATS 2018 Stochastic Three-Composite Convex Minimization with a Linear Operator Renbo Zhao, Volkan Cevher

AISTATS 2017 Faster Coordinate Descent via Adaptive Importance Sampling Dmytro Perekrestenko, Volkan Cevher, Martin Jaggi

NeurIPS 2017 Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data Joel A Tropp, Alp Yurtsever, Madeleine Udell, Volkan Cevher

AISTATS 2017 Lower Bounds on Active Learning for Graphical Model Selection Jonathan Scarlett, Volkan Cevher

COLT 2017 Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization Jonathan Scarlett, Ilija Bogunovic, Volkan Cevher

NeurIPS 2017 Phase Transitions in the Pooled Data Problem Jonathan Scarlett, Volkan Cevher

ICML 2017 Robust Submodular Maximization: A Non-Uniform Partitioning Approach Ilija Bogunovic, Slobodan Mitrović, Jonathan Scarlett, Volkan Cevher

AISTATS 2017 Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage Alp Yurtsever, Madeleine Udell, Joel A. Tropp, Volkan Cevher

NeurIPS 2017 Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization Ahmet Alacaoglu, Quoc Tran Dinh, Olivier Fercoq, Volkan Cevher

NeurIPS 2017 Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach Slobodan Mitrovic, Ilija Bogunovic, Ashkan Norouzi-Fard, Jakub M Tarnawski, Volkan Cevher

NeurIPS 2016 An Efficient Streaming Algorithm for the Submodular Cover Problem Ashkan Norouzi-Fard, Abbas Bazzi, Ilija Bogunovic, Marwa El Halabi, Ya-Ping Hsieh, Volkan Cevher

AISTATS 2016 Convex Block-Sparse Linear Regression with Expanders - Provably Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher

AISTATS 2016 Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices Jonathan Scarlett, Volkan Cevher

NeurIPS 2016 Stochastic Three-Composite Convex Minimization Alp Yurtsever, Bang Cong Vu, Volkan Cevher

AISTATS 2016 Time-Varying Gaussian Process Bandit Optimization Ilija Bogunovic, Jonathan Scarlett, Volkan Cevher

NeurIPS 2016 Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation Ilija Bogunovic, Jonathan Scarlett, Andreas Krause, Volkan Cevher

AISTATS 2015 A Totally Unimodular View of Structured Sparsity Marwa El Halabi, Volkan Cevher

NeurIPS 2015 A Universal Primal-Dual Convex Optimization Framework Alp Yurtsever, Quoc Tran Dinh, Volkan Cevher

JMLR 2015 Composite Self-Concordant Minimization Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher

NeurIPS 2015 Preconditioned Spectral Descent for Deep Learning David E Carlson, Edo Collins, Ya-Ping Hsieh, Lawrence Carin, Volkan Cevher

AISTATS 2015 Sparsistency of 1-Regularized M-Estimators Yen-Huan Li, Jonathan Scarlett, Pradeep Ravikumar, Volkan Cevher

AISTATS 2015 Stochastic Spectral Descent for Restricted Boltzmann Machines David E. Carlson, Volkan Cevher, Lawrence Carin

AISTATS 2015 WASP: Scalable Bayes via Barycenters of Subset Posteriors Sanvesh Srivastava, Volkan Cevher, Quoc Tran-Dinh, David B. Dunson

UAI 2014 A Variational Approach to Stable Principal Component Pursuit Aleksandr Y. Aravkin, Stephen Becker, Volkan Cevher, Peder A. Olsen

NeurIPS 2014 Constrained Convex Minimization via Model-Based Excessive Gap Quoc Tran-Dinh, Volkan Cevher

AAAI 2014 Scalable Sparse Covariance Estimation via Self-Concordance Anastasios Kyrillidis, Rabeeh Karimi Mahabadi, Quoc Tran-Dinh, Volkan Cevher

NeurIPS 2014 Time--Data Tradeoffs by Aggressive Smoothing John J Bruer, Joel A Tropp, Volkan Cevher, Stephen Becker

ICML 2013 A Proximal Newton Framework for Composite Minimization: Graph Learning Without Cholesky Decompositions and Matrix Inversions Quoc Tran Dinh, Anastasios Kyrillidis, Volkan Cevher

NeurIPS 2013 High-Dimensional Gaussian Process Bandits Josip Djolonga, Andreas Krause, Volkan Cevher

ICML 2013 Sparse Projections onto the Simplex Anastasios Kyrillidis, Stephen Becker, Volkan Cevher, Christoph Koch

NeurIPS 2012 Active Learning of Multi-Index Function Models Tyagi Hemant, Volkan Cevher

ICML 2010 Submodular Dictionary Selection for Sparse Representation Andreas Krause, Volkan Cevher

NeurIPS 2009 Learning with Compressible Priors Volkan Cevher

ECCV 2008 Compressive Sensing for Background Subtraction Volkan Cevher, Aswin C. Sankaranarayanan, Marco F. Duarte, Dikpal Reddy, Richard G. Baraniuk, Rama Chellappa

NeurIPS 2008 Sparse Signal Recovery Using Markov Random Fields Volkan Cevher, Marco F. Duarte, Chinmay Hegde, Richard Baraniuk