Scalable convex methods for phase retrieval. - Alp Yurtsever; Ya-Ping Hsieh; Volkan Cevher (CAMSAP, 2015)

A Universal Primal-Dual Convex Optimization Framework. - Alp Yurtsever; Quoc Tran-Dinh; Volkan Cevher (NIPS, 2015)

Frank-Wolfe works for non-Lipschitz continuous gradient objectives: Scalable poisson phase retrieval. - Gergely Ódor; Yen-Huan Li; Alp Yurtsever; Ya-Ping Hsieh; Quoc Tran-Dinh; Marwa El Halabi; Volkan Cevher (ICASSP, 2016)

Stochastic Three-Composite Convex Minimization. - Alp Yurtsever; Bang Công Vu; Volkan Cevher (NIPS, 2016)

Randomized single-view algorithms for low-rank matrix approximation. - Joel A. Tropp; Alp Yurtsever; Madeleine Udell; Volkan Cevher (CoRR, 2016)

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

Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data. - Joel A. Tropp; Alp Yurtsever; Madeleine Udell; Volkan Cevher (NIPS, 2017)

Practical Sketching Algorithms for Low-Rank Matrix Approximation. - Joel A. Tropp; Alp Yurtsever; Madeleine Udell; Volkan Cevher (SIAM J. Matrix Anal. Appl., 2017)

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

Online Adaptive Methods, Universality and Acceleration. - Kfir Yehuda Levy; Alp Yurtsever; Volkan Cevher (NeurIPS, 2018)

A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization. - Ya-Ping Hsieh; Yu-Chun Kao; Rabeeh Karimi Mahabadi; Alp Yurtsever; Anastasios Kyrillidis; Volkan Cevher (IEEE Trans. Signal Process., 2018)

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

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

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

Stochastic Conditional Gradient Method for Composite Convex Minimization. - Francesco Locatello; Alp Yurtsever; Olivier Fercoq; Volkan Cevher (CoRR, 2019)

Streaming Low-Rank Matrix Approximation with an Application to Scientific Simulation. - Joel A. Tropp; Alp Yurtsever; Madeleine Udell; Volkan Cevher (SIAM J. Sci. Comput., 2019)

Scalable Convex Optimization Methods for Semidefinite Programming. - Alp Yurtsever (2019)

Three Operator Splitting with a Nonconvex Loss Function. - Alp Yurtsever; Varun Mangalick; Suvrit Sra (ICML, 2021)

Three Operator Splitting with Subgradients, Stochastic Gradients, and Adaptive Learning Rates. - Alp Yurtsever; Alex Gu; Suvrit Sra (NeurIPS, 2021)

An Optimal-Storage Approach to Semidefinite Programming Using Approximate Complementarity. - Lijun Ding; Alp Yurtsever; Volkan Cevher; Joel A. Tropp; Madeleine Udell (SIAM J. Optim., 2021)

Scalable Semidefinite Programming. - Alp Yurtsever; Joel A. Tropp; Olivier Fercoq; Madeleine Udell; Volkan Cevher (SIAM J. Math. Data Sci., 2021)

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

Q-FW: A Hybrid Classical-Quantum Frank-Wolfe for Quadratic Binary Optimization. - Alp Yurtsever; Tolga Birdal; Vladislav Golyanik (ECCV (23), 2022)

CCCP is Frank-Wolfe in disguise. - Alp Yurtsever; Suvrit Sra (NeurIPS, 2022)

A Variational Perspective on High-Resolution ODEs. - Hoomaan Maskan; Konstantinos Zygalakis; Alp Yurtsever (NeurIPS, 2023)

Federated Frank-Wolfe Algorithm. - Ali Dadras; Sourasekhar Banerjee; Karthik Prakhya; Alp Yurtsever (ECML/PKDD (3), 2024)

Personalized Multi-tier Federated Learning. - Sourasekhar Banerjee; Ali Dadras; Alp Yurtsever; Monowar H. Bhuyan (CoRR, 2024)

Convex Formulations for Training Two-Layer ReLU Neural Networks. - Karthik Prakhya; Tolga Birdal; Alp Yurtsever (ICLR, 2025)

Personalized Federated Learning via Low-Rank Matrix Optimization. - Ali Dadras; Sebastian U. Stich; Alp Yurtsever (Trans. Mach. Learn. Res., 2025)

Implicit Bias in Matrix Factorization and its Explicit Realization in a New Architecture. - Yikun Hou; Suvrit Sra; Alp Yurtsever (CoRR, 2025)

Revisiting Frank-Wolfe for Structured Nonconvex Optimization. - Hoomaan Maskan; Yikun Hou; Suvrit Sra; Alp Yurtsever (CoRR, 2025)

Provable Reduction in Communication Rounds for Non-Smooth Convex Federated Learning. - Karlo Palenzuela; Ali Dadras; Alp Yurtsever; Tommy Löfstedt (CoRR, 2025)