Matrix-free interior point method for compressed sensing problems. - Kimon Fountoulakis; Jacek Gondzio; Pavel Zhlobich (Math. Program. Comput., 2014)

A Randomized Rounding Algorithm for Sparse PCA. - Petros Drineas; Kimon Fountoulakis; Abhisek Kundu (CoRR, 2015)

A Preconditioner for A Primal-Dual Newton Conjugate Gradient Method for Compressed Sensing Problems. - Ioannis K. Dassios; Kimon Fountoulakis; Jacek Gondzio (SIAM J. Sci. Comput., 2015)

Performance of first- and second-order methods for ( ell _1 ) -regularized least squares problems. - Kimon Fountoulakis; Jacek Gondzio (Comput. Optim. Appl., 2016)

A second-order method for strongly convex ℓ 1 -regularization problems. - Kimon Fountoulakis; Jacek Gondzio (Math. Program., 2016)

Parallel Local Graph Clustering. - Julian Shun; Farbod Roosta-Khorasani; Kimon Fountoulakis; Michael W. Mahoney (Proc. VLDB Endow., 2016)

Capacity Releasing Diffusion for Speed and Locality. - Di Wang 005; Kimon Fountoulakis; Monika Henzinger; Michael W. Mahoney; Satish Rao (ICML, 2017)

Social Discrete Choice Models. - Danqing Zhang; Kimon Fountoulakis; Junyu Cao; Mogeng Yin; Michael W. Mahoney; Alexei Pozdnoukhov (CoRR, 2017)

An Optimization Approach to Locally-Biased Graph Algorithms. - Kimon Fountoulakis; David F. Gleich; Michael W. Mahoney (Proc. IEEE, 2017)

A Randomized Rounding Algorithm for Sparse PCA. - Kimon Fountoulakis; Abhisek Kundu; Eugenia-Maria Kontopoulou; Petros Drineas (ACM Trans. Knowl. Discov. Data, 2017)

Avoiding Synchronization in First-Order Methods for Sparse Convex Optimization. - Aditya Devarakonda; Kimon Fountoulakis; James Demmel; Michael W. Mahoney (IPDPS, 2018)

LASAGNE: Locality and Structure Aware Graph Node Embedding. - Evgheniy Faerman; Felix Borutta; Kimon Fountoulakis; Michael W. Mahoney (WI, 2018)

A flexible coordinate descent method. - Kimon Fountoulakis; Rachael Tappenden (Comput. Optim. Appl., 2018)

A Short Introduction to Local Graph Clustering Methods and Software. - Kimon Fountoulakis; David F. Gleich; Michael W. Mahoney (CoRR, 2018)

Parallel and Communication Avoiding Least Angle Regression. - Swapnil Das; Jim Demmel; Kimon Fountoulakis; Laura Grigori; Michael W. Mahoney (CoRR, 2019)

Variational perspective on local graph clustering. - Kimon Fountoulakis; Farbod Roosta-Khorasani; Julian Shun; Xiang Cheng 006; Michael W. Mahoney (Math. Program., 2019)

Avoiding Communication in Primal and Dual Block Coordinate Descent Methods. - Aditya Devarakonda; Kimon Fountoulakis; James Demmel; Michael W. Mahoney (SIAM J. Sci. Comput., 2019)

p-Norm Flow Diffusion for Local Graph Clustering. - Kimon Fountoulakis; Di Wang 005; Shenghao Yang 002 (ICML, 2020)

Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization. - Aseem Baranwal; Kimon Fountoulakis; Aukosh Jagannath (ICML, 2021)

Local Hyper-Flow Diffusion. - Kimon Fountoulakis; Pan Li 005; Shenghao Yang 002 (NeurIPS, 2021)

Statistical guarantees for local graph clustering. - Wooseok Ha; Kimon Fountoulakis; Michael W. Mahoney (J. Mach. Learn. Res., 2021)

Targeted pandemic containment through identifying local contact network bottlenecks. - Shenghao Yang 002; Priyabrata Senapati; Di Wang 005; Chris T. Bauch; Kimon Fountoulakis (PLoS Comput. Biol., 2021)

Parallel and Communication Avoiding Least Angle Regression. - Swapnil Das; James Demmel; Kimon Fountoulakis; Laura Grigori; Michael W. Mahoney; Shenghao Yang 002 (SIAM J. Sci. Comput., 2021)

Effects of Graph Convolutions in Deep Networks. - Aseem Baranwal; Kimon Fountoulakis; Aukosh Jagannath (CoRR, 2022)

On Classification Thresholds for Graph Attention with Edge Features. - Kimon Fountoulakis; Dake He; Silvio Lattanzi; Bryan Perozzi; Anton Tsitsulin; Shenghao Yang 002 (CoRR, 2022)

Effects of Graph Convolutions in Multi-layer Networks. - Aseem Baranwal; Kimon Fountoulakis; Aukosh Jagannath (ICLR, 2023)

Weighted Flow Diffusion for Local Graph Clustering with Node Attributes: an Algorithm and Statistical Guarantees. - Shenghao Yang 002; Kimon Fountoulakis (ICML, 2023)

Optimality of Message-Passing Architectures for Sparse Graphs. - Aseem Baranwal; Kimon Fountoulakis; Aukosh Jagannath (NeurIPS, 2023)

Graph Attention Retrospective. - Kimon Fountoulakis; Amit Levi; Shenghao Yang 002; Aseem Baranwal; Aukosh Jagannath (J. Mach. Learn. Res., 2023)

Flow-Based Algorithms for Improving Clusters: A Unifying Framework, Software, and Performance. - Kimon Fountoulakis; Meng Liu 027; David F. Gleich; Michael W. Mahoney (SIAM Rev., 2023)

Local Graph Clustering with Noisy Labels. - Artur Back de Luca; Kimon Fountoulakis; Shenghao Yang 002 (ICLR, 2024)

Simulation of Graph Algorithms with Looped Transformers. - Artur Back de Luca; Kimon Fountoulakis (ICML, 2024)

Analysis of Corrected Graph Convolutions. - Robert Wang 004; Aseem Baranwal; Kimon Fountoulakis (NeurIPS, 2024)

Positional Attention: Out-of-Distribution Generalization and Expressivity for Neural Algorithmic Reasoning. - Artur Back de Luca; George Giapitzakis; Shenghao Yang 002; Petar Velickovic; Kimon Fountoulakis (CoRR, 2024)

LVLM-COUNT: Enhancing the Counting Ability of Large Vision-Language Models. - Muhammad Fetrat Qharabagh; Mohammadreza Ghofrani; Kimon Fountoulakis (CoRR, 2024)

Exact Learning of Permutations for Nonzero Binary Inputs with Logarithmic Training Size and Quadratic Ensemble Complexity. - George Giapitzakis; Artur Back de Luca; Kimon Fountoulakis (CoRR, 2025)