Denoising and Completion of Structured Low-Rank Matrices via Iteratively Reweighted Least Squares. - Christian Kümmerle; Claudio Mayrink Verdun (CoRR, 2018)

Harmonic Mean Iteratively Reweighted Least Squares for Low-Rank Matrix Recovery. - Christian Kümmerle; Juliane Sigl (J. Mach. Learn. Res., 2018)

The Oracle of DLphi. - Dominik Alfke; Weston Baines; Jan Blechschmidt; Mauricio J. del Razo Sarmina; Amnon Drory; Dennis Elbrächter; Nando Farchmin; Matteo Gambara; Silke Glas; Philipp Grohs; Peter Hinz; Danijel Kivaranovic; et al. (CoRR, 2019)

On the geometry of polytopes generated by heavy-tailed random vectors. - Olivier Guédon; Felix Krahmer; Christian Kümmerle; Shahar Mendelson; Holger Rauhut (CoRR, 2019)

Escaping Saddle Points in Ill-Conditioned Matrix Completion with a Scalable Second Order Method. - Christian Kümmerle; Claudio Mayrink Verdun (CoRR, 2020)

On the robustness of noise-blind low-rank recovery from rank-one measurements. - Felix Krahmer; Christian Kümmerle; Oleh Melnyk (CoRR, 2020)

Iteratively Reweighted Least Squares for 𝓁1-minimization with Global Linear Convergence Rate. - Christian Kümmerle; Claudio Mayrink Verdun; Dominik Stöger (CoRR, 2020)

A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few Samples. - Christian Kümmerle; Claudio Mayrink Verdun (ICML, 2021)

Iteratively Reweighted Least Squares for Basis Pursuit with Global Linear Convergence Rate. - Christian Kümmerle; Claudio Mayrink Verdun; Dominik Stöger (NeurIPS, 2021)

Dictionary-Sparse Recovery From Heavy-Tailed Measurements. - Pedro Abdalla; Christian Kümmerle (CoRR, 2021)

Global Linear and Local Superlinear Convergence of IRLS for Non-Smooth Robust Regression. - Liangzu Peng; Christian Kümmerle; René Vidal (NeurIPS, 2022)

On the Convergence of IRLS and Its Variants in Outlier-Robust Estimation. - Liangzu Peng; Christian Kümmerle; René Vidal (CVPR, 2023)

Recovering Simultaneously Structured Data via Non-Convex Iteratively Reweighted Least Squares. - Christian Kümmerle; Johannes Maly (NeurIPS, 2023)

Data-Driven Graph Construction of Power Flow Graphs for Electric Power Transmission Networks. - Benjamin Poole; Rajan Ratnakumar; Dulip Tharaka Madurasinghe; Christian Kümmerle; Ganesh Kumar Venayagamoorthy; Minwoo Lee (ICMLA, 2024)

Linear Convergence of Iteratively Reweighted Least Squares for Nuclear Norm Minimization. - Christian Kümmerle; Dominik Stöger (SAM, 2024)

Sample-Efficient Geometry Reconstruction from Euclidean Distances using Non-Convex Optimization. - Ipsita Ghosh; Abiy Tasissa; Christian Kümmerle (NeurIPS, 2024)

UnitNorm: Rethinking Normalization for Transformers in Time Series. - Nan Huang 004; Christian Kümmerle; Xiang Zhang 012 (CoRR, 2024)

Fibottention: Inceptive Visual Representation Learning with Diverse Attention Across Heads. - Ali Khaleghi Rahimian; Manish Kumar Govind; Subhajit Maity; Dominick Reilly; Christian Kümmerle; Srijan Das; Aritra Dutta (CoRR, 2024)

Sparse Recovery for Overcomplete Frames: Sensing Matrices and Recovery Guarantees. - Xuemei Chen; Christian Kümmerle; Rongrong Wang (CoRR, 2024)

An Exposition of Pathfinding Strategies Within Lightning Network Clients. - Sindura Saraswathi; Christian Kümmerle (CoRR, 2024)

Learning Transition Operators From Sparse Space-Time Samples. - Christian Kümmerle; Mauro Maggioni; Sui Tang (IEEE Trans. Inf. Theory, 2024)