Privacy-Preserving Distributed Learning with Secret Gradient Descent. - Valentin Hartmann; Robert West 001 (CoRR, 2019)

Privacy-Preserving Classification with Secret Vector Machines. - Valentin Hartmann; Konark Modi; Josep M. Pujol; Robert West 001 (CIKM, 2020)

Orderings of Data - More Than a Tripping Hazard: Visionary. - Anna Beer 001; Valentin Hartmann; Thomas Seidl 001 (SSDBM, 2020)

Semi-discrete optimal transport: a solution procedure for the unsquared Euclidean distance case. - Valentin Hartmann; Dominic Schuhmacher (Math. Methods Oper. Res., 2020)

KISS - A fast kNN-based Importance Score for Subspaces. - Anna Beer 001; Ekaterina Allerborn; Valentin Hartmann; Thomas Seidl 001 (EDBT, 2021)

On the Choice of Databases in Differential Privacy Composition. - Valentin Hartmann; Vincent Bindschaedler; Robert West 001 (CoRR, 2022)

Differentially Private Propensity Scores for Bias Correction. - Liangwei Chen; Valentin Hartmann; Robert West 001 (CoRR, 2022)

Language Model Decoding as Likelihood-Utility Alignment. - Martin Josifoski; Maxime Peyrard; Frano Rajic; Jiheng Wei; Debjit Paul; Valentin Hartmann; Barun Patra; Vishrav Chaudhary; Emre Kiciman; Boi Faltings; Robert West 001 (CoRR, 2022)

Privacy accounting εconomics: Improving differential privacy composition via a posteriori bounds. - Valentin Hartmann; Vincent Bindschaedler; Alexander Bentkamp; Robert West 001 (Proc. Priv. Enhancing Technol., 2022)

Language Model Decoding as Likelihood-Utility Alignment. - Martin Josifoski; Maxime Peyrard; Frano Rajic; Jiheng Wei; Debjit Paul; Valentin Hartmann; Barun Patra; Vishrav Chaudhary; Emre Kiciman; Boi Faltings (EACL (Findings), 2023)

DiPPS: Differentially Private Propensity Scores for Bias Correction. - Liangwei Chen; Valentin Hartmann; Robert West 001 (ICWSM, 2023)

Distribution Inference Risks: Identifying and Mitigating Sources of Leakage. - Valentin Hartmann; Léo Meynent; Maxime Peyrard; Dimitrios Dimitriadis; Shruti Tople; Robert West 001 (SaTML, 2023)

SoK: Memorization in General-Purpose Large Language Models. - Valentin Hartmann; Anshuman Suri; Vincent Bindschaedler; David Evans 001; Shruti Tople; Robert West 001 (CoRR, 2023)

Neural Redshift: Random Networks are not Random Functions. - Damien Teney; Armand Mihai Nicolicioiu; Valentin Hartmann; Ehsan Abbasnejad (CVPR, 2024)