Steiner Tree Heuristic in the Euclidean d-Space Using Bottleneck Distances. - Stephan Sloth Lorenzen; Pawel Winter (SEA, 2016)

On PAC-Bayesian bounds for random forests. - Stephan Sloth Lorenzen; Christian Igel; Yevgeny Seldin (Mach. Learn., 2019)

Second Order PAC-Bayesian Bounds for the Weighted Majority Vote. - Andrés R. Masegosa; Stephan Sloth Lorenzen; Christian Igel; Yevgeny Seldin (NeurIPS, 2020)

Revisiting Wedge Sampling for Budgeted Maximum Inner Product Search. - Stephan Sloth Lorenzen; Ninh Pham (ECML/PKDD (1), 2020)

Revisiting Wedge Sampling for Budgeted Maximum Inner Product Search (Extended Abstract). - Stephan Sloth Lorenzen; Ninh Pham (IJCAI, 2021)

Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote. - Yi-Shan Wu 003; Andrés R. Masegosa; Stephan Sloth Lorenzen; Christian Igel; Yevgeny Seldin (NeurIPS, 2021)

Information Bottleneck: Exact Analysis of (Quantized) Neural Networks. - Stephan Sloth Lorenzen; Christian Igel; Mads Nielsen (ICLR, 2022)

Online transfer learning with partial feedback. - Zhongfeng Kang; Mads Nielsen; Bo Yang 011; Lihui Deng; Stephan Sloth Lorenzen (Expert Syst. Appl., 2023)