Gossmann, Alexej

9 publications

ICML 2025 "Who Experiences Large Model Decay and Why?" a Hierarchical Framework for Diagnosing Heterogeneous Performance Drift Harvineet Singh, Fan Xia, Alexej Gossmann, Andrew Chuang, Julian C. Hong, Jean Feng

AISTATS 2025 M-HOF-Opt: Multi-Objective Hierarchical Output Feedback Optimization via Multiplier Induced Loss Landscape Scheduling Xudong Sun, Nutan Chen, Alexej Gossmann, Yu Xing, Matteo Wohlrapp, Emilio Dorigatti, Carla Feistner, Felix Drost, Daniele Scarcella, Lisa Helen Beer, Carsten Marr

NeurIPS 2024 A Hierarchical Decomposition for Explaining ML Performance Discrepancies Harvineet Singh, Fan Xia, Adarsh Subbaswamy, Alexej Gossmann, Jean Feng

CHIL 2024 Contextual Unsupervised Deep Clustering in Digital Pathology Mariia Sidulova, Seyed Kahaki, Ian Hagemann, Alexej Gossmann

CLeaR 2024 Designing Monitoring Strategies for Deployed Machine Learning Algorithms: Navigating Performativity Through a Causal Lens Jean Feng, Adarsh Subbaswamy, Alexej Gossmann, Harvineet Singh, Berkman Sahiner, Mi-Ok Kim, Gene Anthony Pennello, Nicholas Petrick, Romain Pirracchio, Fan Xia

AISTATS 2024 Is This Model Reliable for Everyone? Testing for Strong Calibration Jean Feng, Alexej Gossmann, Romain Pirracchio, Nicholas Petrick, Gene A Pennello, Berkman Sahiner

AISTATS 2024 Monitoring Machine Learning-Based Risk Prediction Algorithms in the Presence of Performativity Jean Feng, Alexej Gossmann, Gene A Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio

NeurIPSW 2023 Towards a Post-Market Monitoring Framework for Machine Learning-Based Medical Devices: A Case Study Jean Feng, Adarsh Subbaswamy, Alexej Gossmann, Harvineet Singh, Berkman Sahiner, Mi-Ok Kim, Gene Pennello, Nicholas Petrick, Romain Pirracchio, Fan Xia

UAI 2022 Sequential Algorithmic Modification with Test Data Reuse Jean Feng, Gene Pennllo, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio, Alexej Gossmann