4 papers · 1 filter
Performative Prediction with Selective Labels
Giovani Valdrighi, Isabel Valera, Marcos Medeiros Raimundo
Many social applications of machine learning exhibit performative effects: population behavior changes in response to deployed models. Performative prediction studies this interact…
Learning Pareto Stationary Fronts via Single-Pass Backpropagation
Elina Rojin Celik, Marcos Medeiros Raimundo, Isabel Valera
We propose MOSEL (Multi-Objective Stackelberg Efficient Learning), a framework for a posteriori multi-objective optimization (MOO) in deep neural networks that recovers a full fron…
Sparse Mixture-of-Experts Reward Models Learn Interpretable and Specialized Experts for Personalized Preference Modeling
Yifan Wang, Jinyi Mu, Mayank Jobanputra +5
Preference modeling plays a central role in reinforcement learning from human feedback (RLHF), enabling large language models (LLMs) to align with human values. However, most exist…
Long-term Fairness with Selective Labels
Giovani Valdrighi, Isabel Valera, Marcos Medeiros Raimundo
Long-term fairness algorithms aim to satisfy fairness beyond static and short-term notions by accounting for the dynamics between decision-making policies and population behavior.…