3 papers
math.ST2026
Equilibrium and Pricing in Consumer Networks with Nonlinear Utilities: An Online Shape-Constrained Learning Approach
Daniele Bracale, George Michailidis
We study optimal monopoly pricing over consumer networks governed by general nonlinear utilities. In our framework, a consumer's utility is jointly determined by an individualized…
stat.ML2025
Neural Network-Based Change Point Detection for Large-Scale Time-Evolving Data
Jialiang Geng, George Michailidis
The paper studies the problem of detecting and locating change points in multivariate time-evolving data. The problem has a long history in statistics and signal processing and var…
stat.ML2024
Deep Learning-based Approaches for State Space Models: A Selective Review
Jiahe Lin, George Michailidis
State-space models (SSMs) offer a powerful framework for dynamical system analysis, wherein the temporal dynamics of the system are assumed to be captured through the evolution of…