collaborators

6 papers

cs.GT2026

Online Price Competition under Generalized Linear Demands

Daniele Bracale, Moulinath Banerjee, Cong Shi +1

We study a sequential price competition among sellers, each influenced by the pricing decisions of their rivals. Specifically, the demand function for each seller follows t…

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.ML2026

Revenue Maximization Under Sequential Price Competition Via The Estimation Of s-Concave Demand Functions

Daniele Bracale, Moulinath Banerjee, Cong Shi +1

We consider price competition among multiple sellers over a selling horizon of periods. In each period, sellers simultaneously offer their prices (which are made public) and su…

stat.ML2025

Dynamic Pricing in the Linear Valuation Model using Shape Constraints

Daniele Bracale, Moulinath Banerjee, Yuekai Sun +2

We propose a shape-constrained approach to dynamic pricing for censored data in the linear valuation model eliminating the need for tuning parameters commonly required by existing…

stat.ML2025

Microfoundation Inference for Strategic Prediction

Daniele Bracale, Subha Maity, Felipe Maia Polo +3

Often in prediction tasks, the predictive model itself can influence the distribution of the target variable, a phenomenon termed performative prediction. Generally, this influence…

stat.ML2025

Learning the Distribution Map in Reverse Causal Performative Prediction

Daniele Bracale, Subha Maity, Moulinath Banerjee +1

In numerous predictive scenarios, the predictive model affects the sampling distribution; for example, job applicants often meticulously craft their resumes to navigate through a s…