A survey on the densest subgraph problem and its variants

T Lanciano, A Miyauchi, A Fazzone, F Bonchi - ACM Computing Surveys, 2024 - dl.acm.org
The Densest Subgraph Problem requires us to find, in a given graph, a subset of vertices
whose induced subgraph maximizes a measure of density. The problem has received a …

Modeling the AC power flow equations with optimally compact neural networks: Application to unit commitment

A Kody, S Chevalier, S Chatzivasileiadis… - Electric Power Systems …, 2022 - Elsevier
Nonlinear power flow constraints render a variety of power system optimization problems
computationally intractable. Emerging research shows, however, that the nonlinear AC …

Loss functions for discrete contextual pricing with observational data

M Biggs, R Gao, W Sun - arXiv preprint arXiv:2111.09933, 2021 - arxiv.org
We study a pricing setting where each customer is offered a contextualized price based on
customer and/or product features. Often only historical sales data are available, so we …

Tackling provably hard representative selection via graph neural networks

M Kazemi, A Tsitsulin, H Esfandiari, MH Bateni… - arXiv preprint arXiv …, 2022 - arxiv.org
Representative Selection (RS) is the problem of finding a small subset of exemplars from a
dataset that is representative of the dataset. In this paper, we study RS for attributed graphs …

Convex Surrogate Loss Functions for Contextual Pricing with Transaction Data

M Biggs - arXiv preprint arXiv:2202.10944, 2022 - arxiv.org
We study an off-policy contextual pricing problem where the seller has access to samples of
prices that customers were previously offered, whether they purchased at that price, and …