Results 31 to 40 of about 11,336 (151)
Maximizing non-monotone submodular set functions subject to different constraints: Combined algorithms [PDF]
Operations Research Letters, 2011 We study the problem of maximizing constrained non-monotone submodular functions and provide approximation algorithms that improve existing algorithms in terms of either the approximation factor or simplicity. Our algorithms combine existing local search and greedy based algorithms. Different constraints that we study are exact cardinality and multiple
Salman Fadaei +2 more
openaire +4 more sources
Polymatroidal tilings and the Chow class of linked projective spaces
Bulletin of the London Mathematical Society, Volume 58, Issue 5, May 2026.Abstract Linked projective spaces are quiver Grassmannians of constant dimension one of certain quiver representations, called linked nets, over certain quivers, called Zn$\mathbb {Z}^n$‐quivers. They were recently introduced as a tool for describing schematic limits of families of divisors.
Felipe de Leon, Eduardo Esteves
wiley +1 more source
A Universal Meta‐Heuristic Framework for Influence Maximisation in Hypergraphs
CAAI Transactions on Intelligence Technology, Volume 11, Issue 2, Page 396-410, April 2026.ABSTRACT Influence maximisation (IM) aims to select a small number of nodes that are able to maximise their influence in a network and covers a wide range of applications. Despite numerous attempts to provide effective solutions in simple networks, higher‐order interactions between entities in various real‐world systems are usually not taken into ...
Ming Xie +5 more
wiley +1 more source
Fossil Fuels and Renewable Energy: Mix or Match?
The RAND Journal of Economics, Volume 57, Issue 1, Page 140-157, Spring 2026.ABSTRACT This article investigates the influence of technological ownership on pricing strategies and productive efficiency. Our motivation comes from the evolving landscape of electricity markets where firms are transitioning from diversified to specialized portfolios, focusing on renewable energy or fossil fuels.
Natalia Fabra, Gerard Llobet
wiley +1 more source
Same/Other/All K‐Fold Cross‐Validation for Estimating Similarity of Patterns in Data Subsets
Statistical Analysis and Data Mining: An ASA Data Science Journal, Volume 19, Issue 1, February 2026.ABSTRACT In many real‐world applications of machine learning, we are interested to know if it is possible to train on the data that we have gathered so far, and obtain accurate predictions on a new test data subset that is qualitatively different in some respect (time period, geographic region, etc.).
Toby Dylan Hocking +5 more
wiley +1 more source
International Journal of Energy Research, Volume 2026, Issue 1, 2026.The strategic placement and sizing of electric vehicle (EV) charging stations on highways are critical for alleviating range anxiety and fostering widespread EV adoption. This paper presents a novel mixed‐integer linear programming (MILP) model for optimizing the location and capacity of charging stations along highway corridors.
Raka Jovanovic +3 more
wiley +1 more source
The Lov\'asz Hinge: A Novel Convex Surrogate for Submodular Losses [PDF]
, 2017 Learning with non-modular losses is an important problem when sets of predictions are made simultaneously. The main tools for constructing convex surrogate loss functions for set prediction are margin rescaling and slack rescaling.
Blaschko, Matthew, Yu, Jiaqian
core +2 more sources
On Some Algorithmic and Structural Results on Flames
Journal of Graph Theory, Volume 110, Issue 4, Page 392-397, December 2025.ABSTRACT A directed graph F with a root node r is called a flame if for every vertex v other than r the local edge‐connectivity value λ F ( r , v ) from r to v is equal to ϱ F ( v ), the in‐degree of v. It is a classic, simple and beautiful result of Lovász [4] that every digraph D with a root node r has a spanning subgraph F that is a flame and the λ (
Dávid Szeszlér
wiley +1 more source
Structured sparsity-inducing norms through submodular functions [PDF]
, 2010 Sparse methods for supervised learning aim at finding good linear predictors from as few variables as possible, i.e., with small cardinality of their supports.
Bach, Francis
core +8 more sources
Control Node Placement and Structural Controllability of Water Quality Dynamics in Drinking Networks
Water Resources Research, Volume 61, Issue 12, December 2025.Abstract Chlorine, the most widely used disinfectant, needs to be adequately distributed in water distribution networks (WDNs) to maintain consistent residual levels and ensure safe water. This is performed through control node injections at the treatment plant and via booster stations distributed across the WDNs.
Salma M. Elsherif, Ahmad F. Taha
wiley +1 more source