Results 61 to 70 of about 9,788 (160)
Submodular Optimization over Streams with Inhomogeneous Decays
Proceedings of the AAAI Conference on Artificial Intelligence, 2019 Cardinality constrained submodular function maximization, which aims to select a subset of size at most k to maximize a monotone submodular utility function, is the key in many data mining and machine learning applications such as data summarization and maximum coverage problems.
Zhao, Junzhou +4 more
openaire +3 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
Optimal Algorithms for Continuous Non-monotone Submodular and DR-Submodular Maximization
, 2018 In this paper we study the fundamental problems of maximizing a continuous non-monotone submodular function over the hypercube, both with and without coordinate-wise concavity. This family of optimization problems has several applications in machine learning, economics, and communication systems. Our main result is the first $\frac{1}{2}$-approximation
Niazadeh, Rad +2 more
openaire +3 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
Multivariate Incomplete Information in the Mixture Model of Contests
The RAND Journal of Economics, Volume 56, Issue 4, Page 607-624, Winter 2025.ABSTRACT A general mixture model of contests is introduced, combining stochastic performance and multivariate incomplete information. Performance is determined by a mixture distribution with endogenous weights on a good and bad distribution, respectively.
René Kirkegaard
wiley +1 more source
Journal of Economic Surveys, Volume 39, Issue 5, Page 1971-1998, December 2025.ABSTRACT This study reports the results of a systematic literature review on auctions mechanism. Auctions are a very popular practice employed in many fields but does not exist a research that investigates the use of auctions under a cross‐disciplinary approach. This work is focused on analyzing which are the areas where auctions are mostly adopted and
Alberto Michele Felicetti +3 more
wiley +1 more source
Robust and MaxMin Optimization under Matroid and Knapsack Uncertainty Sets [PDF]
, 2011 Consider the following problem: given a set system (U,I) and an edge-weighted graph G = (U, E) on the same universe U, find the set A in I such that the Steiner tree cost with terminals A is as large as possible: "which set in I is the most difficult to ...
Gupta, Anupam +2 more
core
Does Twin Transition Facilitate Exporting? The Case of Logistics Innovation
Business Strategy and the Environment, Volume 34, Issue 7, Page 8194-8212, November 2025.ABSTRACT Firms need to overcome two hurdles to enter foreign markets: deciding whether to export and the intensity of their export sales. Although logistics plays a crucial role in exporting, the link between logistics innovation and exporting remains unexplored.
Areti Gkypali +2 more
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
Feature Cross Search via Submodular Optimization
, 2021 In this paper, we study feature cross search as a fundamental primitive in feature engineering. The importance of feature cross search especially for the linear model has been known for a while, with well-known textbook examples. In this problem, the goal is to select a small subset of features, combine them to form a new feature (called the crossed ...
Chen, Lin +4 more
openaire +4 more sources