Results 81 to 90 of about 1,516 (207)
On Unconstrained Quasi-Submodular Function Optimization
Proceedings of the AAAI Conference on Artificial Intelligence, 2015 With the extensive application of submodularity, its generalizations are constantly being proposed. However, most of them are tailored for special problems. In this paper, we focus on quasi-submodularity, a universal generalization, which satisfies weaker properties than submodularity but still enjoys favorable performance in ...
Jincheng Mei, Kang Zhao, Bao-Liang Lu
openaire +2 more sources
Online Submodular Maximization via Online Convex Optimization [PDF]
We study monotone submodular maximization under general matroid constraints in the online setting. We prove that online optimization of a large class of submodular functions, namely, threshold potential functions, reduces to online convex optimization ...
Ioannidis, Stratis +4 more
core +4 more sources
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
Robust Budget Allocation Via Continuous Submodular Functions [PDF]
, 2020 The optimal allocation of resources for maximizing influence, spread of information or coverage, has gained attention in the past years, in particular in machine learning and data mining.
Staib, Matthew +1 more
core +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
An Approximation Algorithm for Risk-Averse Submodular Optimization [PDF]
, 2020 Whole version for WAFR, 2018 final ...
Lifeng Zhou 0001, Pratap Tokekar
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Game‐Theoretic Multi‐Agent Dynamic Traffic Assignment Using Congestion‐Aware Adaptive Learning
IET Intelligent Transport Systems, Volume 20, Issue 1, January/December 2026.This paper proposes a novel game‐theoretic multi‐agent framework for dynamic traffic assignment problems, integrating congestion‐aware adaptive learning to simultaneously reduce individual travel time and improve overall network efficiency under dynamic congestion.
Dandan Wu +4 more
wiley +1 more source
Scalable Submodular Policy Optimization via Pruned Submodularity Graph
CoRR16 ...
Aditi Anand +2 more
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On the Supremum of Singleton Ratios in Submodular Functions
MathematicsLet N be a finite set of cardinality n, and let a∈N. A submodular function f on N with f(a)=1 is defined to be a-reduced if, for any decomposition f=g+h into submodular functions, where h does not depend on a, it follows that h is identically zero.
Laszlo Csirmaz
doaj +1 more source
IET Renewable Power Generation, Volume 20, Issue 1, January/December 2026.ABSTRACT This paper presents a two‐level hierarchical adaptive damping control strategy designed to robustly mitigate inter‐area low‐frequency oscillations (LFOs) in large‐scale power systems featuring high shares of doubly‐fed induction generator (DFIG) wind farms. The proposed structure integrates a central wide‐area damping controller (WADC), driven
Mohsen Darabian +4 more
wiley +1 more source