Results 61 to 70 of about 9,987 (195)
An Ensemble Hypergraph Learning Framework for Recommendation
, 2021 Recommender systems are designed to predict user preferences over collections of items. These systems process users’ previous interactions to decide which items should be ranked higher to satisfy their desires. An ensemble recommender system can achieve great recommendation performance by effectively combining the decisions generated by individual ...
Gharahighehi, Alireza +2 more
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Cognitive Networks for Knowledge Modeling: A Gentle Introduction for Data‐ and Cognitive Scientists
WIREs Cognitive Science, Volume 17, Issue 2, March/April 2026.Cognitive network science helps organize associative knowledge—that is, the connections between concepts. These connections play a key role in cognitive processes such as language understanding and context interpretation, even though they are not obvious in language use.
Edith Haim, Massimo Stella
wiley +1 more source
MHCLSyn: Multi-View Hypergraph Contrastive Learning for Synergistic Drug Combination Prediction
Big Data Mining and AnalyticsIn the field of cancer treatment, drug combination therapy appears to be a promising treatment strategy compared to monotherapy. Recently, plenty of computational models are gradually applied to prioritize synergistic drug combinations.
Lei Li +4 more
doaj +1 more source
Adaptive Learning a Hidden Hypergraph
, 2016 Learning a hidden hypergraph is a natural generalization of the classical group testing problem that consists in detecting unknown hypergraph $H_{un}=H(V,E)$ by carrying out edge-detecting tests. In the given paper we focus our attention only on a specific family $\mathcal{F}(t,s,\ell)$ of localized hypergraphs for which the total number of vertices ...
D'yachkov, A. G. +3 more
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Zarankiewicz bounds from distal regularity lemma
Bulletin of the London Mathematical Society, Volume 58, Issue 3, March 2026.Abstract Since Kővári, Sós and Turán proved upper bounds for the Zarankiewicz problem in 1954, much work has been undertaken to improve these bounds, and some have done so by restricting to particular classes of graphs. In 2017, Fox, Pach, Sheffer, Suk and Zahl proved better bounds for semialgebraic binary relations, and this work was extended by Do in
Mervyn Tong
wiley +1 more source
Labeling Gaps Between Words: Recognizing Overlapping Mentions with Mention Separators
, 2017 In this paper, we propose a new model that is capable of recognizing overlapping mentions. We introduce a novel notion of mention separators that can be effectively used to capture how mentions overlap with one another.
Lu, Wei, Muis, Aldrian Obaja
core +1 more source
Learning on Partial-Order Hypergraphs
Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18, 2018 Graph-based learning methods explicitly consider the relations between two entities (i.e., vertices) for learning the prediction function. They have been widely used in semi-supervised learning, manifold ranking, and clustering, among other tasks.
Fuli Feng +4 more
openaire +1 more source
Journal of the London Mathematical Society, Volume 113, Issue 3, March 2026.Abstract Heilbronn's triangle problem is a classical question in discrete geometry. It asks to determine the smallest number Δ=Δ(N)$\Delta = \Delta (N)$ for which every collection in N$N$ points in the unit square spans a triangle with area at most Δ$\Delta$.
Dmitrii Zakharov
wiley +1 more source
On interference among moving sensors and related problems
, 2017 We show that for any set of $n$ points moving along "simple" trajectories (i.e., each coordinate is described with a polynomial of bounded degree) in $\Re^d$ and any parameter $2 \le k \le n$, one can select a fixed non-empty subset of the points of size
De Carufel, Jean-Lou +5 more
core +1 more source
Stall‐Free Asynchronous State Repartitioning With a Proactive Workload Tracking Window
Concurrency and Computation: Practice and Experience, Volume 38, Issue 3, February 2026.ABSTRACT High‐throughput stateful applications rely on dynamic data repartitioning to adapt to changing workloads, but this process presents significant challenges. This paper provides a detailed analysis of such challenges, drilling down into the tradeoffs between adaptation, computational overhead, and service availability. We identify that a primary
Douglas Pereira Luiz +1 more
wiley +1 more source