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Streaming Algorithms for Maximizing Non-submodular Functions on the Integer Latticehing-return (DR) ratio ., we present a one pass streaming algorithm that gives a .-approximation, requires at most . space and . . update time per element. To the best of our knowledge, this is the first streaming algorithm on the integer lattice for this constrained maximization problem.Itinerant 发表于 2025-3-24 15:38:59
Causal Inference for Influence Propagation—Identifiability of the Independent Cascade Modeldentifiability or unidentifiability of parameters for several special structures including the Markovian IC model, semi-Markovian IC model, and IC model with a global unobserved variable. Parameter identifiability is important for other tasks such as influence maximization under the diffusion networks with unobserved confounding factors.insincerity 发表于 2025-3-24 20:11:04
Detecting Hate Speech Contents Using Embedding Modelsdictionary in a semi-supervised fashion. We conduct experiments on two popular datasets, which show that the combination of word embeddings and hate speech embeddings can produce promising results when compared with the methods that employ large-scale pre-trained language models.Fillet,Filet 发表于 2025-3-24 23:31:42
Die beobachteten Eigenschaften der Sterne,terministic streaming algorithm which provides an approximation ratio of . when . is monotone and . when . is non-monotone. For the general case, we propose a random streaming algorithm that provides an approximation ratio of . when . is monotone and . when . is non-monotone in expectation, where . and . are fixed inputs.