tangle
发表于 2025-3-30 09:42:46
moment of one-dimensional data streams..Prior work presented a nearly space-optimal algorithm for estimating .. for . ∈ and . ∈ . Here, we complement that work by presenting a nearly space-optimal algorithm for estimating .. for . ∈ and . ∈ .
抛物线
发表于 2025-3-30 13:44:00
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QUAIL
发表于 2025-3-30 18:49:18
Power Indices in Spanning Connectivity Games,to compute the Banzhaf indices. This answers (positively) an open question of whether computing Shapley-Shubik indices for a simple game represented by the set of minimal winning coalitions is NP-hard.
呼吸
发表于 2025-3-30 21:06:37
Three Results on Frequency Assignment in Linear Cellular Networks,etitive ratio .. Second, in the general online case, where the requests arrive and depart over time, we improve the current lower bound on the (asymptotic) competitive ratio to .. Third, we prove that the offline version of this problem is .-complete.
哑巴
发表于 2025-3-31 02:34:03
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发起
发表于 2025-3-31 06:01:23
5 Miscellaneous Compounds, CnH(2n-6), both shown to be APX-hard previously. We show in this paper that MFR has a polynomial time .(log.)-factor approximation. We also consider Maximum Fragment Identification (MFI), which is the complementary version of MFR; and Maximum SNP Identification (MSI), which is the complementary version of MSR
dialect
发表于 2025-3-31 11:12:30
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臭了生气
发表于 2025-3-31 13:21:08
Densities of Aromatic Hydrocarbonsetitive ratio .. Second, in the general online case, where the requests arrive and depart over time, we improve the current lower bound on the (asymptotic) competitive ratio to .. Third, we prove that the offline version of this problem is .-complete.
acetylcholine
发表于 2025-3-31 17:49:34
Densities of Aromatic Hydrocarbonsefore we give some general methods to construct equiseparable pairs and compare the methods in the case of Wiener index. More specifically, we show that terminal Wiener index is degenerative to some extent.
Arctic
发表于 2025-3-31 21:52:15
Algorithmic Challenge in Online Advertising,eval, statistical modeling, machine learning, classification, optimization, and microeconomics. The central challenge of computational advertising is to find the “best match” between a given user in a given context and a suitable advertisement. The context could be a user entering a query in a searc