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Complexity and Intractability: Limitations to Implementation in Analytical Cartography
2000
Cartography and Geographic Information Science
The three sub-areas are map projections, map feature labeling, and map generalization. ...
The computational complexity of algorithms is an important consideration for all computer systems, including geographic information systems and mapping systems. ...
The inverse transformation is estimable on an entire regularly spaced grid of n(= m-by-m) (x, y) points in O(n log n) time. ...
doi:10.1559/152304000783547849
fatcat:pf6nayh4lvfipo7uzaq4jndury
Spike sorting: Bayesian clustering of non-stationary data
2006
Journal of Neuroscience Methods
At a second stage transition probabilities between candidate mixtures are computed, and a globally optimal clustering is found as the MAP solution of the resulting probabilistic model. ...
We propose an automated technique for the clustering of non-stationary Gaussian sources in a Bayesian framework. ...
,πn (P 1 , .., P n ) = n i=1 π i D kl (G(x|µ i , Σ i ), G(x|µ * , Σ * )) (5) = H(G(x|µ * , Σ * )) − n i=1 π i H(G(x|µ i , Σ i )) = 1 2 (log |Σ * | − n i=1 π i log |Σ i |) using this identity in (3) , ...
doi:10.1016/j.jneumeth.2006.04.023
pmid:16828167
fatcat:dhy2v44sj5aslmuu566vers6my
Generative Model for Proposing Drug Candidates Satisfying Anticancer Properties Using a Conditional Variational Autoencoder
2020
ACS Omega
We confirm that the generated fingerprints, not included in the training data set, represent the desired property using the CVAE model. ...
In addition, our method can be used as a query expansion method for searching databases because fingerprints generated using our method can be regarded as expanded queries. ...
Mean −log GI50 of molecules in the test set that is highly similar to FPs generated from the model. We used five different segments of the target label to train the model and generate FPs. ...
doi:10.1021/acsomega.0c01149
pmid:32775866
pmcid:PMC7407547
fatcat:imivtfpi2va5fcymmngtphnefi
An Algorithmic Study of Fully Dynamic Independent Sets for Map Labeling
2022
ACM Journal of Experimental Algorithmics
We conclude with an algorithm that maintains a 2-approximate Max-IS for dynamic sets of unit-height and arbitrary-width rectangles with \( O(\log ^2 n + \omega \log n) \) update time, where \( \omega \ ...
In a subsequent algorithm, we establish the trade-off between approximation quality \( 2(1+\frac{1}{k}) \) and update time \( O(k^2\log n) \) , for \( k\in \mathbb {N} \) . ...
Corollary 5 . 5 We can maintain a 4-approximate Max-IS of a dynamic set of unit squares, in amortized O ( log n log log n ) update time.
1. 8 : 8 S 88 .Bhore et al. ...
doi:10.1145/3514240
fatcat:tekdybdy6bdbrfapw6of7ev2by
Solving the symmetric tridiagonal eigenvalue problem on hypercubes
1993
Computers and Mathematics with Applications
The corresponding eigenvectors problem can be solved in O(log n) time on the same networks. ...
O(ml logn) time using O(n2/logn) processors, where ml is the number of iterations. ...
., n = 2 r. Therefore, there are log n + 2 stages in this network, and the computation time is only O(log n) time. ...
doi:10.1016/0898-1221(93)90135-i
fatcat:3zkqh37eabdchktbypzyvjsyma
On the Rigidity of Sparse Random Graphs
2016
Journal of Graph Theory
We show that in the sparser case $\omega(\frac 1 n)\leq p\leq \frac{\log n}{n}+\omega(\frac 1n)$, it holds whp that $G$'s $2$-core is rigid. ...
A graph with a trivial automorphism group is said to be rigid. Wright proved that for $\frac{\log n}{n}+\omega(\frac 1n)\leq p\leq \frac 12$ a random graph $G\in G(n,p)$ is rigid whp. ...
The most interesting range of this statement is p ≤ log n+(1+ ) log log n n . ...
doi:10.1002/jgt.22073
fatcat:6sxkbmwvbraofoyidzaqzbwpom
Semi-supervised Learning for Aggregated Multilayer Graphs Using Diffuse Interface Methods and Fast Matrix-Vector Products
2021
SIAM Journal on Mathematics of Data Science
In particular, we test the performance of our method on data sets with up to 10 million nodes per layer as well as up to 104 dimensions, resulting in graphs with up to 52 layers. ...
Besides the treatment of various applications with an inherent multilayer structure, we present a very flexible approach that interprets high-dimensional data in a low-dimensional multilayer graph representation ...
functional (5.1) in the multiclass case, where \omega (x i ) is a penalty parameter that is equal to the constant \omega 0 \gg 0 for labeled vertices x i and 0 for unlabeled vertices. ...
doi:10.1137/20m1352028
fatcat:3wrtqnekbnghllv6anwq5lk3wa
From Gap-Exponential Time Hypothesis to Fixed Parameter Tractable Inapproximability: Clique, Dominating Set, and More
2020
SIAM journal on computing (Print)
By outputting any single vertex, we get a trivial polynomial-time n-approximation algorithm. The bound can be improved to O( n log n ) and even to O( n(log log n) 2 log 3 n ) with clever ideas [41] . ...
f that are independent of N (for Clique, we want f (OPT) = \omega (1))? ...
Furthermore, 2 \Omega (log 2/3 n) -factor inapproximability is known under the planted clique hypothesis [4] and, under ETH (respectively, Gap-ETH), n 1/ poly log log n (respectively, n o(1) ) factor ...
doi:10.1137/18m1166869
fatcat:cfjriedfenae7escnsgsb3xvuu
Counting Solutions to Random CNF Formulas
2021
SIAM journal on computing (Print)
We give the first efficient algorithm to approximately count the number of solutions in the random k-SAT model when the density of the formula scales exponentially with k. ...
The main challenge in our setting is to account for the presence of high-degree variables whose marginal distributions are hard to control and which cause significant correlations within the formula. ...
In contrast, for a random k-CNF formula, although the average degree of variables is low, with high probability there are variables with degrees as high as \Omega (log n/log log n). ...
doi:10.1137/20m1351527
fatcat:zzdf76xssngipefh5khhqr73kq
Moments of Uniform Random Multigraphs with Fixed Degree Sequences
2020
SIAM Journal on Mathematics of Data Science
We study the expected adjacency matrix of a uniformly random multigraph with fixed degree sequence \bfd \in \BbbZ n + . ...
Its structure is well understood for large, sparse, simple graphs: the expected number of edges between nodes i and j is roughly Many network data sets are neither large, sparse, nor simple, and in these ...
(f) Approximation of \sigma ij = \sigma (Wij) via (3.16). Note the log-log axis. ...
doi:10.1137/19m1288772
fatcat:sqpg5kntafgbpk6berbeb6qls4
Artificial Neural Networks for Galaxy Clustering. Learning from the two-point correlation function of BOSS galaxies
[article]
2021
arXiv
pre-print
The training set is constructed from log-normal mock catalogues which reproduce the clustering of the Baryon Oscillation Spectroscopic Survey (BOSS) galaxies. ...
We test this new Artificial Neural Network on real BOSS data, finding Omega m=0.309p/m0.008, which is remarkably consistent with standard analysis results. ...
During the training process, the interval of the labels, that is 0.24 ≤ Ω m ≤ 0.38, has been mapped into [0, 1] through the following linear operation: L = l − 0.24 0.14 , (9) where l is the original label ...
arXiv:2107.11397v1
fatcat:uk2nrpv6orgsdhpet4d6rorw5u
Inapproximability of the Independent Set Polynomial in the Complex Plane
2020
SIAM journal on computing (Print)
It is known that if \lambda is a real number in the interval ( - \lambda \ast , \lambda c) then there is a fully polynomial time approximation scheme (FPTAS) for approximating Z G (\lambda ) on graphs ...
In fact, when \lambda is outside of \Lambda \Delta and is not a positive real number, we give the stronger result that approximating Z G (\lambda ) is actually \#P-hard. ...
If \lambda is in the interval - \lambda \ast < \lambda < \lambda c , there is a fully polynomial time approximation scheme (FPTAS) for approximating Z G (\lambda ) on graphs G \in \scrG \Delta . ...
doi:10.1137/18m1184485
fatcat:ajevdohpnbeubidanwvxv7aa7u
On approximate decidability of minimal programs
[article]
2014
arXiv
pre-print
We investigate whether the task of determining minimal indices can be solved in an approximate sense. ...
Our first question, regarding the set of minimal indices, is whether there exists an algorithm which can correctly label 1 out of k indices as either minimal or non-minimal. ...
The authors thank Sanjay Jain for useful comments on the presentation of this work and are grateful to Sasha Shen and Nikolay Vereshchagin for their help with the "warm-up" in Section 2. ...
arXiv:1409.0496v1
fatcat:ukz6f6krrjb23gn4ockvrde6ny
On the benefits for model regularization of a variational formulation of GTM
2008
2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)
In this formulation, GTM is prone to data overfitting unless a regularization mechanism is included. ...
Generative Topographic Mapping (GTM) is a manifold learning model for the simultaneous visualization and clustering of multivariate data. ...
The original three-class structure of the Wine data is only recognized by labelling each class differently in the display. ...
doi:10.1109/ijcnn.2008.4634005
dblp:conf/ijcnn/OlierV08a
fatcat:6o5msr7okzhinluxr3hff24sv4
Minimum Label s-t Cut has Large Integrality Gaps
[article]
2019
arXiv
pre-print
As Min Label s-t Cut is NP-hard and the linear programming technique is a main approach to design approximation algorithms, our results give negative answer to the hope that designs better approximation ...
In this paper, we study two linear programs for Min Label s-t Cut, proving that both of them have large integrality gaps, namely, Omega(m) and Omega(m^1/3-epsilon) for the respective linear programs, where ...
Acknowledgements Peng Zhang is supported by the National Natural Science Foundation of China (61672323), the Natural Science Foundation of Shandong Province (ZR2016AM28), and the Fundamental Research Funds ...
arXiv:1908.11491v1
fatcat:axgcdul3lncgtewearlrinukqu
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