• Title/Summary/Keyword: Embeddings

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NORM ESTIMATES ON HARDY SPACES AND MULTIPLE SINGULAR INTEGRALS

  • Cho, Yong-Kum
    • Journal of the Korean Mathematical Society
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    • v.35 no.2
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    • pp.295-314
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    • 1998
  • In this article we examine certain distinctive features regarding Hardy spaces of both classical and product notions on $R^{N}$ with our focus on their interrelations through embeddings and restrictions. Applications of our results to multiple singular integrals are included.d.

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Next Location Prediction with a Graph Convolutional Network Based on a Seq2seq Framework

  • Chen, Jianwei;Li, Jianbo;Ahmed, Manzoor;Pang, Junjie;Lu, Minchao;Sun, Xiufang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.5
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    • pp.1909-1928
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    • 2020
  • Predicting human mobility has always been an important task in Location-based Social Network. Previous efforts fail to capture spatial dependence effectively, mainly reflected in weakening the location topology information. In this paper, we propose a neural network-based method which can capture spatial-temporal dependence to predict the next location of a person. Specifically, we involve a graph convolutional network (GCN) based on a seq2seq framework to capture the location topology information and temporal dependence, respectively. The encoder of the seq2seq framework first generates the hidden state and cell state of the historical trajectories. The GCN is then used to generate graph embeddings of the location topology graph. Finally, we predict future trajectories by aggregated temporal dependence and graph embeddings in the decoder. For evaluation, we leverage two real-world datasets, Foursquare and Gowalla. The experimental results demonstrate that our model has a better performance than the compared models.

Performance Comparison of Automatic Classification Using Word Embeddings of Book Titles (단행본 서명의 단어 임베딩에 따른 자동분류의 성능 비교)

  • Yong-Gu Lee
    • Journal of the Korean Society for information Management
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    • v.40 no.4
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    • pp.307-327
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    • 2023
  • To analyze the impact of word embedding on book titles, this study utilized word embedding models (Word2vec, GloVe, fastText) to generate embedding vectors from book titles. These vectors were then used as classification features for automatic classification. The classifier utilized the k-nearest neighbors (kNN) algorithm, with the categories for automatic classification based on the DDC (Dewey Decimal Classification) main class 300 assigned by libraries to books. In the automatic classification experiment applying word embeddings to book titles, the Skip-gram architectures of Word2vec and fastText showed better results in the automatic classification performance of the kNN classifier compared to the TF-IDF features. In the optimization of various hyperparameters across the three models, the Skip-gram architecture of the fastText model demonstrated overall good performance. Specifically, better performance was observed when using hierarchical softmax and larger embedding dimensions as hyperparameters in this model. From a performance perspective, fastText can generate embeddings for substrings or subwords using the n-gram method, which has been shown to increase recall. The Skip-gram architecture of the Word2vec model generally showed good performance at low dimensions(size 300) and with small sizes of negative sampling (3 or 5).

HEPTAGONAL KNOTS AND RADON PARTITIONS

  • Huh, Young-Sik
    • Journal of the Korean Mathematical Society
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    • v.48 no.2
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    • pp.367-382
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    • 2011
  • We establish a necessary and sufficient condition for a heptagonal knot to be figure-8 knot. The condition is described by a set of Radon partitions formed by vertices of the heptagon. In addition we relate this result to the number of nontrivial heptagonal knots in linear embeddings of the complete graph $K_7$ into $\mathbb{R}^3$.

GEOMETRIC SIMPLICIAL EMBEDDINGS OF ARC-TYPE GRAPHS

  • Parlier, Hugo;Weber, Ashley
    • Journal of the Korean Mathematical Society
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    • v.57 no.5
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    • pp.1103-1118
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    • 2020
  • In this paper, we investigate a family of graphs associated to collections of arcs on surfaces. These multiarc graphs naturally interpolate between arc graphs and flip graphs, both well studied objects in low dimensional geometry and topology. We show a number of rigidity results, namely showing that, under certain complexity conditions, that simplicial maps between them only arise in the "obvious way". We also observe that, again under necessary complexity conditions, subsurface strata are convex. Put together, these results imply that certain simplicial maps always give rise to convex images.

EMBEDDING RIEMANNIAN MANIFOLDS VIA THEIR EIGENFUNCTIONS AND THEIR HEAT KERNEL

  • Abdalla, Hiba
    • Bulletin of the Korean Mathematical Society
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    • v.49 no.5
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    • pp.939-947
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    • 2012
  • In this paper, we give a generalization of the embeddings of Riemannian manifolds via their heat kernel and via a finite number of eigenfunctions. More precisely, we embed a family of Riemannian manifolds endowed with a time-dependent metric analytic in time into a Hilbert space via a finite number of eigenfunctions of the corresponding Laplacian. If furthermore the volume form on the manifold is constant with time, then we can construct an embedding with a complete eigenfunctions basis.

Area-Optimization for VLSI by CAD (CAD에 의한 VLSI 설계를 위한 면적 최적화)

  • Yi, Cheon-Hee
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.24 no.4
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    • pp.708-712
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    • 1987
  • This paper deals with minimizing layout area of VLSI design. A long wire in a VLSI layout causes delay which can be reduced by using a driver. There can be significant area increase when many drivers are introduced in a layout. This paper describes a method to obtain tight bound on the worst-case increase in area when drivers are introduced along many long wires in a layout. The area occupied by minimum-area embedding for a circuit can depend on the aspect ratio of the bounding rectangle of the layout. This paper presents a separator-based area optimal embeddings for VLSI graphs in rectangles of several aspect ratios.

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The Fibonacci Edge Labeling on Fibonacci Trees

  • Kim, yong-Seok
    • Proceedings of the IEEK Conference
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    • 2000.07b
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    • pp.731-734
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    • 2000
  • We present a novel graph labeling problem called Fibonacci edge labeling. The constraint in this labeling is placed on the allowable edge label which is the difference between the labels of endvertices of an edge. Each edge label should be (3m+2)-th Fibonacci numbers. We show that every Fibonacci tree can be labeled Fibonacci edge labeling. The labelings on the Fibonacci trees are applied to their embeddings into Fibonacci Circulants.

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