Relevant bibliographies by topics / Embedding Analysis

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Embedding Analysis'

Author: Grafiati
Published: 6 September 2023
Last updated: 31 July 2025

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Journal articles on the topic "Embedding Analysis"

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Lainscsek, Claudia, and Terrence J. Sejnowski. "Delay Differential Analysis of Time Series." Neural Computation 27, no. 3 (2015): 594–614. http://dx.doi.org/10.1162/neco_a_00706.

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Nonlinear dynamical system analysis based on embedding theory has been used for modeling and prediction, but it also has applications to signal detection and classification of time series. An embedding creates a multidimensional geometrical object from a single time series. Traditionally either delay or derivative embeddings have been used. The delay embedding is composed of delayed versions of the signal, and the derivative embedding is composed of successive derivatives of the signal. The delay embedding has been extended to nonuniform embeddings to take multiple timescales into account. Bot
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Mihail Mateev. "Comparative Analysis on Implementing Embeddings for Image Analysis." Journal of Information Systems Engineering and Management 10, no. 17s (2025): 89–102. https://doi.org/10.52783/jisem.v10i17s.2710.

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This research explores how artificial intelligence enhances construction maintenance and diagnostics, achieving 95% accuracy on a dataset of 10,000 cases. The findings highlight AI's potential to revolutionize predictive maintenance in the industry. The growing adoption of image embeddings has transformed visual data processing across AI applications. This study evaluates embedding implementations in major platforms, including Azure AI, OpenAI's GPT-4 Vision, and frameworks like Hugging Face, Replicate, and Eden AI. It assesses their scalability, accuracy, cost-effectiveness, and integration f
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Samko, Natasha. "Embeddings of weighted generalized Morrey spaces into Lebesgue spaces on fractal sets." Fractional Calculus and Applied Analysis 22, no. 5 (2019): 1203–24. http://dx.doi.org/10.1515/fca-2019-0064.

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Abstract We study embeddings of weighted local and consequently global generalized Morrey spaces defined on a quasi-metric measure set (X, d, μ) of general nature which may be unbounded, into Lebesgue spaces Ls(X), 1 ≤ s ≤ p < ∞. The main motivation for obtaining such an embedding is to have an embedding of non-separable Morrey space into a separable space. In the general setting of quasi-metric measure spaces and arbitrary weights we give a sufficient condition for such an embedding. In the case of radial weights related to the center of local Morrey space, we obtain an effective sufficien
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Sabbeh, Sahar F., and Heba A. Fasihuddin. "A Comparative Analysis of Word Embedding and Deep Learning for Arabic Sentiment Classification." Electronics 12, no. 6 (2023): 1425. http://dx.doi.org/10.3390/electronics12061425.

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Sentiment analysis on social media platforms (i.e., Twitter or Facebook) has become an important tool to learn about users’ opinions and preferences. However, the accuracy of sentiment analysis is disrupted by the challenges of natural language processing (NLP). Recently, deep learning models have proved superior performance over statistical- and lexical-based approaches in NLP-related tasks. Word embedding is an important layer of deep learning models to generate input features. Many word embedding models have been presented for text representation of both classic and context-based word embed
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He, Hongliang, Junlei Zhang, Zhenzhong Lan, and Yue Zhang. "Instance Smoothed Contrastive Learning for Unsupervised Sentence Embedding." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 11 (2023): 12863–71. http://dx.doi.org/10.1609/aaai.v37i11.26512.

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Contrastive learning-based methods, such as unsup-SimCSE, have achieved state-of-the-art (SOTA) performances in learning unsupervised sentence embeddings. However, in previous studies, each embedding used for contrastive learning only derived from one sentence instance, and we call these embeddings instance-level embeddings. In other words, each embedding is regarded as a unique class of its own, which may hurt the generalization performance. In this study, we propose IS-CSE (instance smoothing contrastive sentence embedding) to smooth the boundaries of embeddings in the feature space. Specifi
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Srinidhi, K., T. L.S Tejaswi, CH Rama Rupesh Kumar, and I. Sai Siva Charan. "An Advanced Sentiment Embeddings with Applications to Sentiment Based Result Analysis." International Journal of Engineering & Technology 7, no. 2.32 (2018): 393. http://dx.doi.org/10.14419/ijet.v7i2.32.15721.

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We propose an advanced well-trained sentiment analysis based adoptive analysis “word specific embedding’s, dubbed sentiment embedding’s”. Using available word and phrase embedded learning and trained algorithms mainly make use of contexts of terms but ignore the sentiment of texts and analyzing the process of word and text classifications. sentimental analysis on unlike words conveying same meaning matched to corresponding word vector. This problem is bridged by combining encoding opinion carrying text with sentiment embeddings words. But performing sentimental analysis on e-commerce, social n
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Ruskanda, Fariska Zakhralativa, Stefanus Stanley Yoga Setiawan, Nadya Aditama, and Masayu Leylia Khodra. "Sentiment Analysis of Sentence-Level using Dependency Embedding and Pre-trained BERT Model." PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic 11, no. 1 (2023): 171–80. http://dx.doi.org/10.33558/piksel.v11i1.6938.

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Sentiment analysis is a valuable field of research in NLP with many applications. Dependency tree is one of the language features that can be utilized in this field. Dependency embedding, as one of the semantic representations of a sentence, has shown to provide more significant results compared to other embeddings, which makes it a potential way to improve the performance of sentiment analysis tasks. This study aimed to investigate the effect of dependency embedding on sentence-level sentiment analysis through experimental research. The study replaced the Vocabulary Graph embedding in the VGC
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Truică, Ciprian-Octavian, Elena-Simona Apostol, Maria-Luiza Șerban, and Adrian Paschke. "Topic-Based Document-Level Sentiment Analysis Using Contextual Cues." Mathematics 9, no. 21 (2021): 2722. http://dx.doi.org/10.3390/math9212722.

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Document-level Sentiment Analysis is a complex task that implies the analysis of large textual content that can incorporate multiple contradictory polarities at the phrase and word levels. Most of the current approaches either represent textual data using pre-trained word embeddings without considering the local context that can be extracted from the dataset, or they detect the overall topic polarity without considering both the local and global context. In this paper, we propose a novel document-topic embedding model, DocTopic2Vec, for document-level polarity detection in large texts by emplo
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Li, Qizhi, Xianyong Li, Yajun Du, Yongquan Fan, and Xiaoliang Chen. "A New Sentiment-Enhanced Word Embedding Method for Sentiment Analysis." Applied Sciences 12, no. 20 (2022): 10236. http://dx.doi.org/10.3390/app122010236.

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Since some sentiment words have similar syntactic and semantic features in the corpus, existing pre-trained word embeddings always perform poorly in sentiment analysis tasks. This paper proposes a new sentiment-enhanced word embedding (S-EWE) method to improve the effectiveness of sentence-level sentiment classification. This sentiment enhancement method takes full advantage of the mapping relationship between word embeddings and their corresponding sentiment orientations. This method first converts words to word embeddings and assigns sentiment mapping vectors to all word embeddings. Then, wo
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Moudhich, Ihab, and Abdelhadi Fennan. "Evaluating sentiment analysis and word embedding techniques on Brexit." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 1 (2024): 695–702. https://doi.org/10.11591/ijai.v13.i1.pp695-702.

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In this study, we investigate the effectiveness of pre-trained word embeddings for sentiment analysis on a real-world topic, namely Brexit. We compare the performance of several popular word embedding models such global vectors for word representation (GloVe), FastText, word to vec (word2vec), and embeddings from language models (ELMo) on a dataset of tweets related to Brexit and evaluate their ability to classify the sentiment of the tweets as positive, negative, or neutral. We find that pre-trained word embeddings provide useful features for sentiment analysis and can significantly improve t
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Dissertations / Theses on the topic "Embedding Analysis"

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Abdikalikova, Zamira. "Embedding theorems for spaces with multiweighted derivatives." Licentiate thesis, Luleå tekniska universitet, Matematiska vetenskaper, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-26092.

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This Licentiate Thesis consists of four chapters, which deal with a new Sobolev type function space called the space with multiweighted derivatives. This space is a generalization of the usual one dimensional Sobolev space. Chapter 1 is an introduction, where, in particular, the importance to study function spaces with weights is discussed and motivated. In Chapter 2 we consider and analyze some results of L. D. Kudryavtsev, where he investigated one dimensional Sobolev spaces. Moreover, in this chapter we present and prove analogous results by B. L. Baidel'dinov for generalized Sobolev spaces
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JOHANSSON, SIMON, and EMIL LENNGREN. "Steganographic embedding and steganalysisevaluation : An evaluation of common methods for steganographic embedding and analysis indigital images." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-157499.

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Steganography is the technique that hides secret messages in seemingly inoccuous data. Steganalysis is the technique that is used to discover the use of steganography. Usuallyit is difficult to extract the exact hidden message because itis usually encrypted. Though often it is enough to merely uncover the use of steganography to reveal important information.In this report we discuss some common methods for steganography in images, as well as some methods of analysis,both general and targeted towards specific methods. We test how well the methods fare against each other and what one should cons
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Rossiter, Darien Elizabeth. "Embedding e-learning in universities : analysis and conceptualisation of change processes." Thesis, Queensland University of Technology, 2006. https://eprints.qut.edu.au/16223/1/Darien_Rossiter_Thesis.pdf.

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E-learning has acquired the status of a "radical innovation" in higher education over the past decade. This claim is contestable, but certainly as the latest educational innovation, it can be attributed with introducing significant disruption into many facets of university life, reaching well beyond the traditional activities associated with the classroom pedagogies. In Australian universities, there are many now who simply take e-learning for granted as accepted teaching and learning practice (Oliver, 2004). Conversely, there are others who forecast its demise, claiming that, like previous ed
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Rossiter, Darien Elizabeth. "Embedding e-learning in universities : analysis and conceptualisation of change processes." Queensland University of Technology, 2006. http://eprints.qut.edu.au/16223/.

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E-learning has acquired the status of a "radical innovation" in higher education over the past decade. This claim is contestable, but certainly as the latest educational innovation, it can be attributed with introducing significant disruption into many facets of university life, reaching well beyond the traditional activities associated with the classroom pedagogies. In Australian universities, there are many now who simply take e-learning for granted as accepted teaching and learning practice (Oliver, 2004). Conversely, there are others who forecast its demise, claiming that, like previous ed
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Algervik, Robert. "Embedding Theorems for Mixed Norm Spaces and Applications." Doctoral thesis, Karlstads universitet, Avdelningen för matematik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-5646.

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This thesis is devoted to the study of mixed norm spaces that arise in connection with embeddings of Sobolev and Besov type spaces. We study different structural, integrability, and smoothness properties of functions satisfying certain mixed norm conditions. Conditions of this type are determined by the behaviour of linear sections of functions. The work in this direction originates in a paper due to Gagliardo (1958), and was further developed by Fournier (1988), by Blei and Fournier (1989), and by Kolyada (2005). Here we continue these studies. We obtain some refinements of known embeddings f
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Chen, Brian 1972. "Design and analysis of digital watermarking, information embedding, and data hiding systems." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/31086.

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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.<br>Includes bibliographical references (p. 139-142).<br>Digital watermarking, information embedding, and data hiding systems embed information, sometimes called a digital watermark, inside a host signal, which is typically an image, audio signal, or video signal. The host signal is not degraded unacceptably in the process, and one can recover the watermark even if the composite host and watermark signal undergo a variety of corruptions and attacks as long as these corruptions do n
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Perinelli, Alessio. "A new approach to optimal embedding of time series." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/280754.

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The analysis of signals stemming from a physical system is crucial for the experimental investigation of the underlying dynamics that drives the system itself. The field of time series analysis comprises a wide variety of techniques developed with the purpose of characterizing signals and, ultimately, of providing insights on the phenomena that govern the temporal evolution of the generating system. A renowned example in this field is given by spectral analysis: the use of Fourier or Laplace transforms to bring time-domain signals into the more convenient frequency space allows to disclose the
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Perinelli, Alessio. "A new approach to optimal embedding of time series." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/280754.

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The analysis of signals stemming from a physical system is crucial for the experimental investigation of the underlying dynamics that drives the system itself. The field of time series analysis comprises a wide variety of techniques developed with the purpose of characterizing signals and, ultimately, of providing insights on the phenomena that govern the temporal evolution of the generating system. A renowned example in this field is given by spectral analysis: the use of Fourier or Laplace transforms to bring time-domain signals into the more convenient frequency space allows to disclose the
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Zha, Xiao. "Topological Data Analysis on Road Network Data." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu155563664988436.

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Liang, Qingqing. "Systematic Analysis and Optimization of Broadband Noise and Linearity in SiGe HBTs." Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/6980.

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Noise and linearity are the two key concerns in RF transceiver systems. However, the impact of circuit topology and device technology on systems noise and linearity behaviors is poorly understood because of the complexity and diversity involved. There are two general questions that are addressed by the RF device and circuit designers: for a given device technology, how best to optimize the circuit topology; and for a given circuit topology, how best to optimize the device technology to improve the noise and linearity performance. In this dissertation, a systematic noise and linearity calc
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Books on the topic "Embedding Analysis"

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Fu, Yun, and Yunqian Ma, eds. Graph Embedding for Pattern Analysis. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-4457-2.

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K, Binienda Wieslaw, Kreider K. L, and Lewis Research Center, eds. Analysis of multiple cracks in an infinite functionally graded plate. National Aeronautics and Space Administration, Lewis Research Center, 1999.

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K, Binienda Wieslaw, Kreider K. L, and Lewis Research Center, eds. Analysis of multiple cracks in an infinite functionally graded plate. National Aeronautics and Space Administration, Lewis Research Center, 1999.

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Kootz, Elisabeth. Structural holes, market constraints, and embedding strategies: An empirical analysis of mergers & acquisitions in Germany. [s.n.], 1996.

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Seitz, Evan Elliott. Analysis of Conformational Continuum and Free-energy Landscapes from Manifold Embedding of Single-particle Cryo-EM Ensembles of Biomolecules. [publisher not identified], 2022.

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Simon, Barry. Harmonic analysis. American Mathematical Society, 2015.

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Jakobson, Dmitry, Pierre Albin, and Frédéric Rochon. Geometric and spectral analysis. American Mathematical Society, 2014.

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Milman, Mario. Extrapolation and optimal decompositions withapplications to analysis. Springer-Verlag, 1994.

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Milman, Mario. Extrapolation and optimal decompositions: With applications to analysis. Springer-Verlag, 1994.

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Edmunds, David E. Hardy Operators, Function Spaces and Embeddings. Springer Berlin Heidelberg, 2004.

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Book chapters on the topic "Embedding Analysis"

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Sidorova, Natalia, and Martin Steffen. "Embedding Chaos." In Static Analysis. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-47764-0_18.

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Berthelot, Jean-Michel. "6. The implications of ‘societal analysis’ for a programme of research." In Embedding Organizations. John Benjamins Publishing Company, 2000. http://dx.doi.org/10.1075/aios.4.09ber.

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Barrère-Maurisson, Marie-Agnes. "21. Societal analysis and social change in the family division of labour." In Embedding Organizations. John Benjamins Publishing Company, 2000. http://dx.doi.org/10.1075/aios.4.32bar.

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Sellier, François. "9. The contribution of societal analysis to the economic theory of the firm." In Embedding Organizations. John Benjamins Publishing Company, 2000. http://dx.doi.org/10.1075/aios.4.14sel.

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Härdle, Wolfgang Karl, Léopold Simar, and Matthias R. Fengler. "Locally Linear Embedding." In Applied Multivariate Statistical Analysis. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-63833-6_21.

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Härdle, Wolfgang Karl, Léopold Simar, and Matthias R. Fengler. "Stochastic Neighborhood Embedding." In Applied Multivariate Statistical Analysis. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-63833-6_22.

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Maurice, Marc. "2. The paradoxes of societal analysis. A review of the past and prospects for the future." In Embedding Organizations. John Benjamins Publishing Company, 2000. http://dx.doi.org/10.1075/aios.4.05mau.

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Kouropteva, Olga, Oleg Okun, and Matti Pietikäinen. "Incremental Locally Linear Embedding Algorithm." In Image Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11499145_53.

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Théret, Bruno. "7. Theoretical problems in international comparisons: Towards a reciprocal improvement of societal analysis and régulation theory by methodic structuralism." In Embedding Organizations. John Benjamins Publishing Company, 2000. http://dx.doi.org/10.1075/aios.4.10the.

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Ren, Peng, Furqan Aziz, Lin Han, Eliza Xu, Richard C. Wilson, and Edwin R. Hancock. "Geometricity and Embedding." In Similarity-Based Pattern Analysis and Recognition. Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5628-4_6.

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Conference papers on the topic "Embedding Analysis"

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Xu, Yang, and Wenliang Peng. "Code Search Oriented Node-Enhanced Control Flow Graph Embedding." In 2024 IEEE International Conference on Source Code Analysis and Manipulation (SCAM). IEEE, 2024. https://doi.org/10.1109/scam63643.2024.00016.

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Bollegala, Danushka. "Learning Meta Word Embeddings by Unsupervised Weighted Concatenation of Source Embeddings." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/563.

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Given multiple source word embeddings learnt using diverse algorithms and lexical resources, meta word embedding learning methods attempt to learn more accurate and wide-coverage word embeddings. Prior work on meta-embedding has repeatedly discovered that simple vector concatenation of the source embeddings to be a competitive baseline. However, it remains unclear as to why and when simple vector concatenation can produce accurate meta-embeddings. We show that weighted concatenation can be seen as a spectrum matching operation between each source embedding and the meta-embedding, minimising th
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Fu, Yun, and Thomas S. Huang. "Correlation Embedding Analysis." In 2008 15th IEEE International Conference on Image Processing. IEEE, 2008. http://dx.doi.org/10.1109/icip.2008.4712100.

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Dey, Sourya, Michael Robinson, Shauna Sweet, Andrew Lauziere, Jonathan Daugherty, and Caitlin Burgess. "Analyzing Large Language Model Behavior via Embedding Analysis." In 2024 AHFE International Conference on Human Factors in Design, Engineering, and Computing (AHFE 2024 Hawaii Edition). AHFE International, 2024. http://dx.doi.org/10.54941/ahfe1005724.

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The usage of large language models (LLMs) as a generative artificial intelligence tool is becoming increasingly widespread, yet there is limited understanding of the mechanisms by which prompts in whole or in part influence their behavior, capabilities, and limitations. In this paper, the authors conduct a mathematical and topological analysis of token embeddings – the first step in the computational workflow of LLMs. This work shows that the subspace where token embeddings lie is a stratified manifold with varying local dimension, and in those cases where semantically related tokens are co-lo
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Hui Xue and Song-Can Chen. "Alternative robust local embedding." In 2007 International Conference on Wavelet Analysis and Pattern Recognition. IEEE, 2007. http://dx.doi.org/10.1109/icwapr.2007.4420738.

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Ting, I.-Hsien, Kazunori Minetaki, Mei-Yun Hsu, and Chia-Sung Yen. "Applying Social Network Embedding and Word Embedding for Socialbots Detection." In ASONAM '23: International Conference on Advances in Social Networks Analysis and Mining. ACM, 2023. http://dx.doi.org/10.1145/3625007.3627306.

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Rodriguez, Alejandro, Korn Sooksatra, Pablo Rivas, et al. "An Empirical Analysis Towards Replacing Vocabulary-Rigid Embeddings by a Vocabulary-Free Mechanism." In LatinX in AI at International Conference on Machine Learning 2023. Journal of LatinX in AI Research, 2023. http://dx.doi.org/10.52591/lxai202307237.

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This paper addresses the limitations of subword based models in NLP by aligning the word embedding layer of a vocabulary-rigid transformer model to a vocabulary-free one. In order to do so, a CNN is trained to mimic the word embeddings layer of a BERT model, using a sequence of byte tokens as input. The study compares cosine-based and Euclidean-based loss functions for training the student network and finds better results with cosine-based metrics. The research contributes techniques for re-training transformer embedding layers and provides insights into loss function selection. The findings h
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Zheng, Q., and D. B. Skillicorn. "Spectral Embedding of Directed Networks." In ASONAM '15: Advances in Social Networks Analysis and Mining 2015. ACM, 2015. http://dx.doi.org/10.1145/2808797.2809310.

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Ghindici, Dorina, Gilles Grimaud, and Isabelle Simplot-Ryl. "Embedding verifiable information flow analysis." In the 2006 International Conference. ACM Press, 2006. http://dx.doi.org/10.1145/1501434.1501481.

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Oscar Deho, B., A. William Agangiba, L. Felix Aryeh, and A. Jeffery Ansah. "Sentiment Analysis with Word Embedding." In 2018 IEEE 7th International Conference on Adaptive Science & Technology (ICAST). IEEE, 2018. http://dx.doi.org/10.1109/icastech.2018.8506717.

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Reports on the topic "Embedding Analysis"

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Dunlavy, Daniel, Timothy Shead, Daniel Dunlavy, et al. Embedding Python for In-Situ Analysis. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1734473.

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McGarrigle, M. Embedding Building Information Modelling into Construction Technology and Documentation Courses. Unitec ePress, 2014. http://dx.doi.org/10.34074/rsrp.005.

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The aim of this research is to generate a resource to assist construction lecturers in identifying opportunities where Building Information Modelling [BIM] could be employed to augment the delivery of subject content within individual courses on construction technology programmes. The methodology involved a detailed analysis of the learning objectives and underpinning knowledge of the course content by topic area, within the residential Construction Systems 1 course presently delivered at Unitec on the National Diplomas in Architectural Technology[NDAT], Construction Management [NDCM] and Quan
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McGarrigle, M. Embedding Building Information Modelling into Construction Technology and Documentation Courses. Unitec ePress, 2014. http://dx.doi.org/10.34074/rsrp.005.

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The aim of this research is to generate a resource to assist construction lecturers in identifying opportunities where Building Information Modelling [BIM] could be employed to augment the delivery of subject content within individual courses on construction technology programmes. The methodology involved a detailed analysis of the learning objectives and underpinning knowledge of the course content by topic area, within the residential Construction Systems 1 course presently delivered at Unitec on the National Diplomas in Architectural Technology[NDAT], Construction Management [NDCM] and Quan
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Romova, Zina, and Martin Andrew. Embedding Learning for Future and Imagined Communities in Portfolio Assessment. Unitec ePress, 2015. http://dx.doi.org/10.34074/rsrp.42015.

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In tertiary contexts where adults study writing for future academic purposes, teaching and learning via portfolio provides them with multiple opportunities to create and recreate texts characteristic of their future and imagined discourse communities. This paper discusses the value of portfolios as vehicles for rehearsing membership of what Benedict Anderson (1983) called “imagined communities”, a concept applied by such scholars as Yasuko Kanno and Bonny Norton (2003). Portfolios can achieve this process of apprenticeship to a specialist discourse through reproducing texts similar to the auth
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Zhao, Yufei, Zhiwei Wang, Shangke Kuang, and Shuxin Zhang. A Meta Analysis of the Acupoint Catgut Embedding in the Treatment of Functional Constipation. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2025. https://doi.org/10.37766/inplasy2025.7.0017.

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Xiao, Yao, Jun Xiong, Yuntao Zeng, and Ming Gong. Systematic evaluation and Meta analysis of the treatment of allergic rhinitis with needle-embedding therapy. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2021. http://dx.doi.org/10.37766/inplasy2021.8.0029.

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Luo, Jing, Chen Zhang, Mengjie Xia, and Yuelian Chen. Acupoint catgut embedding reduces postoperative pain of mixed hemorrhoids: a meta-analysis of randomized controlled trials. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.2.0021.

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Abstract:
Review question / Objective: Can acupoint catgut embedding alleviate postoperative pain of mixed hemorrhoids? Condition being studied: Mixed hemorrhoids. Information sources: Two authors (JL and CZ) will examine the publications independently and extract data according to predefined criteria. RCTs will be assessed for the methodology, study design, inclusion and exclusion criteria, and outcome measures. The methodological quality of each RCT will be recorded for method of randomization, blinding, protocol violation, and allocation concealment Any disagreement will be resolved by consensus disc
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Xue, Feng, Hao Huang, Yiwei Fu, Bojun Feng, Weizhong Yan, and Tianyi Wang. Deep Analysis Net with Causal Embedding for Coal-fired power plant Fault Detection and Diagnosis (DANCE4CFDD). Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1844966.

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Chen, Qiu. The effectiveness of acupoint catgut embedding in hyperlipidemia with obesity：protocol for a systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review Protocols, 2020. http://dx.doi.org/10.37766/inplasy2020.4.0036.

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Yi, Xingqian, Li Wang, Qingying He, Rigun A, and Yimin Le. Acupoint catgut embedding for the treatment of peptic ulcers：A protocol for a systematic reviews and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2021. http://dx.doi.org/10.37766/inplasy2021.3.0097.

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