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1.
  • Wilhelmsson, Kenneth, 1976 (författare)
  • Huvudansatser för parsningsmetoder. Om programutvecklingens förutsättningar i en svensk kontext
  • 2016
  • Rapport (övrigt vetenskapligt/konstnärligt)abstract
    • Syftet med denna text var att ge en inblick i området (syntaktisk) parsning. Tanken var att ge en bild av utvecklingen som var 1) fri från alltför tekniska detaljer, då området är programmeringstekniskt, och 2) beskriven ur ett svenskt perspektiv. Bakgrunden till valet av ämne till texten, som var tänkt att finnas med i antologin Text och kontext, var att parsning är relativt okänt för många personer verksamma inom närliggande områden, samtidigt som det är ett absolut nyckelbegrepp för den som ägnar sig åt datorlingvistik eller språkteknologi. Målet var alltså att ge en ganska allmän utifrånblick på några centrala sidor av utvecklingen, samtidigt som det tydligt är så att den som själv arbetat med utveckling kan ha starka åsikter och preferenser rörande metodval, något som i ärlighetens namn kanske inte heller denna text är lösgjord från. Hur ska det göras? Konsten att utveckla automatisk syntaxanalys av naturlig text kan läras ut från ett flertal perspektiv. Det kan t.ex. ske med fokus på användandet av en viss grammatikformalism, med fokus på beräkningssnabbhet, med fokus på entydiggörande av möjliga ambiguiteter. Tolkningsval kan göras med hjälp av antingen handskrivna regler eller inhämtad statistik. En sorts huvudtema i denna text är hur metoder för parsning på senare år uppvisar förändringar som kanske kan förklaras med att programmen har fått andra användningsområden och att metoderna har anpassats därefter (en annan tolkning är att flera senare system inte längre gör parsning i strikt mening). När detta tänkta ”kapitel” var färdigt fick det kommentaren att det inte var anpassat för antologins målgrupp. Det fick skrivas en annan kapiteltext, men det kom samtidigt ett förslag att publicera texten om parsning här som denna rapport.
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2.
  • Wilhelmsson, Kenneth, 1976 (författare)
  • Autentiska och artificiella frågor till svensk text Automatisk frågegenerering jämfört med användares frågor för informationsåtkomst : Authentic and artificial questions to Swedish text Automatically generated questions versus user-generated questions for information access
  • 2015
  • Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
    • Informationssökning mot ostrukturerade datakällor som fri text är ett av de områden där användargränssnitt med fri formulering i naturligt språk har tagits fram. I ett sådant, eventuellt AI-betonat, system kan några grundläggande svårigheter från användarperspektivet märkas. En sådan svårighet är att en användare inte känner till huruvida en fråga som hon avser att ställa egentligen kan besvaras av den aktuella texten. Denna svårighet, tillsammans med andra, som de kraftiga variationsmöjligheterna för formen för ett giltigt svar på en ställd fråga, riskerar att leda till att användarintrycken av systemtypen blir negativa. De moment som behöver ingå i ett sådant frågebaserat informationssystems funktionssätt måste på något sätt inbegripa en mappning av frågeled i frågan (t.ex. när) till den form och grammatisk funktion som svaret i texten måste ha (för frågan när normalt ett tidsadverbial). Bland annat denna iakttagelse inbjuder till användning av automatisk frågegenerering (question generation, QG). Frågegenerering innebär att frågor som en naturlig text besvarar initialt utvinns av ett program som samlar in dem i explicit form. Tanken för användning i informationssökning är att en användare i gränssnittet enbart ska kunna ställa just dessa frågor, vilka faktiskt besvaras av texten. Denna studie gäller just de frågor som ett automatiskt frågegenereringssystem för svenska kan, och genom vidare utveckling, skulle kunna generera för godtycklig digital svensk text. Även om mängden automatiskt genererade frågor och frågeformuleringar kan bli mycket stor, utrymmesmässigt många gånger större än ursprungstexten, så är det tydligt att den beskrivna metoden för frågegenerering för svenska inte kan och troligen inte heller kommer att kunna förmås att skapa alla de frågor och frågeformuleringar som en vanlig användare skulle anse att en viss text besvarar. Men hur väl fungerar då automatiskt genererade frågor i detta sammanhang? Denna uppsats kretsar kring en användarundersökning där undersökningsdeltagare har ombetts att formulera frågor som texter besvarar, och som anses vara relevanta frågor. Den resulterande samlingen frågor undersöktes och kategoriserades. Resultatet av undersökningens huvudfråga visar att bara 20-25 % av användarnas frågeformuleringar skulle kunna genereras direkt automatiskt med aktuell ansats – utan vissa informationstekniska förbättringar. Uppsatsen föreslår viss ny terminologi för detta outforskade område, bl.a. för att skilja mellan de olika grader av processkrav som generering av olika frågeslag från text kräver.
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3.
  • Chatterjee, Bapi, 1982 (författare)
  • Lock-free Concurrent Search
  • 2017
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • The contemporary computers typically consist of multiple computing cores with high compute power. Such computers make excellent concurrent asynchronous shared memory system. On the other hand, though many celebrated books on data structure and algorithm provide a comprehensive study of sequential search data structures, unfortunately, we do not have such a luxury if concurrency comes in the setting. The present dissertation aims to address this paucity. We describe novel lock-free algorithms for concurrent data structures that target a variety of search problems. (i) Point search (membership query, predecessor query, nearest neighbour query) for 1-dimensional data: Lock-free linked-list; lock-free internal and external binary search trees (BST). (ii) Range search for 1-dimensional data: A range search method for lock-free ordered set data structures - linked-list, skip-list and BST. (iii) Point search for multi-dimensional data: Lock-free kD-tree, specially, a generic method for nearest neighbour search. We prove that the presented algorithms are linearizable i.e. the concurrent data structure operations intuitively display their sequential behaviour to an observer of the concurrent system. The lock-freedom in the introduced algorithms guarantee overall progress in an asynchronous shared memory system. We present the amortized analysis of lock-free data structures to show their efficiency. Moreover, we provide sample implementations of the algorithms and test them over extensive micro-benchmarks. Our experiments demonstrate that the implementations are scalable and perform well when compared to related existing alternative implementations on common multi-core computers. Our focus is on propounding the generic methodologies for efficient lock-free concurrent search. In this direction, we present the notion of help-optimality, which captures the optimization of amortized step complexity of the operations. In addition to that, we explore the language-portable design of lock-free data structures that aims to simplify an implementation from programmer’s point of view. Finally, our techniques to implement lock-free linearizable range search and nearest neighbour search are independent of the underlying data structures and thus are adaptive to similar data structures.
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6.
  • Norlund, Tobias, 1991, et al. (författare)
  • Transferring Knowledge from Vision to Language: How to Achieve it and how to Measure it?
  • 2021
  • Ingår i: Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, pp. 149-162, Punta Cana, Dominican Republic. - : Association for Computational Linguistics.
  • Konferensbidrag (refereegranskat)abstract
    • Large language models are known to suffer from the hallucination problem in that they are prone to output statements that are false or inconsistent, indicating a lack of knowledge. A proposed solution to this is to provide the model with additional data modalities that complements the knowledge obtained through text. We investigate the use of visual data to complement the knowledge of large language models by proposing a method for evaluating visual knowledge transfer to text for uni- or multimodal language models. The method is based on two steps, 1) a novel task querying for knowledge of memory colors, i.e. typical colors of well-known objects, and 2) filtering of model training data to clearly separate knowledge contributions. Additionally, we introduce a model architecture that involves a visual imagination step and evaluate it with our proposed method. We find that our method can successfully be used to measure visual knowledge transfer capabilities in models and that our novel model architecture shows promising results for leveraging multimodal knowledge in a unimodal setting.
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7.
  • Scheuner, Joel, 1991, et al. (författare)
  • Performance Benchmarking of Infrastructure-as-a-Service (IaaS) Clouds with CloudWorkBench
  • 2019
  • Ingår i: ICPE 2019 - Companion of the 2019 ACM/SPEC International Conference on Performance Engineering. - New York, NY, USA : ACM. ; , s. 53-56
  • Konferensbidrag (refereegranskat)abstract
    • The continuing growth of the cloud computing market has led to an unprecedented diversity of cloud services with different performance characteristics. To support service selection, researchers and practitioners conduct cloud performance benchmarking by measuring and objectively comparing the performance of different providers and configurations (e.g., instance types in different data center regions). In this tutorial, we demonstrate how to write performance tests for IaaS clouds using the Web-based benchmarking tool Cloud WorkBench (CWB). We will motivate and introduce benchmarking of IaaS cloud in general, demonstrate the execution of a simple benchmark in a public cloud environment, summarize the CWB tool architecture, and interactively develop and deploy a more advanced benchmark together with the participants.
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9.
  • Sweidan, Dirar, et al. (författare)
  • Predicting Customer Churn in Retailing
  • 2022
  • Ingår i: Proceedings 21st IEEE International Conference on Machine Learning and Applications ICMLA 2022. - : IEEE. - 9781665462839 - 9781665462846 ; , s. 635-640
  • Konferensbidrag (refereegranskat)abstract
    • Customer churn is one of the most challenging problems for digital retailers. With significantly higher costs for acquiring new customers than retaining existing ones, knowledge about which customers are likely to churn becomes essential. This paper reports a case study where a data-driven approach to churn prediction is used for predicting churners and gaining insights about the problem domain. The real-world data set used contains approximately 200 000 customers, describing each customer using more than 50 features. In the pre-processing, exploration, modeling and analysis, attributes related to recency, frequency, and monetary concepts are identified and utilized. In addition, correlations and feature importance are used to discover and understand churn indicators. One important finding is that the churn rate highly depends on the number of previous purchases. In the segment consisting of customers with only one previous purchase, more than 75% will churn, i.e., not make another purchase in the coming year. For customers with at least four previous purchases, the corresponding churn rate is around 25%. Further analysis shows that churning customers in general, and as expected, make smaller purchases and visit the online store less often. In the experimentation, three modeling techniques are evaluated, and the results show that, in particular, Gradient Boosting models can predict churners with relatively high accuracy while obtaining a good balance between precision and recall. 
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11.
  • Al Sabbagh, Khaled, 1987, et al. (författare)
  • Improving Data Quality for Regression Test Selection by Reducing Annotation Noise
  • 2020
  • Ingår i: Proceedings - 46th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2020. ; , s. 191-194
  • Konferensbidrag (refereegranskat)abstract
    • Big data and machine learning models have been increasingly used to support software engineering processes and practices. One example is the use of machine learning models to improve test case selection in continuous integration. However, one of the challenges in building such models is the identification and reduction of noise that often comes in large data. In this paper, we present a noise reduction approach that deals with the problem of contradictory training entries. We empirically evaluate the effectiveness of the approach in the context of selective regression testing. For this purpose, we use a curated training set as input to a tree-based machine learning ensemble and compare the classification precision, recall, and f-score against a non-curated set. Our study shows that using the noise reduction approach on the training instances gives better results in prediction with an improvement of 37% on precision, 70% on recall, and 59% on f-score.
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12.
  • Somanath, Sanjay, 1994, et al. (författare)
  • Towards Urban Digital Twins: A Workflow for Procedural Visualization Using Geospatial Data
  • 2024
  • Ingår i: Remote Sensing. - 2072-4292. ; 16:11
  • Tidskriftsartikel (refereegranskat)abstract
    • A key feature for urban digital twins (DTs) is an automatically generated detailed 3D representation of the built and unbuilt environment from aerial imagery, footprints, LiDAR, or a fusion of these. Such 3D models have applications in architecture, civil engineering, urban planning, construction, real estate, Geographical Information Systems (GIS), and many other areas. While the visualization of large-scale data in conjunction with the generated 3D models is often a recurring and resource-intensive task, an automated workflow is complex, requiring many steps to achieve a high-quality visualization. Methods for building reconstruction approaches have come a long way, from previously manual approaches to semi-automatic or automatic approaches. This paper aims to complement existing methods of 3D building generation. First, we present a literature review covering different options for procedural context generation and visualization methods, focusing on workflows and data pipelines. Next, we present a semi-automated workflow that extends the building reconstruction pipeline to include procedural context generation using Python and Unreal Engine. Finally, we propose a workflow for integrating various types of large-scale urban analysis data for visualization. We conclude with a series of challenges faced in achieving such pipelines and the limitations of the current approach. However, the steps for a complete, end-to-end solution involve further developing robust systems for building detection, rooftop recognition, and geometry generation and importing and visualizing data in the same 3D environment, highlighting a need for further research and development in this field.
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13.
  • Bergström, Gustav, et al. (författare)
  • Evaluating the layout quality of UML class diagrams using machine learning
  • 2022
  • Ingår i: Journal of Systems and Software. - : Elsevier BV. - 0164-1212. ; 192
  • Tidskriftsartikel (refereegranskat)abstract
    • UML is the de facto standard notation for graphically representing software. UML diagrams are used in the analysis, construction, and maintenance of software systems. Mostly, UML diagrams capture an abstract view of a (piece of a) software system. A key purpose of UML diagrams is to share knowledge about the system among developers. The quality of the layout of UML diagrams plays a crucial role in their comprehension. In this paper, we present an automated method for evaluating the layout quality of UML class diagrams. We use machine learning based on features extracted from the class diagram images using image processing. Such an automated evaluator has several uses: (1) From an industrial perspective, this tool could be used for automated quality assurance for class diagrams (e.g., as part of a quality monitor integrated into a DevOps toolchain). For example, automated feedback can be generated once a UML diagram is checked in the project repository. (2) In an educational setting, the evaluator can grade the layout aspect of student assignments in courses on software modeling, analysis, and design. (3) In the field of algorithm design for graph layouts, our evaluator can assess the layouts generated by such algorithms. In this way, this evaluator opens up the road for using machine learning to learn good layouting algorithms. Approach.: We use machine learning techniques to build (linear) regression models based on features extracted from the class diagram images using image processing. As ground truth, we use a dataset of 600+ UML Class Diagrams for which experts manually label the quality of the layout. Contributions.: This paper makes the following contributions: (1) We show the feasibility of the automatic evaluation of the layout quality of UML class diagrams. (2) We analyze which features of UML class diagrams are most strongly related to the quality of their layout. (3) We evaluate the performance of our layout evaluator. (4) We offer a dataset of labeled UML class diagrams. In this dataset, we supply for every diagram the following information: (a) a manually established ground truth of the quality of the layout, (b) an automatically established value for the layout-quality of the diagram (produced by our classifier), and (c) the values of key features of the layout of the diagram (obtained by image processing). This dataset can be used for replication of our study and others to build on and improve on this work. Editor's note: Open Science material was validated by the Journal of Systems and Software Open Science Board.
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14.
  • Brunetta, Carlo, 1992 (författare)
  • Cryptographic Tools for Privacy Preservation
  • 2021
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Data permeates every aspect of our daily life and it is the backbone of our digitalized society. Smartphones, smartwatches and many more smart devices measure, collect, modify and share data in what is known as the Internet of Things. Often, these devices don’t have enough computation power/storage space thus out-sourcing some aspects of the data management to the Cloud. Outsourcing computation/storage to a third party poses natural questions regarding the security and privacy of the shared sensitive data. Intuitively, Cryptography is a toolset of primitives/protocols of which security prop- erties are formally proven while Privacy typically captures additional social/legislative requirements that relate more to the concept of “trust” between people, “how” data is used and/or “who” has access to data. This thesis separates the concepts by introducing an abstract model that classifies data leaks into different types of breaches. Each class represents a specific requirement/goal related to cryptography, e.g. confidentiality or integrity, or related to privacy, e.g. liability, sensitive data management and more. The thesis contains cryptographic tools designed to provide privacy guarantees for different application scenarios. In more details, the thesis: (a) defines new encryption schemes that provide formal privacy guarantees such as theoretical privacy definitions like Differential Privacy (DP), or concrete privacy-oriented applications covered by existing regulations such as the European General Data Protection Regulation (GDPR); (b) proposes new tools and procedures for providing verifiable computation’s guarantees in concrete scenarios for post-quantum cryptography or generalisation of signature schemes; (c) proposes a methodology for utilising Machine Learning (ML) for analysing the effective security and privacy of a crypto-tool and, dually, proposes a secure primitive that allows computing specific ML algorithm in a privacy-preserving way; (d) provides an alternative protocol for secure communication between two parties, based on the idea of communicating in a periodically timed fashion.
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15.
  • Dodig-Crnkovic, Gordana, 1955 (författare)
  • Cognitive Architectures Based on Natural Info-Computation
  • 2022
  • Ingår i: Studies in Applied Philosophy, Epistemology and Rational Ethics. - Cham : Springer. - 2192-6255 .- 2192-6263. ; , s. 3-13, s. 3-13
  • Bokkapitel (refereegranskat)abstract
    • At the time when the first models of cognitive architectures have been proposed, some forty years ago, understanding of cognition, embodiment and evolution was substantially different from today’s. So was the state of the art of information physics, information chemistry, bioinformatics, neuroinformatics, computational neuroscience, complexity theory, self-organization, theory of evolution, as well as the basic concepts of information and computation. Novel developments support a constructive interdisciplinary framework for cognitive architectures based on natural morphological computing, where interactions between constituents at different levels of organization of matter-energy and their corresponding time-dependent dynamics, lead to complexification of agency and increased cognitive capacities of living organisms that unfold through evolution. Proposed info-computational framework for naturalizing cognition considers present updates (generalizations) of the concepts of information, computation, cognition, and evolution in order to attain an alignment with the current state of the art in corresponding research fields. Some important open questions are suggested for future research with implications for further development of cognitive and intelligent technologies.
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16.
  • Ferro, Nicola, et al. (författare)
  • PROMISE Retreat Report Prospects and Opportunities for Information Access Evaluation
  • 2013
  • Ingår i: ACM SIGIR Forum. - : Association for Computing Machinery (ACM). - 0163-5840 .- 1558-0229. ; 46:2, s. 60-84
  • Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
    • The PROMISE network of excellence organized a two-days brainstorming workshop on 30th and 31st May 2012 in Padua, Italy, to discuss and envisage future directions and perspectives for the evaluation of information access and retrieval systems in multiple languages and multiple media. This document reports on the outcomes of this event and provides details about the six envisaged research lines: search applications; contextual evaluation; challenges in test collection design and exploitation; component-based evaluation; ongoing evaluation; and signal-aware evaluation. The ultimate goal of the PROMISE retreat is to stimulate and involve the research community along these research lines and to provide funding agencies with effective and scientifically sound ideas for coordinating and supporting information access research.
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17.
  • Fröberg, Rikard, 1971, et al. (författare)
  • Introduction to Databases
  • 2018
  • Bok (övrigt vetenskapligt/konstnärligt)abstract
    • Kurlitteratur för bland annat 7,5 hp databaser (delkurs i TIG058 programmeringsteknik och databaser). Kurlitteraturen (läromedlet) består av texter, exempel, övningar, föreläsningspresentationer, videoföreläsningar: Antal slidesidor193 Tid per slidesida i snitt (sv):0:00:56 Antal slides:15 Total tid eng. video:1:24:44 Total tid sv. video:2:46:39 Totalt antal övningar/frågor85 Totalt antal A4-sidor med övningar69 Totalt antal A4-sidor med text och exempel73 Totalt antal A4-sidor med text och övningar142 Materialet underhålls och utvecklas kontinuerligt. Senaste upplaga är från 2018.
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18.
  • Rafiq, Y., et al. (författare)
  • Learning to Share: Engineering Adaptive Decision-Support for Online Social Networks
  • 2017
  • Ingår i: PROCEEDINGS OF THE 2017 32ND IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING (ASE'17). - 1527-1366. - 9781538626849 ; , s. 280-285
  • Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
    • Some online social networks (OSNs) allow users to define friendship-groups as reusable shortcuts for sharing information with multiple contacts. Posting exclusively to a friendship-group gives some privacy control, while supporting communication with (and within) this group. However, recipients of such posts may want to reuse content for their own social advantage, and can bypass existing controls by copy-pasting into a new post; this cross-posting poses privacy risks. This paper presents a learning to share approach that enables the incorporation of more nuanced privacy controls into OSNs. Specifically, we propose a reusable, adaptive software architecture that uses rigorous runtime analysis to help OSN users to make informed decisions about suitable audiences for their posts. This is achieved by supporting dynamic formation of recipient-groups that benefit social interactions while reducing privacy risks. We exemplify the use of our approach in the context of Facebook.
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19.
  • Tsaloli, Georgia, 1993 (författare)
  • Secure and Privacy-Preserving Cloud-Assisted Computing
  • 2022
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Smart devices such as smartphones, wearables, and smart appliances collect significant amounts of data and transmit them over the network forming the Internet of Things (IoT). Many applications in our daily lives (e.g., health, smart grid, traffic monitoring) involve IoT devices that often have low computational capabilities. Subsequently, powerful cloud servers are employed to process the data collected from these devices. Nevertheless, security and privacy concerns arise in cloud-assisted computing settings. Collected data can be sensitive, and it is essential to protect their confidentiality. Additionally, outsourcing computations to untrusted cloud servers creates the need to ensure that servers perform the computations as requested and that any misbehavior can be detected, safeguarding security. Cryptographic primitives and protocols are the foundation to design secure and privacy-preserving solutions that address these challenges. This thesis focuses on providing privacy and security guarantees when outsourcing heavy computations on sensitive data to untrusted cloud servers. More concretely, this work: (a)  provides solutions for outsourcing the secure computation of the sum and the product functions in the multi-server, multi-client setting, protecting the sensitive data of the data owners, even against potentially untrusted cloud servers; (b)  provides integrity guarantees for the proposed protocols, by enabling anyone to verify the correctness of the computed function values. More precisely, the employed servers or the clients (depending on the proposed solution) provide specific values which are the proofs that the computed results are correct; (c)  designs decentralized settings, where multiple cloud servers are employed to perform the requested computations as opposed to relying on a single server that might fail or lose connection; (d)  suggests ways to protect individual privacy and provide integrity. More pre- cisely, we propose a verifiable differentially private solution that provides verifiability and avoids any leakage of information regardless of the participa- tion of some individual’s sensitive data in the computation or not.
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20.
  • Fu, Keren, et al. (författare)
  • Deepside: A general deep framework for salient object detection
  • 2019
  • Ingår i: Neurocomputing. - : Elsevier BV. - 0925-2312 .- 1872-8286. ; 356, s. 69-82
  • Tidskriftsartikel (refereegranskat)abstract
    • Deep learning-based salient object detection techniques have shown impressive results compared to con- ventional saliency detection by handcrafted features. Integrating hierarchical features of Convolutional Neural Networks (CNN) to achieve fine-grained saliency detection is a current trend, and various deep architectures are proposed by researchers, including “skip-layer” architecture, “top-down” architecture, “short-connection” architecture and so on. While these architectures have achieved progressive improve- ment on detection accuracy, it is still unclear about the underlying distinctions and connections between these schemes. In this paper, we review and draw underlying connections between these architectures, and show that they actually could be unified into a general framework, which simply just has side struc- tures with different depths. Based on the idea of designing deeper side structures for better detection accuracy, we propose a unified framework called Deepside that can be deeply supervised to incorporate hierarchical CNN features. Additionally, to fuse multiple side outputs from the network, we propose a novel fusion technique based on segmentation-based pooling, which severs as a built-in component in the CNN architecture and guarantees more accurate boundary details of detected salient objects. The effectiveness of the proposed Deepside scheme against state-of-the-art models is validated on 8 benchmark datasets.
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21.
  • Gerken, Jan, 1991, et al. (författare)
  • Equivariance versus augmentation for spherical images
  • 2022
  • Ingår i: Proceedings of Machine Learning Resaerch. ; , s. 7404-7421
  • Konferensbidrag (refereegranskat)abstract
    • We analyze the role of rotational equivariance in convolutional neural networks (CNNs) applied to spherical images. We compare the performance of the group equivariant networks known as S2CNNs and standard non-equivariant CNNs trained with an increasing amount of data augmentation. The chosen architectures can be considered baseline references for the respective design paradigms. Our models are trained and evaluated on single or multiple items from the MNIST- or FashionMNIST dataset projected onto the sphere. For the task of image classification, which is inherently rotationally invariant, we find that by considerably increasing the amount of data augmentation and the size of the networks, it is possible for the standard CNNs to reach at least the same performance as the equivariant network. In contrast, for the inherently equivariant task of semantic segmentation, the non-equivariant networks are consistently outperformed by the equivariant networks with significantly fewer parameters. We also analyze and compare the inference latency and training times of the different networks, enabling detailed tradeoff considerations between equivariant architectures and data augmentation for practical problems.
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22.
  • Isaksson, Martin, et al. (författare)
  • Adaptive Expert Models for Federated Learning
  • 2023
  • Ingår i: <em>Lecture Notes in Computer Science </em>Volume 13448 Pages 1 - 16 2023. - Cham : Springer Science and Business Media Deutschland GmbH. - 9783031289958 ; 13448 LNAI, s. 1-16
  • Konferensbidrag (refereegranskat)abstract
    • Federated Learning (FL) is a promising framework for distributed learning when data is private and sensitive. However, the state-of-the-art solutions in this framework are not optimal when data is heterogeneous and non-IID. We propose a practical and robust approach to personalization in FL that adjusts to heterogeneous and non-IID data by balancing exploration and exploitation of several global models. To achieve our aim of personalization, we use a Mixture of Experts (MoE) that learns to group clients that are similar to each other, while using the global models more efficiently. We show that our approach achieves an accuracy up to 29.78% better than the state-of-the-art and up to 4.38% better compared to a local model in a pathological non-IID setting, even though we tune our approach in the IID setting. © 2023, The Author(s)
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23.
  • Petersson, Jesper, 1974, et al. (författare)
  • Off the record: The invisibility work of doctors in a patient-accessible electronic health record information service.
  • 2021
  • Ingår i: Sociology of health & illness. - : Wiley. - 1467-9566 .- 0141-9889. ; 43:5, s. 1270-1285
  • Tidskriftsartikel (refereegranskat)abstract
    • In this article, we draw on Michael Lipsky's work on street-level bureaucrats and discretion to analyse a real case setting comprising an interview study of 30 Swedish doctors regarding their experiences of changes in clinical work following patients being given access to medical records information online. We introduce the notion of invisibility work to capture how doctors exercise discretion to preserve the invisibility of their work, in contrast to the well-established notion of invisible work, which denotes work made invisible by parties other than those performing it. We discuss three main forms of invisibility work in relation to records: omitting information, cryptic writing and parallel note writing. We argue that invisibility work is a way for doctors to resolve professional tensions arising from the political decision to provide patients with online access to record information. Although invisibility work is understood by doctors as a solution to government-initiated visibility, we highlight how it can create difficulties for doctors concerning accountability towards patients, peers and authorities.
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24.
  • Rexhepi, Hanife, 1984-, et al. (författare)
  • Cancer patients’ information seeking behavior related to online electronic healthcare records
  • 2021
  • Ingår i: Health Informatics Journal. - : Sage Publications. - 1460-4582 .- 1741-2811. ; 27:3, s. 1-12
  • Tidskriftsartikel (refereegranskat)abstract
    • Patients’ online access to their EHR together with the rapid proliferation of medical information on the Internet has changed how patients use information to learn about their health. Patients’ tendency to turn to the Internet to find information about their health and care is well-documented. However, little is known about patients’ information seeking behavior when using online EHRs. By using information horizons as an analytical tool this paper aims to investigate the information behavior of cancer patients who have chosen to view their EHRs (readers) and to those who have not made that option (non-readers). Thirty interviews were conducted with patients. Based on information horizons, it seems that non-reading is associated with living in a narrower information world in comparison to readers. The findings do not suggest that the smallness would be a result of active avoidance of information, or that it would be counterproductive for the patients. The findings suggest, however, that EHRs would benefit from comprehensive linking to authoritative health information sources to help users to understand their contents. In parallel, healthcare professionals should be more aware of their personal role as a key source of health information to those who choose not to read their EHRs. 
  •  
25.
  • Falkman, Göran, 1968-, et al. (författare)
  • SOMWeb - Towards an Infrastructure for Knowledge Sharing in Oral Medicine
  • 2005
  • Ingår i: Connecting Medical Informatics and Bio-Informatics: Proceedings of MIE2005 - The XIXth International Congress of the European Federation for Medical Informatics. - Amsterdam : IOS Press. - 1586035495 ; 116, s. 527-32, s. 527-532
  • Konferensbidrag (refereegranskat)abstract
    • In a net-based society, clinicians can come together for cooperative work and distance learning around a common medical material. This requires suitable techniques for cooperative knowledge management and user interfaces that are adapted to both the group as a whole and to individuals. To support distributed management and sharing of clinical knowledge, we propose the development of an intelligent web community for clinicians within oral medicine. This virtual meeting place will support the ongoing work on developing a digital knowledge base, providing a foundation for a more evidence-based oral medicine. The presented system is founded on the use and development of web services and standards for knowledge modelling and knowledge-based systems. The work is conducted within the frame of a well-established cooperation between oral medicine and computer science.
  •  
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