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Книги з теми "Learning with noisy labels"

Щоб переглянути інші типи публікацій з цієї теми, перейдіть за посиланням: Learning with noisy labels.

Автор: Grafiati

Опубліковано: 6 вересня 2023

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1

Ramsay, Carol A. Pesticides: Learning about labels. [Pullman]: Cooperative Extension, Washington State University, 1999.

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2

Zamzmi, Ghada, Sameer Antani, Ulas Bagci, Marius George Linguraru, Sivaramakrishnan Rajaraman, and Zhiyun Xue, eds. Medical Image Learning with Limited and Noisy Data. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-16760-7.

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3

Allan, John A. B. 1941-, ed. Kids with labels: Keys to intimacy. Toronto: Lugus Productions, 1990.

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4

Literacy, not labels: Celebrating students' strengths through whole language. Portsmouth, NH: Boynton/Cook Publishers, 1995.

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5

Wang, Qian, Fausto Milletari, Hien V. Nguyen, Shadi Albarqouni, M. Jorge Cardoso, Nicola Rieke, Ziyue Xu, et al., eds. Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33391-1.

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6

Carneiro, Gustavo. Machine Learning with Noisy Labels: Definitions, Theory, Techniques and Solutions. Elsevier Science & Technology Books, 2024.

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7

Herzog, Joyce. Learning in Spite of Labels. JoyceHerzog.com, Inc., 1994.

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8

Owen, Phillip. What-If... ?: Learning Without Labels. Independently Published, 2017.

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9

Publishing, Carson-Dellosa. Celebrate Learning Labels and Organizers. Carson-Dellosa Publishing, LLC, 2018.

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10

National Education Trust (Great Britain) Staff and Marc Rowland. Learning Without Labels: Improving Outcomes for Vulnerable Pupils. Catt Educational, Limited, John, 2017.

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11

Geiger, Constance J., and Patricia H. Harper. Learning the New Food Labels: An Educator's Slide Kit. Taplinger Publishing Company, 1994.

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12

Machine Learning Methods with Noisy, Incomplete or Small Datasets. MDPI, 2021. http://dx.doi.org/10.3390/books978-3-0365-1288-4.

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13

Mann, Jean. Literacy Labels: Book C : For Fun Things (An Essential Learning Product). Essential Learning Products Co, 1994.

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14

Fisher, Beth. Remorseless: Learning to Lose Labels, Expectations, and Assumptions--Without Losing Yourself. Brookstone Publishing Group, 2020.

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15

Literacy Labels: Book E : For Things We Wear (An Essential Learning Product). Essential Learning Products Co, 1994.

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16

Roehrs, Renae. Come Sit with Me: Learning to Hear God's Voice in a Noisy World. Independently Published, 2018.

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17

Spence, Rhian. Children Beyond Labels: Understanding Standardised Assessment and Managing Additional Learning Needs in Primary School. Taylor & Francis Group, 2018.

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18

Matheson, Ashley. Student Perceptions of Learning Disability Labels at the Junior High and High School Level. Cedarville University, 2009. http://dx.doi.org/10.15385/tmed.2009.6.

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19

Spence, Rhian. Children Beyond Labels: Understanding Standardised Assessment and Managing Additional Learning Needs in Primary School. Taylor & Francis Group, 2018.

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20

Spence, Rhian. Children Beyond Labels: Understanding Standardised Assessment and Managing Additional Learning Needs in Primary School. Taylor & Francis Group, 2018.

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21

Roehrs, Renae. Come Sit with Me - 3rd Edition: Learning to Hear God's Voice in a Noisy World. Independently Published, 2018.

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22

Zhou, Kevin, Qian Wang, M. Jorge Cardoso, Fausto Milletari, Hien V. Nguyen, Shadi Albarqouni, Nicola Rieke, et al. Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data: First MICCAI Workshop, DART 2019, and ... Springer, 2019.

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23

Teaching language concepts and labels to preschool children in special education and Head Start classes through physical education lessons. 1993.

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24

Bagci, Ulas, Sivaramakrishnan Rajaraman, Marius George Linguraru, Sameer Antani, and Ghada Zamzmi. Medical Image Learning with Limited and Noisy Data: First International Workshop, MILLanD 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Springer, 2022.

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25

Let's Sea Coloring Book. Easy and Fun: Sea Life, Sea Animals, Sea Related Pictures with Labels to Color. Learning English. for Sea Lovers, Children and Adults. Learning English Support. Spelling Practice. Relaxing Activity with Crayons or Paints. Independently Published, 2020.

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26

Bradley, Andrew, Gustavo Carneiro, Diana Mateus, Vasileios Belagiannis, and Jacinto C. Nascimento. Deep Learning and Data Labeling for Medical Applications: First International Workshop, Labels 2016, and Second International Workshop, Dlmia 2016, Held in Conjunction with Miccai 2016, Athens, Greece, October 21, 2016, Proceedings. Springer International Publishing AG, 2016.

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27

Peter, Loïc, Andrew Bradley, João Manuel R. S. Tavares, Gustavo Carneiro, and Diana Mateus. Deep Learning and Data Labeling for Medical Applications: First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings. Springer, 2016.

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28

Isgum, Ivana, Hien Van Nguyen, Nicholas Heller, Jaime Cardoso, and Pedro Henriques Abreu. Interpretable and Annotation-Efficient Learning for Medical Image Computing: Third International Workshop, IMIMIC 2020, Second International Workshop, MIL3ID 2020, and 5th International Workshop, LABELS 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4-8, 2020, Proceedings. Springer International Publishing AG, 2020.

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29

Amilevičius, Darius, Andrius Utka, Aistė Meidutė, and Jūratė Ruzaitė. DIGIRES COVID-19 ML Dataset v.1. Vytauto Didžiojo universitetas, 2023. http://dx.doi.org/10.7220/20.500.12259/252155.

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DIGIRES COVID-19 ML dataset v.1 is a tab-separated (.tsv) file prepared for training machine learning algorithms. The training dataset was compiled from various internet public Lithuanian media sources. It contains 351 records and has the following attributes: "Title": the title of a news article "Text": the text of the article "Label": a label that marks the article as 1: unreliable; 0: reliable 1) "unrealiable" marks articles, which were identified by professional fact checkers as fake news; 2) "reliable" marks trustworthy articles. Classes Labels Word tokens Reliable: 175 67902 Unreliable: 176 118747 Total 351 186649.

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30

Dewar, Jacqueline M. Analyzing Evidence. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198821212.003.0008.

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Chapter 7 focuses on two methods for analyzing qualitative data: rubrics and content analysis or coding. Rubrics facilitate the assessment of separate aspects of a complex task. A rubric with dimensions and performance levels that align well with the research question can be a valuable assessment tool in a scholarship of teaching and learning (SoTL) study. The chapter takes the reader through the process of creating a rubric, and then applying it, as well as a discussion of achieving inter-rater agreement. It also describes techniques for coding qualitative data (also called content analysis) to extract meaning by using codes or labels to identify common themes that appear throughout the data set. Multiple examples are provided of science, technology, engineering, and mathematics (STEM) studies that used or developed rubrics and of studies that did a content analysis of verbal and non-verbal data. It also describes and compares the standards used to assess quantitative research and qualitative research.

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31

Matijas-Mecca, Christian. Listen to Psychedelic Rock! Greenwood, 2020. http://dx.doi.org/10.5040/9798400679827.

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Listen to Psychedelic Rock! contains more than 50 entries covering the people, records, places, and events that shaped one of the most exciting and influential periods in popular music. This addition to the Exploring a Music Genre series concentrates solely on psychedelic rock music. Listen to Psychedelic Rock! Exploring a Musical Genre covers over fifty topics, arranged alphabetically, that are central to learning about psychedelic music and will enable readers to understand the breadth and ongoing influence of psychedelia through to the present day. The title contains biographical sketches on selected artists, “song-by-song” descriptions of many albums, and short, informative essays on participants who were influential in the original psychedelic movement. A background section introduces the genre and a legacy section shows how psychedelic music has cemented its place in the world, while another section shows the tremendous impact the music has had on popular culture. Information on record labels and year-of-release dates for all musical entries make it easy for any reader to navigate this title – a must-have for high school and college readers as well as for music scholars and fans of the genre.

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32

Barnhart, Michael A. Can You Beat Churchill? Cornell University Press, 2021. http://dx.doi.org/10.7591/cornell/9781501755644.001.0001.

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How do you get students to engage in a historical episode or era? How do you bring the immediacy and contingency of history to life? This book shares the secret to award-winning success in the classroom, which encourages role-playing for immersive teaching and learning. Combating the declining enrollment in humanities classes, this innovative approach reminds us how critical learning skills are transmitted to students: by reactivating their curiosity and problem-solving abilities. The book provides advice and procedures, both for the use of off-the-shelf commercial simulations and for the instructor who wishes to custom design a simulation from scratch. These reenactments allow students to step into the past, requiring them to think and act in ways historical figures might have. Students must make crucial or dramatic decisions, though these decisions need not align with the historical record. In doing so, they learn, through action and strategic consideration, the impact of real individuals and groups of people on the course of history. There is a quiet revolution underway in how history is taught to undergraduates. This book hopes to make it a noisy one.

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33

Carolini, Gabriella Y. Equity, Evaluation, and International Cooperation. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780192865489.001.0001.

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Abstract This book considers whether South–South Cooperation (SSC) is any different from other international partnerships in practice. This question often gets lost in conventional scholarship on SSC and international cooperation, which privileges macro-level narratives of how cooperation mechanisms fit within geopolitical concerns and shape the outcomes of foreign aid. This book instead offers an answer from the ground up. It highlights two main lessons from the close examination of the ecosystem of international cooperation projects in the urban water-and-sanitation sector in Maputo, Mozambique. First, the book shows that macro labels attributed to international cooperation reflect very little about how cooperation projects operate on the ground and the equity consequences of their work. Second, how projects are designed, implemented, and evaluated does matter to the quality of learning that emanates from partnerships. Beyond the geopolitical and technical proximities favored by the SSC discourse, this book argues that what matters in practice is whether hierarchy or heterarchy is institutionalized in the governance of cooperation projects; whether project partners are locally embedded in shared work spaces; and whether practitioners value flexibility and recognize the epistemic value of learning from all partners as peers. A strong evaluation culture within the international development industry, however, still subjugates such equity-based concerns and deep learning in projects to accountability, reinforcing orthodox power asymmetries in cooperation and sustaining epistemic and distributive injustice. This book instead provides a framework for how project evaluations, as a key narrative instrument of development, can instead promote distributive, procedural, and epistemic justice in international cooperation projects.

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34

Academe Master Baiter: An Academic Book. North Carolina, USA: Pattern Books, 2018.

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35

Academe Master Baiter: An Academic Book. Independently Published, 2020.

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