03333nam 2200589 c 450 991047992760332120200403115510.01-58367-501-9(CKB)3710000000222669(EBL)1767128(MiAaPQ)EBC1767128(EXLCZ)99371000000022266920091214h20092009 uy| 0engur|n|---|||||rdacontentrdamediardacarrierWhen media goes to war hegemonic discourse, public opinion, and the limits of dissent[electronic resource]by Anthony DiMaggio[electronic resource]New York, New York :Monthly Review Press,[2009]©2009384 siderDescription based upon print version of record.1-58367-200-1 Includes bibliographical references (pages [309]-318) and index.Introduction: propaganda and the news in a time of terror -- Withdrawal pains: Iraq and the politics of media deference -- There are no protestors here: media marginalizaition and the antiwar movement -- Worthy and unworthy victims of history: the politicization of genocide and human rights in U.S. foreign policy -- Journalistic norms and propaganda: Iraq and the war on terror -- Iran, nuclear weapons, and the politics of fear -- Media, globalization, and violence: views from around the world -- Public rationality, political elitism, and opposition to war -- Media effects on public opinion: propaganda, indoctrination, and mass resistance -- Propaganda, celebrity gossip, and the decline of news -- Postscript: media coverage in the age of Obama.In this fresh and provocative book, Anthony DiMaggio uses the war in Iraq and the United States confrontations with Iran as his touchstones to probe the sometimes fine line between news and propaganda. Using Antonio Gramsci''s concept of hegemony and drawing upon the seminal works of Noam Chomsky, Edward Herman, and Robert McChesney, DiMaggio combines a rigorousempirical analysis and clear, lucid prose to enlighten readers about issues essential to the struggle for a critical media and a functioning democracy.Mass media and warUnited StatesMass mediaObjectivityUnited StatesMass media and propagandaUnited StatesIraq War, 2003-2011Mass media and the warIraq War, 2003-2011PropagandaPublic opinionUnited StatesElectronic books.mediamedierkrigpropagandaoffentlighethegemoninyhetsdekningmediedekningkrigsjournalistikkobjektivitetkrigsreportasjeroffentlig debattoffentlig meningIrakIranUSAMass media and warMass mediaObjectivityMass media and propagandaIraq War, 2003-2011Mass media and the war.Iraq War, 2003-2011Propaganda.Public opinion320.014Dimaggio Anthony R1980-aut890752MiAaPQMiAaPQMiAaPQNO-TrBIBBOOK9910479927603321When media goes to war2036995UNINA03855nam 22007215 450 991103494320332120260119162711.03-031-99928-210.1007/978-3-031-99928-4(PPN)291741487(CKB)41665897500041(DE-He213)978-3-031-99928-4(MiAaPQ)EBC32372178(Au-PeEL)EBL32372178(EXLCZ)994166589750004120251017d2025 u| 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierAdvanced Supervised and Semi-supervised Learning Theory and Algorithms /by Massih-Reza Amini1st ed. 2025.Cham :Springer Nature Switzerland :Imprint: Springer,2025.1 online resource (XVIII, 309 p. 1 illus.)Cognitive Technologies,2197-66353-031-99927-4 1. Fundamentals of Supervised Learning -- 2. Data-dependent generalization bounds -- 3. Descent direction optimization algorithms -- 4. Deep Learning -- 5. Support Vector Machines -- 6. Boosting -- 7. Semi-supervised Learning -- 8. Learning-To-Rank -- Appendix: Probability reminders.Machine learning is one of the leading areas of artificial intelligence. It concerns the study and development of quantitative models that enable a computer to carry out operations without having been expressly programmed to do so. In this situation, learning is about identifying complex shapes and making intelligent decisions. The challenge in completing this task, given all the available inputs, is that the set of potential decisions is typically quite difficult to enumerate. Machine learning algorithms have been developed with the goal of learning about the problem to be handled based on a collection of limited data from this problem in order to get around this challenge. This textbook presents the scientific foundations of supervised learning theory, the most widespread algorithms developed according to this framework, as well as the semi-supervised and the learning-to-rank frameworks, at a level accessible to master's students. The aim of the book is to provide a coherent presentation linking the theory to the algorithms developed in this field. In addition, this study is not limited to the presentation of these foundations, but it also presents exercises, and is intended for readers who seek to understand the functioning of these models sometimes designated as black boxes.Cognitive Technologies,2197-6635Artificial intelligenceMachine learningInformation storage and retrieval systemsComputer visionPython (Computer program language)StatisticsArtificial IntelligenceMachine LearningInformation Storage and RetrievalComputer VisionPythonBayesian InferenceArtificial intelligence.Machine learning.Information storage and retrieval systems.Computer vision.Python (Computer program language)Statistics.Artificial Intelligence.Machine Learning.Information Storage and Retrieval.Computer Vision.Python.Bayesian Inference.006.3Amini Massih-Rezaauthttp://id.loc.gov/vocabulary/relators/aut1060956MiAaPQMiAaPQMiAaPQBOOK9911034943203321Advanced Supervised and Semi-supervised Learning4449169UNINA