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  1. Classical Statistics and Statistical Learning in Imaging Neuroscience.Danilo Bzdok - unknown
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  • Choosing prediction over explanation in psychology: lessons from machine learning.T. Yarkoni & J. Westfall - 2017 - Perspective on Psychological Science 12 (6):1100-1122.
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  • Pattern Recognition and Machine Learning.Christopher M. Bishop - 2006 - Springer: New York.
    This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would (...)
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  • Vision.David Marr - 1982 - W. H. Freeman.
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  • Some issues in the foundation of statistics.David Freedman - 1995 - Foundations of Science 1 (1):19-39.
    After sketching the conflict between objectivists and subjectivists on the foundations of statistics, this paper discusses an issue facing statisticians of both schools, namely, model validation. Statistical models originate in the study of games of chance, and have been successfully applied in the physical and life sciences. However, there are basic problems in applying the models to social phenomena; some of the difficulties will be pointed out. Hooke's law will be contrasted with regression models for salary discrimination, the latter being (...)
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  • (3 other versions)Logik der Forschung.Karl R. Popper (ed.) - 1935 - Wien: Springer.
    Karl Raimund Poppers (1902-1994) Hauptwerk, die Logik der Forschung (1934), gilt als Grundlagenwerk des kritischen Rationalismus. Der kritische Rationalismus zeigt, warum unser Wissen fehlbar ist und versteht den Erkenntnisfortschritt als Resultat von Hypothesenbildung und -widerlegung. Der Sammelband orientiert sich an der Gliederung der Logik der Forschung. Seine Beiträge kommentieren die jeweiligen Themen nach aktueller Forschungslage.
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  • The Elements of Statistical Learning.Trevor Hastie, Robert Tibshirani & Jerome Friedman - 2010 - Springer: New York.
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  • Logik der Forschung.Karl Popper - 1934 - Erkenntnis 5 (1):290-294.
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  • (1 other version)On the Mathematical Foundations of Theoretical Statistics.Ronald A. Fisher - 1922 - Philosophical Transactions of the Royal Society of London. Series A 222:309--368.
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  • Psychopathology and the Human Connectome: Toward a Transdiagnostic Model of Risk for Mental Illness.Joshua W. Buckholtz & A. Meyer-Lindenberg - 2012 - Neuron 74 (6):990-1004.
    The panoply of cognitive, affective, motivational, and social functions that underpin everyday human experience requires precisely choreographed patterns of interaction between networked brain regions. Perhaps not surprisingly, diverse forms of psychopathology are characterized by breakdowns in these interregional relationships. Here, we discuss how functional brain imaging has provided insights into the nature of brain dysconnectivity in mental illness. Synthesizing work to date, we propose that genetic and environmental risk factors impinge upon systems-level circuits for several core dimensions of cognition, producing (...)
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