Items where Subject is "General Issues > Formal Learning Theory"
Group by: Creators | Item Type Number of items at this level: 52. AAaronson, Scott (2011) Why Philosophers Should Care About Computational Complexity. [Preprint] BBaccelli, Jean and Stewart, Rush T. (2020) Support for Geometric Pooling. The Review of Symbolic Logic. Balduzzi, David (2011) Information, learning and falsification. Advances in Neural Information Processing Systems (NIPS). Barrett, Jeffrey A. (2015) On the Evolution of Truth. [Preprint] Barrett, Jeffrey A. and Dickson, Michael and Purves, Gordon (2013) Prediction Games. [Preprint] Barrett, Jeffrey A. and Gabriel, Nathan (2021) Reinforcement with Iterative Punishment. [Preprint] Barrett, Jeffrey A. and Skyrms, Brian and Cochran, Calvin (2018) Hierarchical Models for the Evolution of Compositional Language. [Preprint] Belot, Gordon (2013) Bayesian Orgulity. [Preprint] Belot, Gordon (2013) Failure of Calibration is Typical. [Preprint] Belot, Gordon (2015) Objectivity and Bias. [Preprint] Benétreau-Dupin, Yann (2014) The Bayesian Who Knew Too Much. Synthese. ISSN 1573-0964 CCarroll, La Shun L. (2017) Theoretical Biomimetics: A biological design-driven concept for creative problem-solving as applied to the optimal sequencing of active learning techniques in educational theory. Multidisciplinary Journal for Education, Social and Technological Sciences, 4 (2). p. 80. ISSN 2341-2593 Climenhaga, Nevin (2019) The Structure of Epistemic Probabilities. Philosophical Studies. pp. 1-30. ISSN 0031-8116 Climenhaga, Nevin and DesAutels, Lane and Ramsey, Grant (2019) Causal Inference from Noise. [Preprint] Colombo, Matteo and Klein, Dominik (2017) Mystery and the evidential impact of unexplainables. [Preprint] Culka, M. (2018) A Probabilistic Modelling Approach for Rational Belief in Meta-Epistemic Contexts. [Preprint] DDavis, Isaac (2019) A Framework for Pragmatic Reliability. [Preprint] Dawidowicz, Edward and Jackson, Vairzora and Bryant, Thomas E and Adams, Martin (2003) The Right Information… and Intelligent Nodes. In: UNSPECIFIED. De Pretis, Francesco and Landes, Juergen and Peden, William and Osimani, Barbara (2021) Pharmacovigilance as Personalized Medicine. In: Chiara Beneduce and Marta Bertolaso (eds.) Personalized Medicine: A Multidisciplinary Approach to Complexity, Springer Nature. [Preprint] Dietrich, Franz and List, Christian and Bradley, Richard (2016) Belief revision generalized: A joint characterization of Bayes' and Jeffrey's rules. Journal of Economic Theory, 162. pp. 352-371. Dowe, David and Gardner, Steve and Oppy, Graham (2006) "Bayes Not Bust! Why Simplicity is no problem for Bayesians". [Preprint] EEberhardt, Frederick (2012) Experimental Indistinguishability of Causal Structures. In: UNSPECIFIED. Ellerman, David (2013) An Introduction to Logical Entropy and its Relation to Shannon Entropy. [Preprint] FFriederich, Simon (2016) Choosing Beauty. [Preprint] GGyenis, Balazs (2014) Bayes rules all: On the equivalence of various forms of learning in a probabilistic setting. [Preprint] Gyenis, Zalán (2018) On the modal logic of Jeffrey conditionalization. [Preprint] Gyenis, Zalán and Rédei, Miklós and Brown, William (2018) The modal logic of Bayesian belief revision. [Preprint] HHancox-Li, Leif (2020) Robustness in Machine Learning Explanations: Does It Matter? [Preprint] Huber, Franz (2008) Assessing Theories, Bayes Style. Synthese, 161 (1). pp. 89-118. Huber, Franz (2007) The Plausibility-Informativeness Theory. New Waves in Epistemology. pp. 164-191. Huber, Franz (2014) What Should I Believe About What Would Have Been the Case? Journal of Philosophicl Logic. Huber, Franz (2017) On the Justification of Deduction and Induction. [Preprint] KKawalec, Pawel (2005) Understanding science of the new millennium. UNSPECIFIED. (Unpublished) LLin, Hanti A General Theory of (Identification in the) Limit and Convergence (to the Truth). UNSPECIFIED. OOsimani, Barbara and Landes, Juergen (2021) Varieties of Error and Varieties of Evidence in Scientific Inference, Forthcoming in The British Journal for Philosophy of Science. [Preprint] Osimani, Barbara and Marta, Bertolaso and Roland, Poellinger and Emanuele, Frontoni (2019) Real and Virtual Clinical Trials: a Formal Analysis. [Preprint] Osimani, Barbara and Poellinger, Roland (2020) Osimani B., Poellinger R. (2020) A Protocol for Model Validation and Causal Inference from Computer Simulation. In: Bertolaso M., Sterpetti F. (eds) A Critical Reflection on Automated Science. Human Perspectives in Health Sciences and Technology, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-030-25001-0_9. [Preprint] PPietsch, Wolfgang (2016) A difference-making account of causation. In: UNSPECIFIED. RRochefort-Maranda, Guillaume (2016) Simplicity and model selection. European Journal for Philosophy of Science. ISSN 1879-4912 Rédei, Miklós and Gyenis, Zalán (2015) General properties of general Bayesian learning. [Preprint] SSant'Anna, Adonai and Bueno, Otavio and da Costa, Newton (2014) A Set-Theoretic Predicate for Semantics in Natural and Formal Languages. [Preprint] Schupbach, Jonah N. (2008) Is the Conjunction Fallacy tied to Probabilistic Confirmation? UNSPECIFIED. Schurz, Gerhard (2016) No Free Lunch Theorem, Inductive Skepticism, and the Optimality of Meta-Induction. In: UNSPECIFIED. Skyrms, Brian and Barrett, Jeffrey A. (2018) PROPOSITIONAL CONTENT in SIGNALS. [Preprint] Soler-Toscano, Fernando (2014) El giro dinámico en la epistemología formal: el caso del razonamiento explicativo. THEORIA. An International Journal for Theory, History and Foundations of Science, 29 (2). pp. 181-199. ISSN 2171-679X Sterrett, S. G. (2012) Bringing Up Turing's 'Child-Machine' (revised). [Preprint] VVictor, Kuligin and Galina, Kuligina and Maria, Korneva (2001) The Scientific Philosophy and Philosophy of Science (Part 1). [Preprint] Victor, Kuligin and Galina, Kuligina and Maria, Korneva (2001) The Scientific Philosophy and Philosophy of Science (Part 3). [Preprint] Victor, Kuligin and Galina, Kuligina and Maria, Korneva (2001) The Scientific Philosophy and Philosophy of Science. [Preprint] WWheeler, Gregory (2016) Machine Epistemology and Big Data. [Preprint] ZZhao, Kino (2018) A statistical learning approach to a problem of induction. In: UNSPECIFIED. Zhao, Kino (2018) A statistical learning approach to a problem of induction. In: UNSPECIFIED. |