Causal Inference by Direction of Information Jilles Vreeken◦ Abstract We focus on data-driven causal inference. In particular, we propose a new principle for causal inference based on algorithmic information theory, i.

Source URL: eda.mmci.uni-saarland.de

Grammatical Inference and Machine Learning Approaches to Post-Hoc LangSec Sheridan S. Curley Dr. Richard E. Harang

Source URL: spw16.langsec.org

• Formal languages
• Cognitive science
• Academia
• Cognition
• Language identification in the limit
• Grammar induction
• Recurrent neural network
• Algorithmic learning theory
• Context-free grammar
• Regular language
• Context-free language
• Formal grammar

Part 2: First-Order Logic 2.1 Syntax 2.2 Semantics 2.3 Models, Validity, Satisfiability 2.4 Algorithmic problems 2.5 Normal forms and Skolemization

Source URL: people.mpi-inf.mpg.de

• Logic
• Mathematical logic
• Mathematics
• Automated theorem proving
• Propositional calculus
• Rules of inference
• Resolution
• Boolean algebra
• Literal
• First-order logic
• SLD resolution
• Horn clause

CS168: The Modern Algorithmic Toolbox Lecture #14: Markov Chain Monte Carlo Tim Roughgarden & Gregory Valiant∗ May 11, 2016 The previous lecture covered several tools for inferring properties of the distribution that u

Source URL: theory.stanford.edu

• Markov models
• Markov processes
• Stochastic processes
• Monte Carlo methods
• Statistical mechanics
• Markov chain
• Stochastic matrix
• Markov property
• Random walk
• Continuous-time Markov chain
• Bayesian inference in phylogeny

Rational Randomness: The role of sampling in an algorithmic account of preschooler’s causal learning Bonawitz, E., Gopnik, A., Denison, S., Griffiths, T. L. University of California, Berkeley; Berkeley, CA 94720

Source URL: ccdlab.rutgers.edu

• Statistics
• Philosophy
• Logic
• Statistical inference
• Philosophy of science
• Statistical theory
• Reasoning
• Bayesian inference
• Statistical forecasting
• Bayesian network
• Bayesian statistics
• Inductive reasoning

Algorithmic Inference approach to learn copulas Simone Bassis Department of Computer Science University of Milano via Comelico 30/41, 20135, Milano, Italy

Source URL: www.probabilistic-numerics.org

Statistical, algorithmic, and robustness aspects of population demographic inference from genomic variation data by Anand Bhaskar A dissertation submitted in partial satisfaction of the

Source URL: anandbhaskar.me

MDL Method: an Inductive Inference Method for Reconstructing Phylogenetic Trees Fengrong Ren

Source URL: www.jsbi.org

• Computational phylogenetics
• Phylogenetics
• Algorithmic information theory
• Minimum description length
• Statistical theory
• Phylogenetic tree
• Maximum parsimony
• PHYLIP
• MDL
• Maximum likelihood estimation

1 Learning, Regularity, and Compression Overview The task of inductive inference is to find laws or regularities underlying some given set of data. These laws are then used to gain insight

Source URL: homepages.cwi.nl

• Information theory
• Randomness
• Minimum description length
• Artificial intelligence
• Kolmogorov complexity
• Ray Solomonoff
• Random sequence
• Per Martin-Löf
• Inductive inference
• Algorithmic information theory
• Theoretical computer science
• Mathematics

doi:j.tcs

Source URL: www-alg.ist.hokudai.ac.jp

• Theoretical computer science
• Mathematics
• Learning theory
• Inductive inference
• Algorithmic learning theory
• Nicolò Cesa-Bianchi
• Algorithm
• Learnability
• Probably approximately correct learning
• Computational learning theory
• Machine learning
• Applied mathematics