List of Accepted Papers

  • Nir Fresco. A Critical Survey of Some Competing Accounts of Concrete Digital Computation
  • Bing Hu, Thanawin Rakthanmanon, Yuan Hao, Scott Evans, Stefano Lonardi and Eamonn Keogh. Towards Discovering the Intrinsic Cardinality and Dimensionality of Time Series using MDL
  • Peter Sunehag and Marcus Hutter. Principles of Solomonoff Induction and AIXI
  • Allen King. Design of a Conscious Machine
  • Josh Hall. Further Reflections on the Timescale of AI
  • Kenshi Miyabe. An optimal superfarthingale and its convergence over a computable topological space
  • Tor Lattimore and Marcus Hutter. No Free Lunch versus Occam's Razor in Supervised Learning
  • Ian Wood, Peter Sunehag and Marcus Hutter. (Non-) equivalence of universal priors
  • John Woodward and Jerry Swan. A Syntactic Approach to Prediction
  • David Balduzzi. Falsification and future performance
  • Hayato Takahashi. Algorithmic analogies to Kamae-Weiss theorem on normal numbers
  • Daniel Schmidt. Minimum Message Length Order Selection and Parameter Estimation of Moving Average Models
  • Enes Makalic and Daniel Schmidt. Minimum Message Length Analysis of the Behrens--Fisher Problem
  • Enes Makalic and Lloyd Allison. MMLD Inference of Multilayer Perceptrons
  • Jean-Louis Dessalles. Algorithmic Simplicity and Relevance
  • Joe Suzuki. MDL/Bayesian Criteria based on Universal Coding/Measure
  • Jukka Corander, Yaqiong Cui and Timo Koski. Inductive Inference and Partition Exchangeability in Classification
  • Norbert Jankowski. Complexity measures for meta-learning and their optimality
  • Steve Petersen. Toward an Algorithmic Metaphysics
  • Rusins Freivalds. Algorithmic information theory  and computational complexity
  • Shane Legg and Joel Veness. An Approximation of the Universal Intelligence Measure
  • Eray Ozkural. Diverse Consequences of Algorithmic Probability
  • Amiza Amir, Anang Hudaya Muhammad Amin and Asad Iqbal Khan. Developing Machine Intelligence within P2P Networks Using a Distributed Associative Memory
  • T. Mark Ellison. Categorisation as Topographic Mapping between Uncorrelated Spaces
  • Elias Saleeby and Ray Solomonoff. On the application of algorithmic probability to autoregressive models
  • Kristiaan Pelckmans. An Adaptive Compression Algorithm in a Deterministic World
  • Adrian Silvescu and Vasant Honavar. Abstraction Super-structuring Normal Forms: Towards a Theory of Structural Induction
  • Alex Solomonoff. Locating a Discontinuity In a Piecewise-Smooth Periodic Function Using Bayes Estimation
  • Reginaldo Inojosa Da Silva Filho, Ricardo Luis De Azevedo Da Rocha and Ricardo Henrique Gracini Guiraldelli. Learning in the Limit: a mutational and adaptive approach
  • Rafal Rzepka, Koichi Muramoto and Kenji Araki. Limiting Context by Using The Web to Minimize Conceptual Jump Size
  • Douglas Campbell. The Semimeasure Property of Algorithmic Probability – “Feature” or “Bug”?
  • Ming Li. Partial Match Distance

  • Grace Solomonoff. Ray Solomonoff and the New Probability








Associated Events

Important Dates

Extended Deadline of Paper Submission: 2 July 2011
Notification of Acceptance of Paper: 3 September 2011
Receipt of Camera-Ready Copy: 12 September 2011
Conference Dates: 30 Nov. - 2 Dec. 2011

Ray Solomonoff's Publications

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