Most of my articles are available online from
the arXiv 
in PDF 
,
PostScript 
,
and LaTeX 
format.
Sometimes also
slides (PS
,
PDF
,
PPT
),
program code 
,
press coverage 
,
project information 
,
BibTeX entry 
,
and/or more 
are available.
Some key publications are highlighted by a *.
They include a
book,
my physics and AI ideas I'm most proud of,
my most popular paper,
a rather technical paper,
a patent,
and my first publication.
Maybe you prefer them sorted w.r.t. topic or
the DBLP listing
or in BibTeX format.
- The Loss Rank Principle for Model Selection
Proc. 20th Annual Conf. on Learning Theory (COLT-2007) 589-603
[for (non)parametric non-stochastic regression and classification like kNN]
- Bayesian Regression of Piecewise Constant Functions
Bayesian Statistics 8 (ISBA-2007) 607-612
[Lindley prize for innovative research in Bayesian statistics]
- Fitness Uniform Optimization (with S. Legg)
IEEE Transactions on Evolutionary Computation, 10:5 (2006) 568-589
[a simple effective selection scheme with no explicit selection pressure]
- Asymptotics of Discrete MDL for Online Prediction (with J. Poland)
IEEE Transactions on Information Theory, 51:11 (2005) 3780-3795
[the Minimal Description Length principle for discrete model classes]
- Hybrid Rounding Techniques for Knapsack Problems (with M. Mastrolilli)
Discrete Applied Mathematics, 154:4 (2006) 640--649
[a linear!time algorithm for the knapsack problem]
- Adaptive Online Prediction by Following the Perturbed Leader (with J. Poland)
Journal of Machine Learning Research 6 (2005) 639-660
[elegant Sqrt(Loss) regret for general loss and adaptive learning rate]
- Distribution of Mutual Information from Complete and Incomplete Data (with M. Zaffalon)
Computational Statistics & Data Analysis 48:3 (2005) 633-657
[simple, fast, and useful expressions]
- Practical Robust Estimators under the Imprecise Dirichlet Model
International Journal of Approximate Reasoning, 50:2 (2009) 231-242
[simple, fast, and useful expressions]
- Towards a Universal Theory of Artificial
Intelligence based on Algorithmic Probability and Sequential Decisions
Proc. 12th European Conf. on Machine Learning (ECML-2001) 226-238
[first publication of the Universal AIXI model]
- Instantons in QCD: Theory and Application of the
Instanton Liquid Model
Ph.D. Thesis, LMU (1996), hep-ph/0107098
[nice introduction with some new results, but nothing remarkable]
Publications in Artificial Intelligence and Related Fields (Statistics & TCS)
My research in AI is centered around
universal artificial intelligence,
algorithmic information theory (see below),
the minimum description length principle,
(universal) Bayesian sequence prediction,
robust predictions,
optimization problems,
(universal) sequential decision theory =
adaptive control theory =
machine/reinforcement learning (agents), and
probability theory and statistics (see below).
Occasionally I also published in the areas of
prediction with expert advice,
computational complexity theory [1,2,3],
genetic algorithms,
and neural nets.
- Discrete MDL Predicts in Total Variation
Advances in Neural Information Processing Systems 22 (NIPS-2009) 817-825
- Matching 2-D Ellipses to 3-D Circles with Application to Vehicle Pose Estimation (with N. Brewer)
Proc. 24th Conf. on Image and Vision Computing New Zealand (IVCNZ-2009) ??-??
- mBPCR: A Package for DNA Copy Number Profile Estimation (with P. M. V. Rancoita)
BioConductor -- Open Source Software for BioInformatics (2009) 1-25
- Feature Reinforcement Learning: Part I: Unstructured MDPs*
Journal of Artificial General Intelligence, 1 (2009) 3-24
- Open Problems in Universal Induction & Intelligence
Algorithms, 3:2 (2009)879-906
- A New Local Distance-based Outlier Detection Approach for Scattered Real-World Data (with K. Zhang & H. Jin)
Proc. 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2009) 813-822
- ALT'07 Special Issue (with R. A. Servedio, editors)
Theoretical Computer Science, 410:19 (2009) 1747-1748/1912
- Limits of Learning about a Categorical Latent Variable under Prior Near-Ignorance (with A. Piatti & M. Zaffalon & F. Trojani)
International Journal of Approximate Reasoning, 50:4 (2009) 597-611
- Exact Non-Parametric Bayesian Inference on Infinite Trees
Technical Report, arXiv 0903.5342 (2009) 1-32
- Artificial General Intelligence 2009: Proceedings (with B. Goertzel & P. Hitzler)
Advances in Intelligent Systems Research 8 (2009), Atlantis Press, Paris
- Feature Markov Decision Processes
Proc. 2nd Conf. on Artificial General Intelligence (AGI-2009) 61-66
- Feature Dynamic Bayesian Networks
Proc. 2nd Conf. on Artificial General Intelligence (AGI-2009) 67-73
- Practical Robust Estimators under the Imprecise Dirichlet Model*
International Journal of Approximate Reasoning, 50:2 (2009) 231-242
- Bayesian DNA Copy Number Analysis (with P. M. V. Rancoita & F. Bertoni & I. Kwee)
BMC Bioinformatics, 10:10 (2009) 1-19
- Tests of Machine Intelligence (with S. Legg)
In 50 Years of Artificial Intelligence, LNAI4850 (2007) 232-242
- Universal Intelligence: A Definition of Machine Intelligence* (with S. Legg)
Minds and Machines, 17:4 (2007) 391-444
- Exact Bayesian Regression of Piecewise Constant Functions*
Bayesian Analysis 2:4 (2007) 635-664
(C-Code and R-Code)
- Algorithmic Learning Theory 2007: Proceedings (with R. A. Servedio and E. Takimoto)
Lecture Notes in Artificial Intelligence, LNAI 4754 (2007), Springer, Berlin
- Algorithmic Learning Theory 2007: Editors' introduction (with R. A. Servedio and E. Takimoto)
Proc. 18th International Conf. on Algorithmic Learning Theory (ALT-2007) 1-8
- On Universal Prediction and Bayesian Confirmation*
Theoretical Computer Science, 384:1 (2007) 33-48
- On Semimeasures Predicting Martin-Loef Random Sequences (with An. A. Muchnik)
Theoretical Computer Science, 382:3 (2007) 247-261
- Algorithmic Probability (with S. Legg and P.M.B. Vitanyi)
Scholarpedia, 2:8 (2007) 2572
- Learning about a Categorical Latent Variable under Prior Near-Ignorance (with A. Piatti and M. Zaffalon and F. Trojani)
Proc. 5th International Symposium on Imprecise Probability: Theories and Applications (ISIPTA-2007) 357-364
- Bayesian Regression of Piecewise Constant Functions
Bayesian Statistics 8 (ISBA-2007) 607-612
(C-Code and R-Code)
- On Sequence Prediction for Arbitrary Measures (with D. Ryabko)
Proc. IEEE International Symposium on Information Theory (ISIT 2007) 2346-2350
- A Collection of Definitions of Intelligence (with S. Legg)
Frontiers in Artificial Intelligence and Applications, 157 (2007) 17-24
- The Loss Rank Principle for Model Selection*
Proc. 20th Annual Conf. on Learning Theory (COLT-2007) 589-603
- Algorithmic Information Theory: a brief non-technical guide to the field*
Scholarpedia, 2:3 (2007) 2519
- Algorithmic Complexity Bounds on Future Prediction Errors (with A. Chernov & J. Schmidhuber)
Information and Computation, 205:2 (2007) 242-261
- Universal Algorithmic Intelligence: A mathematical top->down approach*
Artificial General Intelligence (2007) 227-290, Springer
Publications in Particle Physics (QCD, Instantons)
My physics research concentrates on non-perturbative QCD, especially
instantons, gluon mass,
quark propagator, eta'
mass, meson correlators and masses, and
proton spin. My favorite paper explains the
exponential fermion mass spectrum between
successive generations. Further work can be found in the publication list
below and on my particle physics page.
| © 2000 by ... |
|
... Marcus Hutter |
