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- Sandra Zilles, Steffen Lange, Robert C. Holte, Martin Zinkevich
- Journal of Machine Learning Research
- 2011

While most supervised machine learning models assume that training examples are sampled at random or adversarially, this article is concerned with models of learning from a cooperative teacher that selects " helpful " training examples. The number of training examples a learner needs for identifying a concept in a given class C of possible target concepts… (More)

This paper is concerned with the combinatorial structure of concept classes that can be learned from a small number of examples. We show that the recently introduced notion of recursive teaching dimension (RTD, reflecting the complexity of teaching a concept class) is a relevant parameter in this context. Comparing the RTD to self-directed learning, we… (More)

- Sandra Zilles, Robert C. Holte
- Artif. Intell.
- 2010

ion is a powerful technique for speeding up planning and search. A problem that can arise in using abstraction is the generation of abstract states, called spurious states, from which the goal state is reachable in the abstract space but for which there is no corresponding state in the original space from which the goal state can be reached. Spurious states… (More)

- Steffen Lange, Thomas Zeugmann, Sandra Zilles
- Theor. Comput. Sci.
- 2008

In the past 40 years, research on inductive inference has developed along different lines, e.g., in the formalizations used, and in the classes of target concepts considered. One common root of many of these formalizations is Gold's model of identification in the limit. This model has been studied for learning recursive functions, recur-sively enumerable… (More)

- Thorsten Doliwa, Gaojian Fan, Hans Ulrich Simon, Sandra Zilles
- Journal of Machine Learning Research
- 2014

This paper is concerned with various combinatorial parameters of classes that can be learned from a small set of examples. We show that the recursive teaching dimension, recently introduced by Zilles et al. (2008), is strongly connected to known complexity notions in machine learning, e.g., the self-directed learning complexity and the VC-dimension. To the… (More)

The problem of how a teacher and a learner can cooperate in the process of learning concepts from examples in order to minimize the required sample size without " coding tricks " has been widely addressed , yet without achieving teaching and learning protocols that meet what seems intuitively an optimal choice for selecting samples in teaching. We introduce… (More)

- Steffen Lange, Samuel E. Moelius, Sandra Zilles
- ALT
- 2008

In the inductive inference framework of learning in the limit, a variation of the bounded example memory (B em) language learning model is considered. Intuitively, the new model constrains the learner's memory not only in how much data may be retained, but also in how long that data may be retained. More specifically, the model requires that, if a learner… (More)

- Randy Goebel, Sandra Zilles, Christoph Ringlstetter, Andreas Dengel, Gunnar Aastrand Grimnes
- AAAI Spring Symposium: Symbiotic Relationships…
- 2008

The World Wide Web Consortium (W3C) has been the consolidator for many ideas regarding the evolution of the World Wide Web (WWW), including the promotion of the so-called " Semantic Layer Cake " model for the development of the semantic web. The semantic layer cake provides a framework to discuss a variety of approaches to an integrated view of the… (More)

- Shahab Jabbari Arfaee, Sandra Zilles, Robert C. Holte
- Artif. Intell.
- 2011

In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a r t i c l e i n f o a b s t r a c t We investigate the use of machine learning to… (More)

- Thomas Zeugmann, Sandra Zilles
- Theor. Comput. Sci.
- 2008

Studying the learnability of classes of recursive functions has attracted considerable interest for at least four decades. Starting with Gold's (1967) model of learning in the limit, many variations, modifications and extensions have been proposed. These models differ in some of the following: the mode of convergence, the requirements intermediate… (More)