The following pages link to (Q4115138):
Displaying 50 items.
- On the role of update constraints and text-types in iterative learning (Q259061) (← links)
- Iterative learning from positive data and counters (Q391750) (← links)
- Iterative learning from texts and counterexamples using additional information (Q415613) (← links)
- Learning with ordinal-bounded memory from positive data (Q440010) (← links)
- Hypothesis spaces for learning (Q553319) (← links)
- Learning all subfunctions of a function (Q596299) (← links)
- Monotonic and dual monotonic language learning (Q672148) (← links)
- Automatic learning of subclasses of pattern languages (Q690501) (← links)
- Learning in the limit with lattice-structured hypothesis spaces (Q714848) (← links)
- Resource restricted computability theoretic learning: Illustrative topics and problems (Q733738) (← links)
- On the inference of approximate programs (Q803121) (← links)
- From learning in the limit to stochastic finite learning (Q860825) (← links)
- Learning recursive functions: A survey (Q924164) (← links)
- Reflective inductive inference of recursive functions (Q924166) (← links)
- Quantum inductive inference by finite automata (Q924168) (← links)
- Developments from enquiries into the learnability of the pattern languages from positive data (Q924175) (← links)
- Learning indexed families of recursive languages from positive data: A survey (Q924177) (← links)
- Learning in Friedberg numberings (Q939445) (← links)
- Iterative learning of simple external contextual languages (Q982646) (← links)
- Incremental learning with temporary memory (Q982647) (← links)
- On some open problems in monotonic and conservative learning (Q989527) (← links)
- U-shaped, iterative, and iterative-with-counter learning (Q1009263) (← links)
- Parallelism increases iterative learning power (Q1017664) (← links)
- Incremental learning of approximations from positive data (Q1029042) (← links)
- Saving the phenomena: Requirements that inductive inference machines not contradict known data (Q1115637) (← links)
- Research in the theory of inductive inference by GDR mathematicians - A survey (Q1151889) (← links)
- Aggregating inductive expertise on partial recursive functions (Q1187022) (← links)
- Separation of uniform learning classes. (Q1426150) (← links)
- On learning formulas in the limit and with assurance. (Q1607074) (← links)
- Learning pattern languages over groups (Q1663643) (← links)
- A theory of formal synthesis via inductive learning (Q1674868) (← links)
- Learnability of automatic classes (Q1757849) (← links)
- On the power of incremental learning. (Q1853517) (← links)
- Incremental concept learning for bounded data mining. (Q1854293) (← links)
- Variants of iterative learning (Q1870531) (← links)
- Decision lists over regular patterns. (Q1874229) (← links)
- Robust learning -- rich and poor (Q1880777) (← links)
- Recursion theoretic models of learning: Some results and intuitions (Q1924732) (← links)
- Learning secrets interactively. Dynamic modeling in inductive inference (Q1932174) (← links)
- Automatic learning from positive data and negative counterexamples (Q2013555) (← links)
- Learning languages with decidable hypotheses (Q2117759) (← links)
- Towards a map for incremental learning in the limit from positive and negative information (Q2117790) (← links)
- A solution to Wiehagen's thesis (Q2363964) (← links)
- Results on memory-limited U-shaped learning (Q2384927) (← links)
- Some natural conditions on incremental learning (Q2461797) (← links)
- Iterative learning from positive data and negative counterexamples (Q2464142) (← links)
- Automatic learners with feedback queries (Q2637649) (← links)
- Learning Pattern Languages over Groups (Q2830276) (← links)
- Priced Learning (Q2835616) (← links)
- Computability-theoretic learning complexity (Q2941604) (← links)
