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Structural analysis of polynomial-time query learnability

https://doi.org/10.1007/bf01578844
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/3-540-16079-5openalex-snapshot
Complexity and Structure
inferredcites →https://doi.org/10.1007/3-540-51734-0_53openalex-snapshot
Towards representation independence in PAC learning
inferredcites →https://doi.org/10.1007/978-3-642-79235-9openalex-snapshot
Structural Complexity I
inferredcites →https://doi.org/10.1007/bf00116034openalex-snapshot
Negative Results for Equivalence Queries
inferredcites →https://doi.org/10.1007/bf00116828openalex-snapshot
Queries and Concept Learning
inferredcites →https://doi.org/10.1007/bf01578843openalex-snapshot
A framework for polynomial-time query learnability
inferredcites →https://doi.org/10.1016/0022-0000(90)90028-jopenalex-snapshot
Prediction-preserving reducibility
inferredcites →https://doi.org/10.1016/0304-3975(76)90061-xopenalex-snapshot
The polynomial-time hierarchy
inferredcites →https://doi.org/10.1109/sct.1991.160247openalex-snapshot
On the computational complexity of small descriptions
inferredcites →https://doi.org/10.1109/sct.1992.215399openalex-snapshot
Bounding the complexity of advice functions
inferredcites →https://doi.org/10.1145/103418.103420openalex-snapshot
When won't membership queries help?
inferredcites →https://doi.org/10.1145/174644.174647openalex-snapshot
Cryptographic Limitations on Learning Boolean Formulae and Finite Automata
inferredcites →https://doi.org/10.1145/1968.1972openalex-snapshot
A theory of the learnable
inferredcites →https://doi.org/10.1145/3749740.3749746openalex-snapshot
A Theory of the Learnable
inferredcites →https://doi.org/10.1145/6490.6503openalex-snapshot
How to construct random functions
inferredcites →https://doi.org/10.1145/73007.73049openalex-snapshot
Crytographic limitations on learning Boolean formulae and finite automata
inferredcites →https://doi.org/10.1145/800141.804678openalex-snapshot
Some connections between nonuniform and uniform complexity classes

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1006/jcss.1995.1037openalex-snapshot
Bounding the Complexity of Advice Functions
inferred← citeshttps://doi.org/10.1007/11776420_27openalex-snapshot
Efficient Learning Algorithms Yield Circuit Lower Bounds
inferred← citeshttps://doi.org/10.1007/3-540-36169-3_14openalex-snapshot
The Complexity of Learning Concept Classes with Polynomial General Dimension
inferred← citeshttps://doi.org/10.1007/3-540-59119-2_172openalex-snapshot
Learnability of Kolmogorov-easy circuit expressions via queries
inferred← citeshttps://doi.org/10.1007/3-540-59119-2_195openalex-snapshot
The query complexity of learning some subclasses of context-free grammars
inferred← citeshttps://doi.org/10.1007/3-540-61863-5_38openalex-snapshot
The complexity of exactly learning algebraic concepts
inferred← citeshttps://doi.org/10.1007/3-540-63577-7_50openalex-snapshot
Exact learning via teaching assistants (Extended abstract)
inferred← citeshttps://doi.org/10.1007/978-1-4613-3394-4_3openalex-snapshot
Coding Complexity: The Computational Complexity of Succinct Descriptions
inferred← citeshttps://doi.org/10.1007/bf01578843openalex-snapshot
A framework for polynomial-time query learnability
inferred← citeshttps://doi.org/10.1016/0304-3975(94)00016-6openalex-snapshot
Locating P/poly optimally in the extended low hierarchy
inferred← citeshttps://doi.org/10.1016/j.jcss.2008.07.006openalex-snapshot
Efficient learning algorithms yield circuit lower bounds
inferred← citeshttps://doi.org/10.1016/j.tcs.2005.10.016openalex-snapshot
The complexity of learning concept classes with polynomial general dimension
inferred← citeshttps://doi.org/10.1016/s0304-3975(99)00266-2openalex-snapshot
Exact learning via teaching assistants
inferred← citeshttps://doi.org/10.1109/sct.1994.315791openalex-snapshot
The complexity of learning with queries
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.