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Learning Probabilistic Automata and Markov Chains via Queries
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-51734-0_50openalex-snapshot
Inductive inference, DFAs, and computational complexity
inferredcites →https://doi.org/10.1007/3-540-56483-7_21openalex-snapshot
Cryptographic limitations on learning Boolean formulae and finite automata
inferredcites →https://doi.org/10.1007/bf00116034openalex-snapshot
Negative Results for Equivalence Queries
inferredcites →https://doi.org/10.1007/bf02579150openalex-snapshot
A new polynomial-time algorithm for linear programming
inferredcites →https://doi.org/10.1016/0012-365x(72)90124-0openalex-snapshot
Introduction to probabilistic automata
inferredcites →https://doi.org/10.1016/0022-0000(90)90028-jopenalex-snapshot
Prediction-preserving reducibility
inferredcites →https://doi.org/10.1016/0041-5553(80)90061-0openalex-snapshot
Polynomial algorithms in linear programming
inferredcites →https://doi.org/10.1016/0890-5401(87)90052-6openalex-snapshot
Learning regular sets from queries and counterexamples
inferredcites →https://doi.org/10.1016/b978-0-08-094829-4.50012-xopenalex-snapshot
Equivalence Queries and Approximate Fingerprints
inferredcites →https://doi.org/10.1016/c2013-0-11297-4openalex-snapshot
Introduction to Probabilistic Automata
inferredcites →https://doi.org/10.1016/s0019-9958(78)90562-4openalex-snapshot
Complexity of automaton identification from given data
inferredcites →https://doi.org/10.1016/s0019-9958(78)90683-6openalex-snapshot
On the complexity of minimum inference of regular sets
inferredcites →https://doi.org/10.1016/s0019-9958(81)90090-5openalex-snapshot
A note on the number of queries needed to identify regular languages
inferredcites →https://doi.org/10.1016/s0076-5392(08)60501-9openalex-snapshot
11 Stochastic Automata as Models of Learning Systems
inferredcites →https://doi.org/10.1109/sct.1989.41829openalex-snapshot
The minimum consistent DFA problem cannot be approximated within any polynomial
inferredcites →https://doi.org/10.1109/sfcs.1985.34openalex-snapshot
Inferring the structure of a Markov Chain from its output
inferredcites →https://doi.org/10.1109/sfcs.1988.21929openalex-snapshot
Learning probabilistic prediction functions
inferredcites →https://doi.org/10.1137/0221017openalex-snapshot
A Polynomial-Time Algorithm for the Equivalence of Probabilistic Automata
inferredcites →https://doi.org/10.1145/100216.100223openalex-snapshot
On the necessity of Occam algorithms
inferredcites →https://doi.org/10.1145/138027.138042openalex-snapshot
The minimum consistent DFA problem cannot be approximated within any polynomial
inferredcites →https://doi.org/10.1145/138027.138061openalex-snapshot
Learning read-once formulas with queries
inferredcites →https://doi.org/10.1145/174644.174647openalex-snapshot
Cryptographic Limitations on Learning Boolean Formulae and Finite Automata
inferredcites →https://doi.org/10.1145/28395.28426openalex-snapshot
On the learnability of Boolean formulae
inferredcites →https://doi.org/10.1145/73007.73048openalex-snapshot
The minimum consistent DFA problem cannot be approximated within and polynomial
inferredcites →https://doi.org/10.1145/73007.73049openalex-snapshot
Crytographic limitations on learning Boolean formulae and finite automata
inferredcites →https://doi.org/10.1145/76359.76371openalex-snapshot
Learnability and the Vapnik-Chervonenkis dimension
inferredcites →https://doi.org/10.5555/93025.93040openalex-snapshot
Equivalence of models for polynomial learnability
inferredcites →https://doi.org/10.5555/93335.93351openalex-snapshot
Equivalence queries and approximate fingerprints
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-1-4613-3394-4_2openalex-snapshot
Algorithms for Learning Finite Automata from Queries: A Unified View
inferred← citeshttps://doi.org/10.1007/978-3-030-30942-8_38openalex-snapshot
$$L^*$$-Based Learning of Markov Decision Processes
inferred← citeshttps://doi.org/10.1007/978-3-319-72056-2_5openalex-snapshot
Angluin Learning via Logic
inferred← citeshttps://doi.org/10.1007/978-3-642-24372-1_40openalex-snapshot
Learning-Based Compositional Verification for Synchronous Probabilistic Systems
inferred← citeshttps://doi.org/10.1007/bf00993822openalex-snapshot
Inferring finite automata with stochastic output functions and an application to map learning
inferred← citeshttps://doi.org/10.1007/s00165-021-00536-5openalex-snapshot
L∗-based learning of Markov decision processes (extended version)
inferred← citeshttps://doi.org/10.1007/s10994-016-5565-9openalex-snapshot
Learning deterministic probabilistic automata from a model checking perspective
inferred← citeshttps://doi.org/10.1017/s0960129523000373openalex-snapshot
Learning quantum finite automata with queries
inferred← citeshttps://doi.org/10.1023/a:1022874607797openalex-snapshot
Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning
inferred← citeshttps://doi.org/10.1109/icc54714.2021.9703130openalex-snapshot
Learning event-driven switched linear systems
inferred← citeshttps://doi.org/10.1109/iccis.2004.1460419openalex-snapshot
Supervised hidden Markov model learning using the state distribution Oracle
inferred← citeshttps://doi.org/10.1109/icmla.2004.1383496openalex-snapshot
Learning hidden Markov models from the state distribution oracle
inferred← citeshttps://doi.org/10.1109/lics.2012.54openalex-snapshot
Learning Probabilistic Systems from Tree Samples
inferred← citeshttps://doi.org/10.1109/lics.2017.8005101openalex-snapshot
Polynomial automata: Zeroness and applications
inferred← citeshttps://doi.org/10.1137/s009753979326091xopenalex-snapshot
Learning Behaviors of Automata from Multiplicity and Equivalence Queries
inferred← citeshttps://doi.org/10.1145/180139.181091openalex-snapshot
Inference and minimization of hidden Markov chains
inferred← citeshttps://doi.org/10.1145/2676726.2676998openalex-snapshot
Leveraging Weighted Automata in Compositional Reasoning about Concurrent Probabilistic Systems
inferred← citeshttps://doi.org/10.1145/2775051.2676998openalex-snapshot
Leveraging Weighted Automata in Compositional Reasoning about Concurrent Probabilistic Systems
inferred← citeshttps://doi.org/10.2298/vsp150708181mopenalex-snapshot
Artificial intelligence in clinical medicine and dentistry
inferred← citeshttps://doi.org/10.31390/gradschool_dissertations.4068openalex-snapshot
Learning discrete Hidden Markov Models from state distribution vectors
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