Efficient Language Learning Efficient Language Learning from Restricted Informationfrom Restricted Information

Cristina BibireCristina Bibire

1919thth of May 2006 of May 2006

DEA defenceDEA defence

Professor Colin de la Professor Colin de la HigueraHiguera

Professor Victor MitranaProfessor Victor Mitrana

EURISEEURISE

University of Saint-Etienne, University of Saint-Etienne, FranceFrance

GRLMCGRLMCRovira i Virgili University, Rovira i Virgili University,

SpainSpain

Efficient Language Learning from Restricted InformationEfficient Language Learning from Restricted Information

Goal:

Incremental algorithm which is able to infer CFL (?) from:

-Text (positive examples)

- Correction queries (generalize membership queries)

Negative examples Equivalence queries

Efficient Language Learning from Restricted InformationEfficient Language Learning from Restricted Information

• Characterization of State Merging StrategiesSubmitted to URV Press, 9th of November 2005

Characterization of State Merging StrategiesCharacterization of State Merging Strategies

• TB algorithm (Trakhtenbrot and Barzdin – 1973)

• Gold’s algorithm (Gold – 1978)

• RPNI algorithm (Oncina and Garcia – 1992)

Regular Positive and Negative Inference

• Traxbar algorithm (Lang – 1992)

1997 – Abbadingo One Learning Competition

• EDSM algorithm (Lang, Pearlmutter, Price)

Evidence-Driven State Merging

• W-EDSM algorithm (Lang, Pearlmutter, Price)

Windowed EDSM

• Blue-fringe algorithm (Lang, Pearlmutter, Price)

• SAGE (Juillé – 1997)

Self-Adaptive Greedy Estimate

Efficient Language Learning from Restricted InformationEfficient Language Learning from Restricted Information

• Characterization of State Merging StrategiesSubmitted to URV Press, 9th of November 2005

• Learning DFA from CorrectionsCo-authors: Leonor Becerra-Bonache, Adrian Horia DediuPresented at TAGI, 22nd of September 2005

Learning DFA from CorrectionsLearning DFA from Corrections

Learning DFA from CorrectionsLearning DFA from Corrections

Efficient Language Learning from Restricted InformationEfficient Language Learning from Restricted Information

• Characterization of State Merging StrategiesSubmitted to URV Press, 9th of November 2005

• Learning DFA from CorrectionsCo-authors: Leonor Becerra-Bonache, Adrian Horia DediuPresented at TAGI, 22nd of September 2005

• Learning DFA from Correction and Equivalence queriesCo-authors: Leonor Becerra-Bonache, Adrian Horia Dediu

To be submitted to ALT 2006 – Barcelona, Deadline: 25th of May

Learning DFA from Correction and Equivalence QueriesLearning DFA from Correction and Equivalence Queries

Learning DFA from Correction and Equivalence QueriesLearning DFA from Correction and Equivalence Queries

Learning DFA from Correction and Equivalence QueriesLearning DFA from Correction and Equivalence Queries

Efficient Language Learning from Restricted InformationEfficient Language Learning from Restricted Information

• Characterization of State Merging StrategiesSubmitted to URV Press, 9th of November 2005

• Learning DFA from CorrectionsCo-authors: Leonor Becerra-Bonache, Adrian Horia DediuPresented at TAGI, 22nd of September 2005

• Learning DFA from Correction and Equivalence queriesCo-authors: Leonor Becerra-Bonache, Adrian Horia Dediu

To be submitted to ALT 2006 – Barcelona, Deadline: 25th of May• Learning 0-Reversible Languages from Correction Queries Only

Co-author: Colin de la HigueraTo be submitted to ICGI 2006 – Tokyo, Deadline: 27th of May

Learning 0-Reversible Languages from Correction Queries OnlyLearning 0-Reversible Languages from Correction Queries Only

Learning 0-Reversible Languages from Correction Queries OnlyLearning 0-Reversible Languages from Correction Queries Only

Learning 0-Reversible Languages from Correction Queries OnlyLearning 0-Reversible Languages from Correction Queries Only

Efficient Language Learning from Restricted InformationEfficient Language Learning from Restricted Information

• Characterization of State Merging StrategiesSubmitted to URV Press, 9th of November 2005

• Learning DFA from CorrectionsCo-authors: Leonor Becerra-Bonache, Adrian Horia DediuPresented at TAGI, 22nd of September 2005

• Learning DFA from Correction and Equivalence queriesCo-authors: Leonor Becerra-Bonache, Adrian Horia Dediu

To be submitted to ALT 2006 – Barcelona, Deadline: 25th of May• Learning 0-Reversible Languages from Correction Queries Only

Co-author: Colin de la HigueraTo be submitted to ICGI 2006 – Tokyo, Deadline: 27th of May

• Correction Queries - A New Approach in Active LearningCo-authors: Leonor Becerra-Bonache, Adrian Horia DediuTo be submitted to TCS – 25th of June

Efficient Language Learning from Restricted InformationEfficient Language Learning from Restricted Information

• Characterization of State Merging StrategiesSubmitted to URV Press, 9th of November 2005

• Learning DFA from CorrectionsCo-authors: Leonor Becerra-Bonache, Adrian Horia DediuPresented at TAGI, 22nd of September 2005

• Learning DFA from Correction and Equivalence queriesCo-authors: Leonor Becerra-Bonache, Adrian Horia Dediu

To be submitted to ALT 2006 – Barcelona, Deadline: 25th of May• Learning 0-Reversible Languages from Correction Queries Only

Co-author: Colin de la HigueraTo be submitted to ICGI 2006 – Tokyo, Deadline: 27th of May

• Correction Queries - A New Approach in Active LearningCo-authors: Leonor Becerra-Bonache, Adrian Horia DediuTo be submitted to TCS – 25th of June

• Learning RTL from Correction and Equivalence QueriesCo-author: Cătălin Ionuţ TîrnăucăTo be submitted to WATA 2006, Deadline: 31st of May

Learning RTL from Correction and Equivalence QueriesLearning RTL from Correction and Equivalence Queries

Learning RTL from Correction and Equivalence QueriesLearning RTL from Correction and Equivalence Queries

Learning RTL from Correction and Equivalence QueriesLearning RTL from Correction and Equivalence Queries