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Dana Angluin
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- affiliation: Yale University
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2020 – today
- 2024
- [j55]Dana Angluin, Dana Fisman:
Constructing Concise Characteristic Samples for Acceptors of Omega Regular Languages. Log. Methods Comput. Sci. 20(4) (2024) - [j54]Lena Strobl, William Merrill, Gail Weiss, David Chiang, Dana Angluin:
What Formal Languages Can Transformers Express? A Survey. Trans. Assoc. Comput. Linguistics 12: 543-561 (2024) - [i11]Lena Strobl, Dana Angluin, David Chiang, Jonathan Rawski, Ashish Sabharwal:
Transformers as Transducers. CoRR abs/2404.02040 (2024) - 2023
- [c55]Dana Angluin:
Learning of Regular Languages by Recurrent Neural Networks? (Mainly Questions). ICGI 2023: 4 - [i10]Dana Angluin, David Chiang, Andy Yang:
Masked Hard-Attention Transformers and Boolean RASP Recognize Exactly the Star-Free Languages. CoRR abs/2310.13897 (2023) - [i9]Lena Strobl, William Merrill, Gail Weiss, David Chiang, Dana Angluin:
Transformers as Recognizers of Formal Languages: A Survey on Expressivity. CoRR abs/2311.00208 (2023) - 2022
- [j53]Yiding Hao, Dana Angluin, Robert Frank:
Formal Language Recognition by Hard Attention Transformers: Perspectives from Circuit Complexity. Trans. Assoc. Comput. Linguistics 10: 800-810 (2022) - [c54]Dana Angluin, Timos Antonopoulos, Dana Fisman, Nevin George:
Representing Regular Languages of Infinite Words Using Mod 2 Multiplicity Automata. FoSSaCS 2022: 1-20 - [i8]Yiding Hao, Dana Angluin, Robert Frank:
Formal Language Recognition by Hard Attention Transformers: Perspectives from Circuit Complexity. CoRR abs/2204.06618 (2022) - [i7]Dana Angluin, Dana Fisman, Yaara Shoval:
Polynomial Identification of omega-Automata. CoRR abs/2209.09336 (2022) - 2021
- [j52]Dana Angluin, Dana Fisman:
Regular ω-languages with an informative right congruence. Inf. Comput. 278: 104598 (2021) - 2020
- [j51]Dana Angluin, Tyler Dohrn:
The power of random counterexamples. Theor. Comput. Sci. 808: 2-13 (2020) - [c53]Dana Angluin, Timos Antonopoulos, Dana Fisman:
Strongly Unambiguous Büchi Automata Are Polynomially Predictable With Membership Queries. CSL 2020: 8:1-8:17 - [c52]Dana Angluin, Dana Fisman, Yaara Shoval:
Polynomial Identification of ømega-Automata. TACAS (2) 2020: 325-343 - [i6]Dana Angluin, Dana Fisman:
Polynomial time algorithms for inclusion and equivalence of deterministic omega acceptors. CoRR abs/2002.03191 (2020)
2010 – 2019
- 2019
- [j50]Dana Angluin, Timos Antonopoulos, Dana Fisman:
Query learning of derived ωω\omega-tree languages in polynomial time. Log. Methods Comput. Sci. 15(3) (2019) - 2018
- [j49]Dana Angluin, Udi Boker, Dana Fisman:
Families of DFAs as Acceptors of ω-Regular Languages. Log. Methods Comput. Sci. 14(1) (2018) - [c51]Yiding Hao, William Merrill, Dana Angluin, Robert Frank, Noah Amsel, Andrew Benz, Simon Mendelsohn:
Context-Free Transductions with Neural Stacks. BlackboxNLP@EMNLP 2018: 306-315 - [c50]Dana Angluin, Dana Fisman:
Regular omega-Languages with an Informative Right Congruence. GandALF 2018: 265-279 - [i5]Dana Angluin, Timos Antonopoulos, Dana Fisman:
Query learning of derived ω-tree languages in polynomial time. CoRR abs/1802.04739 (2018) - [i4]Yiding Hao, William Merrill, Dana Angluin, Robert Frank, Noah Amsel, Andrew Benz, Simon Mendelsohn:
Context-Free Transductions with Neural Stacks. CoRR abs/1809.02836 (2018) - 2017
- [j48]Dana Angluin, Leonor Becerra-Bonache:
A model of language learning with semantics and meaning-preserving corrections. Artif. Intell. 242: 23-51 (2017) - [c49]Dana Angluin, Tyler Dohrn:
The Power of Random Counterexamples. ALT 2017: 452-465 - [c48]Dana Angluin, Timos Antonopoulos, Dana Fisman:
Query Learning of Derived Omega-Tree Languages in Polynomial Time. CSL 2017: 10:1-10:21 - 2016
- [j47]Dana Angluin, Dana Fisman:
Learning regular omega languages. Theor. Comput. Sci. 650: 57-72 (2016) - [c47]Dana Angluin, Udi Boker, Dana Fisman:
Families of DFAs as Acceptors of omega-Regular Languages. MFCS 2016: 11:1-11:14 - [i3]Dana Angluin, Udi Boker, Dana Fisman:
Families of DFAs as Acceptors of $ω$-Regular Languages. CoRR abs/1612.08154 (2016) - 2015
- [j46]Dana Angluin, James Aspnes, Lev Reyzin:
Network construction with subgraph connectivity constraints. J. Comb. Optim. 29(2): 418-432 (2015) - [c46]Dana Angluin, Dongqu Chen:
Learning a Random DFA from Uniform Strings and State Information. ALT 2015: 119-133 - [c45]Dana Angluin, Sarah Eisenstat, Dana Fisman:
Learning Regular Languages via Alternating Automata. IJCAI 2015: 3308-3314 - 2014
- [j45]Dana Angluin, James Aspnes, Rida A. Bazzi, Jiang Chen, David Eisenstat, Goran Konjevod:
Effective storage capacity of labeled graphs. Inf. Comput. 234: 44-56 (2014) - [c44]Dana Angluin, Dana Fisman:
Learning Regular Omega Languages. ALT 2014: 125-139 - 2013
- [j44]Dana Angluin, James Aspnes, Raonne Barbosa Vargas:
Mutation systems. Int. J. Comput. Math. 90(6): 1132-1149 (2013) - [j43]Dana Angluin, James Aspnes, Sarah Eisenstat, Aryeh Kontorovich:
On the learnability of shuffle ideals. J. Mach. Learn. Res. 14(1): 1513-1531 (2013) - [c43]Azza Abouzied, Dana Angluin, Christos H. Papadimitriou, Joseph M. Hellerstein, Avi Silberschatz:
Learning and verifying quantified boolean queries by example. PODS 2013: 49-60 - [i2]Azza Abouzied, Dana Angluin, Christos H. Papadimitriou, Joseph M. Hellerstein, Avi Silberschatz:
Learning and Verifying Quantified Boolean Queries by Example. CoRR abs/1304.4303 (2013) - 2012
- [c42]Dana Angluin, James Aspnes, Aryeh Kontorovich:
On the Learnability of Shuffle Ideals. ALT 2012: 111-123 - 2011
- [c41]Dana Angluin, Leonor Becerra-Bonache:
Effects of Meaning-Preserving Corrections on Language Learning. CoNLL 2011: 97-105 - [c40]Dana Angluin, Leonor Becerra-Bonache:
An Overview of How Semantics and Corrections Can Help Language Learning. Web Intelligence/IAT Workshops 2011: 147-150 - [c39]Dana Angluin, James Aspnes, Raonne Barbosa Vargas:
Mutation Systems. LATA 2011: 92-104 - 2010
- [j42]Dana Angluin, James Aspnes, Lev Reyzin:
Optimally learning social networks with activations and suppressions. Theor. Comput. Sci. 411(29-30): 2729-2740 (2010) - [c38]Dana Angluin, James Aspnes, Lev Reyzin:
Inferring Social Networks from Outbreaks. ALT 2010: 104-118 - [c37]Dana Angluin, David Eisenstat, Leonid Kontorovich, Lev Reyzin:
Lower Bounds on Learning Random Structures with Statistical Queries. ALT 2010: 194-208 - [c36]Dana Angluin, James Aspnes, Rida A. Bazzi, Jiang Chen, David Eisenstat, Goran Konjevod:
Storage Capacity of Labeled Graphs. SSS 2010: 573-587
2000 – 2009
- 2009
- [j41]Dana Angluin, James Aspnes, Jiang Chen, Yinghua Wu:
Learning a circuit by injecting values. J. Comput. Syst. Sci. 75(1): 60-77 (2009) - [j40]Dana Angluin, James Aspnes, Jiang Chen, David Eisenstat, Lev Reyzin:
Learning Acyclic Probabilistic Circuits Using Test Paths. J. Mach. Learn. Res. 10: 1881-1911 (2009) - [c35]Dana Angluin, Leonor Becerra-Bonache, Adrian-Horia Dediu, Lev Reyzin:
Learning Finite Automata Using Label Queries. ALT 2009: 171-185 - 2008
- [j39]Dana Angluin, James Aspnes, David Eisenstat:
A simple population protocol for fast robust approximate majority. Distributed Comput. 21(2): 87-102 (2008) - [j38]Dana Angluin, James Aspnes, David Eisenstat:
Fast computation by population protocols with a leader. Distributed Comput. 21(3): 183-199 (2008) - [j37]Dana Angluin, Jiang Chen:
Learning a hidden graph using O(logn) queries per edge. J. Comput. Syst. Sci. 74(4): 546-556 (2008) - [j36]Dana Angluin, James Aspnes, Jiang Chen, Lev Reyzin:
Learning large-alphabet and analog circuits with value injection queries. Mach. Learn. 72(1-2): 113-138 (2008) - [j35]Dana Angluin, James Aspnes, Michael J. Fischer, Hong Jiang:
Self-stabilizing population protocols. ACM Trans. Auton. Adapt. Syst. 3(4): 13:1-13:28 (2008) - [c34]Dana Angluin, James Aspnes, Lev Reyzin:
Optimally Learning Social Networks with Activations and Suppressions. ALT 2008: 272-286 - [c33]Dana Angluin, James Aspnes, Jiang Chen, David Eisenstat, Lev Reyzin:
Learning Acyclic Probabilistic Circuits Using Test Paths. COLT 2008: 169-180 - [c32]Dana Angluin, Leonor Becerra-Bonache:
Learning Meaning Before Syntax. ICGI 2008: 1-14 - 2007
- [j34]Dana Angluin, James Aspnes, David Eisenstat, Eric Ruppert:
The computational power of population protocols. Distributed Comput. 20(4): 279-304 (2007) - [j33]David Eisenstat, Dana Angluin:
The VC dimension of k-fold union. Inf. Process. Lett. 101(5): 181-184 (2007) - [c31]Dana Angluin, James Aspnes, Jiang Chen, Lev Reyzin:
Learning Large-Alphabet and Analog Circuits with Value Injection Queries. COLT 2007: 51-65 - [c30]Dana Angluin, James Aspnes, David Eisenstat:
A Simple Population Protocol for Fast Robust Approximate Majority. DISC 2007: 20-32 - 2006
- [j32]Dana Angluin, James Aspnes, Zoë Diamadi, Michael J. Fischer, René Peralta:
Computation in networks of passively mobile finite-state sensors. Distributed Comput. 18(4): 235-253 (2006) - [j31]Dana Angluin, Jiang Chen:
Learning a Hidden Hypergraph. J. Mach. Learn. Res. 7: 2215-2236 (2006) - [c29]Dana Angluin, Michael J. Fischer, Hong Jiang:
Stabilizing Consensus in Mobile Networks. DCOSS 2006: 37-50 - [c28]Dana Angluin, James Aspnes, David Eisenstat:
Stably computable predicates are semilinear. PODC 2006: 292-299 - [c27]Dana Angluin, James Aspnes, Jiang Chen, Yinghua Wu:
Learning a circuit by injecting values. STOC 2006: 584-593 - [c26]Dana Angluin, James Aspnes, David Eisenstat:
Fast Computation by Population Protocols with a Leader. DISC 2006: 61-75 - [i1]Dana Angluin, James Aspnes, David Eisenstat, Eric Ruppert:
The computational power of population protocols. CoRR abs/cs/0608084 (2006) - 2005
- [c25]Dana Angluin, Jiang Chen:
Learning a Hidden Hypergraph. COLT 2005: 561-575 - [c24]Dana Angluin, James Aspnes, Melody Chan, Michael J. Fischer, Hong Jiang, René Peralta:
Stably Computable Properties of Network Graphs. DCOSS 2005: 63-74 - [c23]Dana Angluin, James Aspnes, Michael J. Fischer, Hong Jiang:
Self-stabilizing Population Protocols. OPODIS 2005: 103-117 - [c22]Dana Angluin, James Aspnes, David Eisenstat, Eric Ruppert:
On the Power of Anonymous One-Way Communication. OPODIS 2005: 396-411 - [c21]Dana Angluin, James Aspnes, Jiang Chen, Yinghua Wu, Yitong Yin:
Fast construction of overlay networks. SPAA 2005: 145-154 - 2004
- [j30]Dana Angluin:
Queries revisited. Theor. Comput. Sci. 313(2): 175-194 (2004) - [c20]Dana Angluin, Jiang Chen:
Learning a Hidden Graph Using O(log n) Queries Per Edge. COLT 2004: 210-223 - [c19]Dana Angluin:
Learning and Mathematics. ICGI 2004: 1-2 - [c18]Dana Angluin, James Aspnes, Zoë Diamadi, Michael J. Fischer, René Peralta:
Computation in networks of passively mobile finite-state sensors. PODC 2004: 290-299 - 2003
- [j29]Dana Angluin, Martins Krikis:
Learning from Different Teachers. Mach. Learn. 51(2): 137-163 (2003) - 2001
- [j28]Chinda Wongngamnit, Dana Angluin:
Robot localization in a grid. Inf. Process. Lett. 77(5-6): 261-267 (2001) - [c17]Dana Angluin:
Queries Revisited. ALT 2001: 12-31 - [c16]Dana Angluin:
Queries Revisited. Discovery Science 2001: 16 - 2000
- [j27]Dana Angluin, Jeffery R. Westbrook, Wenhong Zhu:
Robot Navigation with Distance Queries. SIAM J. Comput. 30(1): 110-144 (2000)
1990 – 1999
- 1997
- [j26]Dana Angluin, Martins Krikis, Robert H. Sloan, György Turán:
Malicious Omissions and Errors in Answers to Membership Queries. Mach. Learn. 28(2-3): 211-255 (1997) - [c15]Dana Angluin, Martins Krikis:
Teachers, Learners and Black Boxes. COLT 1997: 285-297 - [c14]Dana Angluin, Miklós Csürös:
Learning Markov Chains with Variable Memory Length from Noisy Output. COLT 1997: 298-308 - 1996
- [j25]Dana Angluin:
A 1996 Snapshot of Computational Learning Theory. ACM Comput. Surv. 28(4es): 216 (1996) - [c13]Dana Angluin, Jeffery R. Westbrook, Wenhong Zhu:
Robot Navigation with Range Queries. STOC 1996: 469-478 - 1995
- [j24]Dana Angluin, Michael Kharitonov:
When Won't Membership Queries Help? J. Comput. Syst. Sci. 50(2): 336-355 (1995) - [j23]Thomas L. Dean, Dana Angluin, Kenneth Basye, Sean P. Engelson, Leslie Pack Kaelbling, Evangelos Kokkevis, Oded Maron:
Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning. Mach. Learn. 18(1): 81-108 (1995) - 1994
- [j22]Dana Angluin, Donna K. Slonim:
Randomly Fallible Teachers: Learning Monotone DNF with an Incomplete Membership Oracle. Mach. Learn. 14(1): 7-26 (1994) - [c12]Dana Angluin, Martins Krikis:
Learning with Malicious Membership Queries and Exceptions (Extended Abstract). COLT 1994: 57-66 - 1993
- [j21]Dana Angluin, Lisa Hellerstein, Marek Karpinski:
Learning Read-Once Formulas with Queries. J. ACM 40(1): 185-210 (1993) - 1992
- [j20]Dana Angluin, Michael Frazier, Leonard Pitt:
Learning Conjunctions of Horn Clauses. Mach. Learn. 9: 147-164 (1992) - [c11]Thomas L. Dean, Dana Angluin, Kenneth Basye, Sean P. Engelson, Leslie Pack Kaelbling, Evangelos Kokkevis, Oded Maron:
Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning. AAAI 1992: 208-214 - [c10]Dana Angluin:
Computational Learning Theory: Survey and Selected Bibliography. STOC 1992: 351-369 - 1991
- [c9]Dana Angluin, Donna K. Slonim:
Learning Monotone DNF with an Incomplete Membership Oracle. COLT 1991: 139-146 - [c8]Dana Angluin, Michael Kharitonov:
When Won't Membership Queries Help? (Extended Abstract). STOC 1991: 444-454 - 1990
- [j19]Dana Angluin:
Negative Results for Equivalence Queries. Mach. Learn. 5: 121-150 (1990) - [c7]Dana Angluin, Michael Frazier, Leonard Pitt:
Learning Conjunctions of Horn Clauses (Abstract). COLT 1990: 387 - [c6]Dana Angluin, Michael Frazier, Leonard Pitt:
Learning Conjunctions of Horn Clauses (Extended Abstract). FOCS 1990: 186-192
1980 – 1989
- 1989
- [j18]Dana Angluin, William I. Gasarch, Carl H. Smith:
Training Sequences. Theor. Comput. Sci. 66(3): 255-272 (1989) - [c5]Dana Angluin:
Equivalence Queries and Approximate Fingerprints. COLT 1989: 134-145 - 1988
- [c4]Dana Angluin:
Learning With Hints. COLT 1988: 167-181 - 1987
- [j17]Dana Angluin:
Learning Regular Sets from Queries and Counterexamples. Inf. Comput. 75(2): 87-106 (1987) - [j16]Dana Angluin:
Queries and Concept Learning. Mach. Learn. 2(4): 319-342 (1987) - [j15]Dana Angluin, Philip D. Laird:
Learning From Noisy Examples. Mach. Learn. 2(4): 343-370 (1987) - 1984
- [j14]Dana Angluin, Douglas N. Hoover:
Regular Prefix Relations. Math. Syst. Theory 17(3): 167-191 (1984) - 1983
- [j13]Dana Angluin, Carl H. Smith:
Inductive Inference: Theory and Methods. ACM Comput. Surv. 15(3): 237-269 (1983) - 1982
- [j12]Timothy A. Budd, Dana Angluin:
Two Notions of Correctness and Their Relation to Testing. Acta Informatica 18: 31-45 (1982) - [j11]Dana Angluin:
Inference of Reversible Languages. J. ACM 29(3): 741-765 (1982) - 1981
- [j10]Dana Angluin:
A Note on the Number of Queries Needed to Identify Regular Languages. Inf. Control. 51(1): 76-87 (1981) - [j9]Dana Angluin, A. Gardiner:
Finite common coverings of pairs of regular graphs. J. Comb. Theory B 30(2): 184-187 (1981) - 1980
- [j8]Dana Angluin:
Inductive Inference of Formal Languages from Positive Data. Inf. Control. 45(2): 117-135 (1980) - [j7]Dana Angluin:
Finding Patterns Common to a Set of Strings. J. Comput. Syst. Sci. 21(1): 46-62 (1980) - [j6]Dana Angluin:
On Relativizing Auxiliary Pushdown Machines. Math. Syst. Theory 13: 283-299 (1980) - [j5]Dana Angluin:
On Counting Problems and the Polynomial-Time Hierarchy. Theor. Comput. Sci. 12: 161-173 (1980) - [c3]Dana Angluin:
Local and Global Properties in Networks of Processors (Extended Abstract). STOC 1980: 82-93
1970 – 1979
- 1979
- [j4]Dana Angluin:
A Note on a Construction of Margulis. Inf. Process. Lett. 8(1): 17-19 (1979) - [j3]Dana Angluin, Leslie G. Valiant:
Fast Probabilistic Algorithms for Hamiltonian Circuits and Matchings. J. Comput. Syst. Sci. 18(2): 155-193 (1979) - [c2]Dana Angluin:
Finding Patterns Common to a Set of Strings (Extended Abstract). STOC 1979: 130-141 - 1978
- [j2]Dana Angluin:
On the Complexity of Minimum Inference of Regular Sets. Inf. Control. 39(3): 337-350 (1978) - 1977
- [c1]Dana Angluin, Leslie G. Valiant:
Fast Probabilistic Algorithms for Hamiltonian Circuits and Matchings. STOC 1977: 30-41 - 1976
- [j1]Dana Angluin:
The four Russians' algorithm for boolean matrix multiplication is optimal in its class. SIGACT News 8(1): 29-33 (1976)
Coauthor Index
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last updated on 2024-11-27 20:23 CET by the dblp team
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