2008 | ||
---|---|---|
116 | EE | David Haussler: Computing how we became human. STOC 2008: 639-640 |
115 | EE | Mario Stanke, Mark Diekhans, Robert Baertsch, David Haussler: Using native and syntenically mapped cDNA alignments to improve de novo gene finding. Bioinformatics 24(5): 637-644 (2008) |
114 | EE | Jian Ma, Aakrosh Ratan, Brian J. Raney, Bernard B. Suh, Louxin Zhang, Webb Miller, David Haussler: DUPCAR: Reconstructing Contiguous Ancestral Regions with Duplications. Journal of Computational Biology 15(8): 1007-1027 (2008) |
113 | EE | Donna Karolchik, Robert M. Kuhn, Robert Baertsch, Galt P. Barber, Hiram Clawson, Mark Diekhans, Belinda Giardine, Rachel A. Harte, Angela S. Hinrichs, Fan Hsu, K. M. Kober, Webb Miller, J. S. Pedersen, Andy Pohl, Brian J. Raney, Brooke L. Rhead, Kate R. Rosenbloom, Kayla E. Smith, Mario Stanke, Archana Thakkapallayil, Heather Trumbower, T. Wang, Ann S. Zweig, David Haussler, W. James Kent: The UCSC Genome Browser Database: 2008 update. Nucleic Acids Research 36(Database-Issue): 773-779 (2008) |
2007 | ||
112 | EE | Jian Ma, Aakrosh Ratan, Louxin Zhang, Webb Miller, David Haussler: A Heuristic Algorithm for Reconstructing Ancestral Gene Orders with Duplications. RECOMB-CG 2007: 122-135 |
111 | EE | Daryl J. Thomas, Kate R. Rosenbloom, Hiram Clawson, Angie S. Hinrichs, Heather Trumbower, Brian J. Raney, Donna Karolchik, Galt P. Barber, Rachel A. Harte, Jennifer Hillman-Jackson, Robert M. Kuhn, Brooke L. Rhead, Kayla E. Smith, Archana Thakkapallayil, Ann S. Zweig, David Haussler, W. James Kent: The ENCODE Project at UC Santa Cruz. Nucleic Acids Research 35(Database-Issue): 663-667 (2007) |
110 | EE | Robert M. Kuhn, Donna Karolchik, Ann S. Zweig, Heather Trumbower, Daryl J. Thomas, Archana Thakkapallayil, Charles W. Sugnet, Mario Stanke, Kayla E. Smith, Adam C. Siepel, Kate R. Rosenbloom, Brooke L. Rhead, Brian J. Raney, Andy Pohl, J. S. Pedersen, Fan Hsu, Angela S. Hinrichs, Rachel A. Harte, Mark Diekhans, Hiram Clawson, Gill Bejerano, Galt P. Barber, Robert Baertsch, David Haussler, W. James Kent: The UCSC genome browser database: update 2007. Nucleic Acids Research 35(Database-Issue): 668-673 (2007) |
109 | EE | Daryl J. Thomas, Heather Trumbower, Andrew D. Kern, Brooke L. Rhead, Robert M. Kuhn, David Haussler, W. James Kent: Variation resources at UC Santa Cruz. Nucleic Acids Research 35(Database-Issue): 716-720 (2007) |
2006 | ||
108 | EE | Adam C. Siepel, Katherine S. Pollard, David Haussler: New Methods for Detecting Lineage-Specific Selection. RECOMB 2006: 190-205 |
107 | EE | David Haussler: Ultraconserved Elements, Living Fossil Transposons, and Rapid Bursts of Change: Reconstructing the Uneven Evolutionary History of the Human Genome. RECOMB 2006: 336-337 |
106 | EE | Jeremy Darot, Chen-Hsiang Yeang, David Haussler: Detecting the Dependent Evolution of Biosequences. RECOMB 2006: 595-609 |
105 | EE | Fan Hsu, W. James Kent, Hiram Clawson, Robert M. Kuhn, Mark Diekhans, David Haussler: The UCSC Known Genes. Bioinformatics 22(9): 1036-1046 (2006) |
104 | EE | Jing Wu, David Haussler: Coding Exon Detection Using Comparative Sequences. Journal of Computational Biology 13(6): 1148-1164 (2006) |
103 | EE | Angela S. Hinrichs, Donna Karolchik, Robert Baertsch, Galt P. Barber, Gill Bejerano, Hiram Clawson, Mark Diekhans, Terrence S. Furey, Rachel A. Harte, Fan Hsu, Jennifer Hillman-Jackson, Robert M. Kuhn, J. S. Pedersen, Andy Pohl, Brian J. Raney, Kate R. Rosenbloom, Adam C. Siepel, Kayla E. Smith, Charles W. Sugnet, A. Sultan-Qurraie, Daryl J. Thomas, Heather Trumbower, R. J. Weber, M. Weirauch, Ann S. Zweig, David Haussler, W. James Kent: The UCSC Genome Browser Database: update 2006. Nucleic Acids Research 34(Database-Issue): 590-598 (2006) |
2005 | ||
102 | EE | Rachel Karchin, Mark Diekhans, Libusha Kelly, Daryl J. Thomas, Ursula Pieper, Narayanan Eswar, David Haussler, Andrej Sali: LS-SNP: large-scale annotation of coding non-synonymous SNPs based on multiple information sources. Bioinformatics 21(12): 2814-2820 (2005) |
101 | EE | Fan Hsu, Tom H. Pringle, Robert M. Kuhn, Donna Karolchik, Mark Diekhans, David Haussler, W. James Kent: The UCSC Proteome Browser. Nucleic Acids Research 33(Database-Issue): 454-458 (2005) |
2004 | ||
100 | EE | Vladimir Jojic, Nebojsa Jojic, Christopher Meek, Dan Geiger, Adam C. Siepel, David Haussler, David Heckerman: Efficient approximations for learning phylogenetic HMM models from data. ISMB/ECCB (Supplement of Bioinformatics) 2004: 161-168 |
99 | EE | Gill Bejerano, David Haussler, Mathieu Blanchette: Into the heart of darkness: large-scale clustering of human non-coding DNA. ISMB/ECCB (Supplement of Bioinformatics) 2004: 40-48 |
98 | EE | Charles W. Sugnet, W. James Kent, Manual Ares, David Haussler: Transcriptome and Genome Conservation of Alternative Splicing Events in Humans and Mice. Pacific Symposium on Biocomputing 2004: 66-77 |
97 | EE | Adam C. Siepel, David Haussler: Computational identification of evolutionarily conserved exons. RECOMB 2004: 177-186 |
96 | EE | Krishna M. Roskin, Mark Diekhans, David Haussler: Score Functions for Determining Regional Conservation in Two-Species Local Alignments. Journal of Computational Biology 11(2/3): 395-411 (2004) |
95 | EE | Adam C. Siepel, David Haussler: Combining Phylogenetic and Hidden Markov Models in Biosequence Analysis. Journal of Computational Biology 11(2/3): 413-428 (2004) |
94 | Donna Karolchik, Angela S. Hinrichs, Terrence S. Furey, Krishna M. Roskin, Charles W. Sugnet, David Haussler, W. James Kent: The UCSC Table Browser data retrieval tool. Nucleic Acids Research 32(Database-Issue): 493-496 (2004) | |
2003 | ||
93 | EE | Hui Wang, Earl Hubbell, Jing-Shan Hu, Gangwu Mei, Melissa S. Cline, Gang Lu, Tyson Clark, Michael A. Siani-Rose, Manuel Ares, David Kulp, David Haussler: Gene structure-based splice variant deconvolution using a microarry platform. ISMB (Supplement of Bioinformatics) 2003: 315-322 |
92 | EE | David Haussler: Computational analysis of the human and other mammalian genomes. RECOMB 2003: 138-138 |
91 | EE | Krishna M. Roskin, Mark Diekhans, David Haussler: Scoring two-species local alignments to try to statistically separate neutrally evolving from selected DNA segments. RECOMB 2003: 257-266 |
90 | EE | Adam C. Siepel, David Haussler: Combining phylogenetic and hidden Markov models in biosequence analysis. RECOMB 2003: 277-286 |
89 | Donna Karolchik, Robert Baertsch, Mark Diekhans, Terrence S. Furey, Angela S. Hinrichs, Y. T. Lu, Krishna M. Roskin, M. Schwartz, Charles W. Sugnet, Daryl J. Thomas, R. J. Weber, David Haussler, W. James Kent: The UCSC Genome Browser Database. Nucleic Acids Research 31(1): 51-54 (2003) | |
2002 | ||
88 | Rachel Karchin, Kevin Karplus, David Haussler: Classifying G-protein coupled receptors with support vector machines. Bioinformatics 18(1): 147-159 (2002) | |
2001 | ||
87 | EE | Paul Pavlidis, Terrence S. Furey, M. Liberto, David Haussler, William Noble Grundy: Promoter Region-Based Classification of Genes. Pacific Symposium on Biocomputing 2001: 151-164 |
2000 | ||
86 | Terrence S. Furey, Nello Cristianini, Nigel Duffy, David W. Bednarski, Michèl Schummer, David Haussler: Support vector machine classification and validation of cancer tissue samples using microarray expression data. Bioinformatics 16(10): 906-914 (2000) | |
85 | Tommi Jaakkola, Mark Diekhans, David Haussler: A Discriminative Framework for Detecting Remote Protein Homologies. Journal of Computational Biology 7(1-2): 95-114 (2000) | |
1999 | ||
84 | Tommi Jaakkola, Mark Diekhans, David Haussler: Using the Fisher Kernel Method to Detect Remote Protein Homologies. ISMB 1999: 149-158 | |
83 | EE | Betty Lazareva-Ulitsky, David Haussler: A Probabilistic Approach to a Consensus Multiple Alignment. Pacific Symposium on Biocomputing 1999: 150-161 |
1998 | ||
82 | EE | Tommi Jaakkola, David Haussler: Exploiting Generative Models in Discriminative Classifiers. NIPS 1998: 487-493 |
81 | EE | Nicolò Cesa-Bianchi, David Haussler: A Graph-theoretic Generalization of the Sauer-Shelah Lemma. Discrete Applied Mathematics 86(1): 27-35 (1998) |
80 | David Haussler, Jyrki Kivinen, Manfred K. Warmuth: Sequential Prediction of Individual Sequences Under General Loss Functions. IEEE Transactions on Information Theory 44(5): 1906-1925 (1998) | |
1997 | ||
79 | EE | David Haussler: A Brief Look at Some Machine Learning Problems in Genomics. COLT 1997: 109-113 |
78 | EE | Martin G. Reese, Frank H. Eeckman, David Kulp, David Haussler: Improved splice site detection in Genie. RECOMB 1997: 232-240 |
77 | David Haussler, Manfred Opper: Metric Entropy and Minimax Risk in Classification. Structures in Logic and Computer Science 1997: 212-235 | |
76 | David Haussler: A general minimax result for relative entropy. IEEE Transactions on Information Theory 43(4): 1276-1280 (1997) | |
75 | EE | Nicolò Cesa-Bianchi, Yoav Freund, David Haussler, David P. Helmbold, Robert E. Schapire, Manfred K. Warmuth: How to use expert advice. J. ACM 44(3): 427-485 (1997) |
74 | EE | Noga Alon, Shai Ben-David, Nicolò Cesa-Bianchi, David Haussler: Scale-sensitive dimensions, uniform convergence, and learnability. J. ACM 44(4): 615-631 (1997) |
73 | Martin G. Reese, Frank H. Eeckman, David Kulp, David Haussler: Improved Splice Site Detection in Genie. Journal of Computational Biology 4(3): 311-324 (1997) | |
1996 | ||
72 | David Kulp, David Haussler, Martin G. Reese, Frank H. Eeckman: A Generalized Hidden Markov Model for the Recognition of Human Genes in DNA. ISMB 1996: 134-142 | |
71 | Usama M. Fayyad, David Haussler, Paul E. Stolorz: KDD for Science Data Analysis: Issues and Examples. KDD 1996: 50-56 | |
70 | EE | Usama M. Fayyad, David Haussler, Paul E. Stolorz: Mining Scientific Data. Commun. ACM 39(11): 51-57 (1996) |
69 | Kimmen Sjölander, Kevin Karplus, Michael Brown, Richard Hughey, Anders Krogh, I. Saira Mian, David Haussler: Dirichlet mixtures: a method for improved detection of weak but significant protein sequence homology. Computer Applications in the Biosciences 12(4): 327-345 (1996) | |
68 | David Haussler, Michael J. Kearns, H. Sebastian Seung, Naftali Tishby: Rigorous Learning Curve Bounds from Statistical Mechanics. Machine Learning 25(2-3): 195-236 (1996) | |
1995 | ||
67 | EE | David Haussler, Manfred Opper: General Bounds on the Mutual Information Between a Parameter and n Conditionally Independent Observations. COLT 1995: 402-411 |
66 | David Haussler, Jyrki Kivinen, Manfred K. Warmuth: Tight worst-case loss bounds for predicting with expert advice. EuroCOLT 1995: 69-83 | |
65 | EE | Emanuel Knill, Andrzej Ehrenfeucht, David Haussler: The size of k-pseudotrees. Discrete Mathematics 141(1-3): 185-194 (1995) |
64 | David Haussler: Sphere Packing Numbers for Subsets of the Boolean n-Cube with Bounded Vapnik-Chervonenkis Dimension. J. Comb. Theory, Ser. A 69(2): 217-232 (1995) | |
63 | David Haussler, Philip M. Long: A Generalization of Sauer's Lemma. J. Comb. Theory, Ser. A 71(2): 219-240 (1995) | |
62 | Shai Ben-David, Nicolò Cesa-Bianchi, David Haussler, Philip M. Long: Characterizations of Learnability for Classes of {0, ..., n}-Valued Functions. J. Comput. Syst. Sci. 50(1): 74-86 (1995) | |
1994 | ||
61 | EE | David Haussler, H. Sebastian Seung, Michael J. Kearns, Naftali Tishby: Rigorous Learning Curve Bounds from Statistical Mechanics. COLT 1994: 76-87 |
60 | Yasubumi Sakakibara, Michael Brown, Richard Hughey, I. Saira Mian, Kimmen Sjölander, Rebecca C. Underwood, David Haussler: Recent Methods for RNA Modeling Using Stochastic Context-Free Grammars. CPM 1994: 289-306 | |
59 | Yasubumi Sakakibara, Michael Brown, Rebecca C. Underwood, I. Saira Mian, David Haussler: Stochastic Context-Free Grammars for Modeling RN. HICSS (5) 1994: 284-294 | |
58 | Leslie Grate, Mark Herbster, Richard Hughey, David Haussler, I. Saira Mian, Harry Noller: RNA Modeling Using Gibbs Sampling and Stochastic Context Free Grammars. ISMB 1994: 138-146 | |
57 | Gary D. Stormo, David Haussler: Optimally Parsing a Sequence into Different Classes Based on Multiple Types of Evidence. ISMB 1994: 369-375 | |
56 | David Haussler, Nick Littlestone, Manfred K. Warmuth: Predicting \0,1\-Functions on Randomly Drawn Points Inf. Comput. 115(2): 248-292 (1994) | |
55 | David Haussler, Michael J. Kearns, Robert E. Schapire: Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension. Machine Learning 14(1): 83-113 (1994) | |
1993 | ||
54 | Noga Alon, Shai Ben-David, Nicolò Cesa-Bianchi, David Haussler: Scale-sensitive Dimensions, Uniform Convergence, and Learnability FOCS 1993: 292-301 | |
53 | Michael Brown, Richard Hughey, Anders Krogh, I. Saira Mian, Kimmen Sjölander, David Haussler: Using Dirichlet Mixture Priors to Derive Hidden Markov Models for Protein Families. ISMB 1993: 47-55 | |
52 | EE | Nicolò Cesa-Bianchi, Yoav Freund, David P. Helmbold, David Haussler, Robert E. Schapire, Manfred K. Warmuth: How to use expert advice. STOC 1993: 382-391 |
1992 | ||
51 | David Haussler: Decision Theoretic Generalizations of the PAC Model for Neural Net and Other Learning Applications Inf. Comput. 100(1): 78-150 (1992) | |
1991 | ||
50 | EE | David Haussler, Michael J. Kearns, Robert E. Schapire: Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension. COLT 1991: 61-74 |
49 | EE | Manfred Opper, David Haussler: Calculation of the Learning Curve of Bayes Optimal Classification Algorithm for Learning a Perceptron With Noise. COLT 1991: 75-87 |
48 | EE | David Haussler, Michael J. Kearns, Manfred Opper, Robert E. Schapire: Estimating Average-Case Learning Curves Using Bayesian, Statistical Physics and VC Dimension Methods. NIPS 1991: 855-862 |
47 | EE | Yoav Freund, David Haussler: Unsupervised Learning of Distributions of Binary Vectors Using 2-Layer Networks. NIPS 1991: 912-919 |
46 | David Haussler, Michael J. Kearns, Nick Littlestone, Manfred K. Warmuth: Equivalence of Models for Polynomial Learnability Inf. Comput. 95(2): 129-161 (1991) | |
1990 | ||
45 | David Haussler: Probably Approximately Correct Learning. AAAI 1990: 1101-1108 | |
44 | David Haussler: Decision Theoretic Generalizations of the PAC Learning Model. ALT 1990: 21-41 | |
43 | Giulia Pagallo, David Haussler: Boolean Feature Discovery in Empirical Learning. Machine Learning 5: 71-99 (1990) | |
1989 | ||
42 | EE | Aleksandar Milosavljevic, David Haussler, Jerzy Jurka: Informed Parsimonious Inference of Prototypical Genetic Sequences. COLT 1989: 102-117 |
41 | David Haussler: Generalizing the PAC Model: Sample Size Bounds From Metric Dimension-based Uniform Convergence Results FOCS 1989: 40-45 | |
40 | Giulia Pagallo, David Haussler: Two Algorithms That Learn DNF by Discovering Relevant Features. ML 1989: 119-123 | |
39 | EE | Anselm Blumer, Andrzej Ehrenfeucht, David Haussler: Average sizes of suffix trees and DAWGs. Discrete Applied Mathematics 24(1-3): 37-45 (1989) |
38 | Andrzej Ehrenfeucht, David Haussler: Learning Decision Trees from Random Examples Inf. Comput. 82(3): 231-246 (1989) | |
37 | Andrzej Ehrenfeucht, David Haussler, Michael J. Kearns, Leslie G. Valiant: A General Lower Bound on the Number of Examples Needed for Learning Inf. Comput. 82(3): 247-261 (1989) | |
36 | EE | Anselm Blumer, Andrzej Ehrenfeucht, David Haussler, Manfred K. Warmuth: Learnability and the Vapnik-Chervonenkis dimension. J. ACM 36(4): 929-965 (1989) |
35 | David Haussler: Learning Conjunctive Concepts in Structural Domains. Machine Learning 4: 7-40 (1989) | |
1988 | ||
34 | EE | Andrzej Ehrenfeucht, David Haussler, Michael J. Kearns, Leslie G. Valiant: A General Lower Bound on the Number of Examples Needed for Learning. COLT 1988: 139-154 |
33 | EE | Andrzej Ehrenfeucht, David Haussler: Learning Decision Trees from Random Examples. COLT 1988: 182-194 |
32 | EE | David Haussler, Nick Littlestone, Manfred K. Warmuth: Predicting {0, 1}-Functions on Randomly Drawn Points. COLT 1988: 280-296 |
31 | EE | David Haussler, Michael J. Kearns, Nick Littlestone, Manfred K. Warmuth: Equivalence of Models for Polynomial Learnability. COLT 1988: 42-55 |
30 | David Haussler, Nick Littlestone, Manfred K. Warmuth: Predicting {0,1}-Functions on Randomly Drawn Points (Extended Abstract) FOCS 1988: 100-109 | |
29 | EE | Eric B. Baum, David Haussler: What Size Net Gives Valid Generalization? NIPS 1988: 81-90 |
28 | David Haussler: Quantifying Inductive Bias: AI Learning Algorithms and Valiant's Learning Framework. Artif. Intell. 36(2): 177-221 (1988) | |
27 | EE | Andrzej Ehrenfeucht, David Haussler: A new distance metric on strings computable in linear time. Discrete Applied Mathematics 20(3): 191-203 (1988) |
1987 | ||
26 | David Haussler: Learning Conjunctive Concepts in Structural Domains. AAAI 1987: 466-470 | |
25 | EE | Noga Alon, David Haussler, Emo Welzl: Partitioning and Geometric Embedding of Range Spaces of Finite Vapnik-Chervonenkis Dimension. Symposium on Computational Geometry 1987: 331-340 |
24 | David Haussler, Emo Welzl: epsilon-Nets and Simplex Range Queries. Discrete & Computational Geometry 2: 127-151 (1987) | |
23 | Anselm Blumer, Andrzej Ehrenfeucht, David Haussler, Manfred K. Warmuth: Occam's Razor. Inf. Process. Lett. 24(6): 377-380 (1987) | |
22 | EE | Anselm Blumer, J. Blumer, David Haussler, Ross M. McConnell, Andrzej Ehrenfeucht: Complete inverted files for efficient text retrieval and analysis. J. ACM 34(3): 578-595 (1987) |
21 | David Haussler: New Theoretical Directions in Machine Learning. Machine Learning 2(4): 281-284 (1987) | |
20 | Michael G. Main, Walter Bucher, David Haussler: Applications of an Infinite Square-Free CO-CFL. Theor. Comput. Sci. 49: 113-119 (1987) | |
1986 | ||
19 | David Haussler: Quantifying the Inductive Bias in Concept Learning (Extended Abstract). AAAI 1986: 485-489 | |
18 | Anselm Blumer, Andrzej Ehrenfeucht, David Haussler, Manfred K. Warmuth: Classifying Learnable Geometric Concepts with the Vapnik-Chervonenkis Dimension (Extended Abstract) STOC 1986: 273-282 | |
17 | EE | David Haussler, Emo Welzl: Epsilon-Nets and Simplex Range Queries. Symposium on Computational Geometry 1986: 61-71 |
16 | EE | Herbert Edelsbrunner, David Haussler: The complexity of cells in three-dimensional arrangements. Discrete Mathematics 60: 139-146 (1986) |
15 | B. Clift, David Haussler, Ross M. McConnell, Thomas D. Schneider, Gary D. Stormo: Sequence landscapes. Nucleic Acids Research 14(1): 141-158 (1986) | |
1985 | ||
14 | Michael G. Main, Walter Bucher, David Haussler: Applications of an Infinite Squarefree CO-CFL. ICALP 1985: 404-412 | |
13 | Walter Bucher, Andrzej Ehrenfeucht, David Haussler: On Total Regulators Generated by Derivation Relations. ICALP 1985: 71-79 | |
12 | EE | David Haussler: Another generalization of Higman's well quasi order result on Sigma*. Discrete Mathematics 57(3): 237-243 (1985) |
11 | Walter Bucher, Andrzej Ehrenfeucht, David Haussler: On Total Regulators Generated by Derivation Relations. Theor. Comput. Sci. 40: 131-148 (1985) | |
10 | Anselm Blumer, J. Blumer, David Haussler, Andrzej Ehrenfeucht, M. T. Chen, Joel I. Seiferas: The Smallest Automaton Recognizing the Subwords of a Text. Theor. Comput. Sci. 40: 31-55 (1985) | |
1984 | ||
9 | Anselm Blumer, J. Blumer, Andrzej Ehrenfeucht, David Haussler, Ross M. McConnell: Building the Minimal DFA for the Set of all Subwords of a Word On-line in Linear Time. ICALP 1984: 109-118 | |
8 | Anselm Blumer, J. Blumer, Andrzej Ehrenfeucht, David Haussler, Ross M. McConnell: Building a Complete Inverted File for a Set of Text Files in Linear Time STOC 1984: 349-358 | |
7 | Andrzej Ehrenfeucht, David Haussler, Grzegorz Rozenberg: On Ambiguity in Dos Systems. ITA 18(3): 279-295 (1984) | |
6 | Manfred K. Warmuth, David Haussler: On the Complexity of Iterated Shuffle. J. Comput. Syst. Sci. 28(3): 345-358 (1984) | |
1983 | ||
5 | Anselm Blumer, J. Blumer, Andrzej Ehrenfeucht, David Haussler, Ross M. McConnell: Linear size finite automata for the set of all subwords of a word - an outline of results. Bulletin of the EATCS 21: 12-20 (1983) | |
4 | EE | David Haussler: Insertion languages. Inf. Sci. 31(1): 77-89 (1983) |
3 | Andrzej Ehrenfeucht, David Haussler, Grzegorz Rozenberg: On Regularity of Context-Free Languages. Theor. Comput. Sci. 27: 311-332 (1983) | |
1982 | ||
2 | Andrzej Ehrenfeucht, David Haussler, Grzegorz Rozenberg: Conditions Enforcing Regularity of Context-Free Languages. ICALP 1982: 187-191 | |
1980 | ||
1 | David Haussler, H. Paul Zeiger: Very Special Languages and Representations of Recursively Enumerable Languages via Computation Histories Information and Control 47(3): 201-212 (1980) |