-
1
-
-
0001371923
-
Fast discovery of association rules
-
U.M. Fayyad, G. Piatetski-Shapiro, P. Smyth, and R. Uthurusamy (eds.), AAAI Press
-
R. Agrawal, H. Mannila, R. Srikant, H. Toivonen, and A.I. Verkamo. Fast discovery of association rules. In U.M. Fayyad, G. Piatetski-Shapiro, P. Smyth, and R. Uthurusamy (eds.), Advances in Knowledge Discovery and Data Mining, pp. 307-328. AAAI Press, 1996.
-
(1996)
Advances in Knowledge Discovery and Data Mining
, pp. 307-328
-
-
Agrawal, R.1
Mannila, H.2
Srikant, R.3
Toivonen, H.4
Verkamo, A.I.5
-
2
-
-
0042411541
-
Dynamic logic programming
-
A. Cohn, L. Schubert and S. Shapiro (eds.), Morgan Kaufmann
-
J. J. Alferes, J. A. Leite, L. M. Pereira, H. Przymusinska, and T. C. Przymusinski. Dynamic logic programming, In A. Cohn, L. Schubert and S. Shapiro (eds.), Proceedings of the Sixth International Conference on Principles of Knowledge Representation and Reasoning, pp. 98-109. Morgan Kaufmann, 1998.
-
(1998)
Proceedings of the Sixth International Conference on Principles of Knowledge Representation and Reasoning
, pp. 98-109
-
-
Alferes, J.J.1
Leite, J.A.2
Pereira, L.M.3
Przymusinska, H.4
Przymusinski, T.C.5
-
3
-
-
0000452640
-
Learning conjunctions of Horn clauses
-
D. Angluin, M. Frazier, and L. Pitt. Learning conjunctions of Horn clauses. Machine Learning, 9(2/3): 147-164, 1992.
-
(1992)
Machine Learning
, vol.9
, Issue.2-3
, pp. 147-164
-
-
Angluin, D.1
Frazier, M.2
Pitt, L.3
-
4
-
-
0032069371
-
Top-down induction of first-order logical decision trees
-
June
-
H. Blockeel and L. De Raedt. Top-down induction of first-order logical decision trees. Artificial Intelligence 101(1-2): 285-297, June 1998.
-
(1998)
Artificial Intelligence
, vol.101
, Issue.1-2
, pp. 285-297
-
-
Blockeel, H.1
De Raedt, L.2
-
5
-
-
22644449312
-
Scaling up inductive logic programming by learning from interpretations
-
H. Blockeel, L. De Raedt, N. Jacobs, and B. Demoen. Scaling up inductive logic programming by learning from interpretations. Data Mining and Knowledge Discovery, 3(1): 59-93, 1999.
-
(1999)
Data Mining and Knowledge Discovery
, vol.3
, Issue.1
, pp. 59-93
-
-
Blockeel, H.1
De Raedt, L.2
Jacobs, N.3
Demoen, B.4
-
6
-
-
84954410691
-
Executing query packs in ILP
-
J. Cussens and A. Frisch (eds.), Lecture Notes in Artificial Intelligence. Springer-Verlag
-
H. Blockeel, L. Dehaspe, B. Demoen, G. Janssens, J. Ramon, and H. Vandecasteele. Executing query packs in ILP. In J. Cussens and A. Frisch (eds.), Proceedings of the Tenth International Conference on Inductive Logic Programming, Lecture Notes in Artificial Intelligence 1866, pp. 60-77. Springer-Verlag, 2000.
-
(2000)
Proceedings of the Tenth International Conference on Inductive Logic Programming
, vol.1866
, pp. 60-77
-
-
Blockeel, H.1
Dehaspe, L.2
Demoen, B.3
Janssens, G.4
Ramon, J.5
Vandecasteele, H.6
-
7
-
-
0347273047
-
Classification of individuals with complex structure
-
P. Langley (ed.), Morgan Kaufmann
-
A.F. Bowers, C. Giraud-Carrier, and J.W. Lloyd. Classification of individuals with complex structure. In P. Langley (ed.), Proceedings of the Seventeenth International Conference on Machine Learning, pp. 81-88. Morgan Kaufmann, 2000.
-
(2000)
Proceedings of the Seventeenth International Conference on Machine Learning
, pp. 81-88
-
-
Bowers, A.F.1
Giraud-Carrier, C.2
Lloyd, J.W.3
-
8
-
-
0029407394
-
Applications of inductive logic programming
-
November
-
I. Bratko and S. Muggleton. Applications of Inductive Logic Programming. Communications of the ACM 38(11): 65-70, November 1995.
-
(1995)
Communications of the ACM
, vol.38
, Issue.11
, pp. 65-70
-
-
Bratko, I.1
Muggleton, S.2
-
9
-
-
0030211964
-
Bagging predictors
-
L. Breiman. Bagging predictors. Machine Learning 24(2): 123-140, 1996.
-
(1996)
Machine Learning
, vol.24
, Issue.2
, pp. 123-140
-
-
Breiman, L.1
-
10
-
-
0029678885
-
Well-founded semantics for extended logic programs with dynamic preferences
-
G. Brewka. Well-founded semantics for extended logic programs with dynamic preferences. Journal of Artificial Intelligence Research, 4: 19-36, 1996.
-
(1996)
Journal of Artificial Intelligence Research
, vol.4
, pp. 19-36
-
-
Brewka, G.1
-
13
-
-
0002181874
-
Learning the CLASSIC description logic: Theoretical and experimental results
-
J. Doyle, E. Sandewall, and P. Torasso (eds.), Morgan Kaufmann
-
W.W. Cohen and H. Hirsh. Learning the CLASSIC Description Logic: Theoretical and Experimental Results. In J. Doyle, E. Sandewall, and P. Torasso (eds.), Proceedings of the Fourth International Conference on Principles of Knowledge Representation and Reasoning, pp. 121-133. Morgan Kaufmann, 1994.
-
(1994)
Proceedings of the Fourth International Conference on Principles of Knowledge Representation and Reasoning
, pp. 121-133
-
-
Cohen, W.W.1
Hirsh, H.2
-
15
-
-
15544363860
-
-
Lecture Notes in Artificial Intelligence Springer-Verlag
-
J. Cussens and S. Džeroski (eds.). Learning Language in Logic. Lecture Notes in Artificial Intelligence 1925, Springer-Verlag, 2000.
-
(2000)
Learning Language in Logic
, vol.1925
-
-
Cussens, J.1
Džeroski, S.2
-
16
-
-
84957890121
-
Mining association rules in multiple relations
-
S. Džeroski and N. Lavrač (eds.), Lecture Notes in Artificial Intelligence. Springer-Verlag
-
L. Dehaspe and L. De Raedt. Mining association rules in multiple relations. In S. Džeroski and N. Lavrač (eds.), Proceedings of the Seventh International Workshop on Inductive Logic Programming, Lecture Notes in Artificial Intelligence 1297, pp. 125-132. Springer-Verlag, 1997.
-
(1997)
Proceedings of the Seventh International Workshop on Inductive Logic Programming
, vol.1297
, pp. 125-132
-
-
Dehaspe, L.1
De Raedt, L.2
-
17
-
-
84880088183
-
Finding frequent substructures in chemical compounds
-
R. Agrawal, P. Stolorz, and G. Piatetsky-Shapiro (eds.), AAAI Press
-
L. Dehaspe, H. Toivonen, and R.D. King. Finding frequent substructures in chemical compounds. In R. Agrawal, P. Stolorz, and G. Piatetsky-Shapiro (eds.), Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, pp. 30-36. AAAI Press, 1998.
-
(1998)
Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining
, pp. 30-36
-
-
Dehaspe, L.1
Toivonen, H.2
King, R.D.3
-
19
-
-
0031198976
-
Logical settings for concept-learning
-
L. De Raedt. Logical settings for concept-learning. Artificial Intelligence, 95(1): 187-201, 1997.
-
(1997)
Artificial Intelligence
, vol.95
, Issue.1
, pp. 187-201
-
-
De Raedt, L.1
-
20
-
-
84957894351
-
Using logical decision trees for clustering
-
N. Lavrač and S. Džeroski (eds.), Lecture Notes in Artificial Intelligence, Springer-Verlag
-
L. De Raedt and H. Blockeel. Using logical decision trees for clustering. In N. Lavrač and S. Džeroski (eds.), Proceedings of the Seventh International Workshop on Inductive Logic Programming, Lecture Notes in Artificial Intelligence 1297, pp. 133-140. Springer-Verlag, 1997.
-
(1997)
Proceedings of the Seventh International Workshop on Inductive Logic Programming
, vol.1297
, pp. 133-140
-
-
De Raedt, L.1
Blockeel, H.2
-
22
-
-
79955672163
-
An inductive logic programming query language for database mining (extended abstract)
-
J. Calmet and J. Plaza (eds.), Lecture Notes in Artificial Intelligence. Springer-Verlag
-
L. De Raedt. An inductive logic programming query language for database mining (extended abstract). In J. Calmet and J. Plaza (eds.), Proceedings of the Fourth Workshop on Artificial Intelligence and Symbolic Computation, Lecture Notes in Artificial Intelligence 1476. Springer-Verlag, 1998.
-
(1998)
Proceedings of the Fourth Workshop on Artificial Intelligence and Symbolic Computation
, vol.1476
-
-
De Raedt, L.1
-
23
-
-
33747885154
-
A perspective on inductive logic programming
-
K. Apt, V. Marek, M. Truszezynski, and D.S.Warren (eds.), Springer-Verlag
-
L. De Raedt. A perspective on inductive logic programming. In K. Apt, V. Marek, M. Truszezynski, and D.S.Warren (eds.), The logic programming paradigm: current trends and future directions. Springer-Verlag, 1999.
-
(1999)
The Logic Programming Paradigm: Current Trends and Future Directions
-
-
De Raedt, L.1
-
24
-
-
84954451051
-
A logical database mining query language
-
J. Cussens and A. Frisch, Lecture Notes in Artificial Intelligence. Springer-Verlag
-
L. De Raedt. A logical database mining query language. In J. Cussens and A. Frisch, Proceedings of the Tenth International Conference on Inductive Logic Programming, Lecture Notes in Artificial Intelligence 1866, pp. 78-92. Springer-Verlag, 2000.
-
(2000)
Proceedings of the Tenth International Conference on Inductive Logic Programming
, vol.1866
, pp. 78-92
-
-
De Raedt, L.1
-
25
-
-
84948980648
-
Learning non-monotonic logic programs: Learning exceptions
-
N. Lavrač and S. Wrobel (eds.), Lecture Notes in Artificial Intelligence, Springer-Verlag
-
Y. Dimopoulos and A.C. Kakas. Learning non-monotonic logic programs: learning exceptions. In N. Lavrač and S. Wrobel (eds.), Proceedings of the Eighth European Conference on Machine Learning, Lecture Notes in Artificial Intelligence 912, pp. 122-138. Springer-Verlag, 1995.
-
(1995)
Proceedings of the Eighth European Conference on Machine Learning
, vol.912
, pp. 122-138
-
-
Dimopoulos, Y.1
Kakas, A.C.2
-
27
-
-
84880658927
-
Integrating explanatory and descriptive induction in ILP
-
M.E. Pollack (ed.), Morgan Kaufmann
-
Y. Dimopoulos, S. Džeroski, and A.C. Kakas. Integrating Explanatory and Descriptive Induction in ILP. In M.E. Pollack (ed.), Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, pp. 900-907. Morgan Kaufmann, 1997.
-
(1997)
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence
, pp. 900-907
-
-
Dimopoulos, Y.1
Džeroski, S.2
Kakas, A.C.3
-
31
-
-
0242445843
-
Relational reinforcement learning
-
J. Shavlik (ed.), Morgan Kaufmann
-
S. Džeroski, L. De Raedt, and H. Blockeel. Relational reinforcement learning. In J. Shavlik (ed.), Proceedings of the Fifteenth International Conference on Machine Learning, pp. 136-143. Morgan Kaufmann, 1998.
-
(1998)
Proceedings of the Fifteenth International Conference on Machine Learning
, pp. 136-143
-
-
Džeroski, S.1
De Raedt, L.2
Blockeel, H.3
-
33
-
-
85027406031
-
Learning of characteristic concept descriptions from small sets to classified examples
-
F. Bergadano and L. De Raedt (eds.). Lecture Notes in Artificial Intelligence, Springer-Verlag
-
W. Emde. Learning of characteristic concept descriptions from small sets to classified examples. In F. Bergadano and L. De Raedt (eds.), Proceedings of the Seventh European Conference on Machine Learning, Lecture Notes in Artificial Intelligence 784, pp. 103-121. Springer-Verlag, 1994.
-
(1994)
Proceedings of the Seventh European Conference on Machine Learning
, vol.784
, pp. 103-121
-
-
Emde, W.1
-
35
-
-
85028883412
-
Predicate invention in inductive data engineering
-
P. Brazdil (ed.), Lecture Notes in Artificial Intelligence, Springer-Verlag
-
P.A. Flach. Predicate invention in inductive data engineering. In P. Brazdil (ed.), Proceedings of the Sixth European Conference on Machine Learning, Lecture Notes in Artificial Intelligence 667, pp. 83-94. Springer-Verlag, 1993.
-
(1993)
Proceedings of the Sixth European Conference on Machine Learning
, vol.667
, pp. 83-94
-
-
Flach, P.A.1
-
39
-
-
84874506655
-
Normal forms for inductive logic programming
-
N. Lavrač and S. Džeroski (eds.), Lecture Notes in Artificial Intelligence. Springer-Verlag
-
P.A. Flach. Normal forms for Inductive Logic Programming. In N. Lavrač and S. Džeroski (eds.), Proceedings of the Seventh International Workshop on Inductive Logic Programming, Lecture Notes in Artificial Intelligence 1297, pp. 149-156. Springer-Verlag, 1997.
-
(1997)
Proceedings of the Seventh International Workshop on Inductive Logic Programming
, vol.1297
, pp. 149-156
-
-
Flach, P.A.1
-
40
-
-
84874455572
-
Strongly typed inductive concept learning
-
D. Page (ed.), Lecture Notes in Artificial Intelligence. Springer-Verlag
-
P.A. Flach, C. Giraud-Carrier, and J.W. Lloyd. Strongly typed inductive concept learning. In D. Page (ed.), Proceedings of the Eighth International Conference on Inductive Logic Programming, Lecture Notes in Artificial Intelligence 1446, pp. 185-194. Springer-Verlag, 1998.
-
(1998)
Proceedings of the Eighth International Conference on Inductive Logic Programming
, vol.1446
, pp. 185-194
-
-
Flach, P.A.1
Giraud-Carrier, C.2
Lloyd, J.W.3
-
41
-
-
0033350089
-
Database dependency discovery: A machine learning approach
-
November
-
P.A. Flach and I. Savnik. Database dependency discovery: a machine learning approach. AI Communications, 12(3): 139-160, November 1999.
-
(1999)
AI Communications
, vol.12
, Issue.3
, pp. 139-160
-
-
Flach, P.A.1
Savnik, I.2
-
42
-
-
84949227828
-
1BC: A first-order Bayesian classifier
-
S. Džeroski and P.A. Flach (eds.), Lecture Notes in Artificial Intelligence, Springer-Verlag
-
P.A. Flach and N. Lachiche. 1BC: A first-order Bayesian classifier. In S. Džeroski and P.A. Flach (eds.), Proceedings of the Ninth International Workshop on Inductive Logic Programming, Lecture Notes in Artificial Intelligence 1634, pp. 92-103. Springer-Verlag, 1999.
-
(1999)
Proceedings of the Ninth International Workshop on Inductive Logic Programming
, vol.1634
, pp. 92-103
-
-
Flach, P.A.1
Lachiche, N.2
-
44
-
-
0034832530
-
Confirmation-guided discovery of first-order rules with Tertius
-
P.A. Flach and N. Lachiche. Confirmation-guided discovery of first-order rules with Tertius. Machine Learning, 42(1/2): 61-95, 2001.
-
(2001)
Machine Learning
, vol.42
, Issue.1-2
, pp. 61-95
-
-
Flach, P.A.1
Lachiche, N.2
-
48
-
-
0031069041
-
Learning qualitative models of dynamic systems
-
D.T. Hau and E.W. Coiera. Learning qualitative models of dynamic systems. Machine Learning, 26(2/3): 177-212, 1997.
-
(1997)
Machine Learning
, vol.26
, Issue.2-3
, pp. 177-212
-
-
Hau, D.T.1
Coiera, E.W.2
-
49
-
-
0013387647
-
Induction as nonmonotonic inference
-
R.J. Brachman, H.J. Levesque, and R. Reiter (eds.), Morgan Kaufmann
-
N. Helft. Induction as nonmonotonic inference. In R.J. Brachman, H.J. Levesque, and R. Reiter (eds.), Proceedings of the First International Conference on Principles of Knowledge Representation and Reasoning, pp. 149-156. Morgan Kaufmann, 1989.
-
(1989)
Proceedings of the First International Conference on Principles of Knowledge Representation and Reasoning
, pp. 149-156
-
-
Helft, N.1
-
52
-
-
84957894431
-
Learning with abduction
-
S. Džeroski and N. Lavrač (eds.), Lecture Notes in Artificial Intelligence, Springer-Verlag
-
A.C. Kakas and F. Riguzzi. Learning with abduction. In S. Džeroski and N. Lavrač (eds.), Proceedings of the Seventh International Workshop on Inductive Logic Programming, Lecture Notes in Artificial Intelligence 1297, pp. 181-188. Springer-Verlag, 1997.
-
(1997)
Proceedings of the Seventh International Workshop on Inductive Logic Programming
, vol.1297
, pp. 181-188
-
-
Kakas, A.C.1
Riguzzi, F.2
-
53
-
-
0031074323
-
First-order regression
-
A. Karalič and I. Bratko. First-order regression. Machine Learning, 26(2/3): 147-176, 1997.
-
(1997)
Machine Learning
, vol.26
, Issue.2-3
, pp. 147-176
-
-
Karalič, A.1
Bratko, I.2
-
55
-
-
0026459988
-
Drug design by machine learning: The use of inductive logic programming to model the structure-activity relationships of trimethoprim analogues binding to dihydrofolate reductase
-
R.D. King, S. Muggleton, R. Lewis, and M.J.E. Sternberg. Drug design by machine learning: The use of inductive logic programming to model the structure-activity relationships of trimethoprim analogues binding to dihydrofolate reductase. In Proceedings of the National Academy of Sciences of the USA 89(23): 11322-11326, 1992.
-
(1992)
Proceedings of the National Academy of Sciences of the USA
, vol.89
, Issue.23
, pp. 11322-11326
-
-
King, R.D.1
Muggleton, S.2
Lewis, R.3
Sternberg, M.J.E.4
-
56
-
-
0034592764
-
Genome scale prediction of protein functional class from sequence using data mining
-
ACM Press, New York
-
R.D. King, A. Karwath, A. Clare, and L. Dehaspe. Genome scale prediction of protein functional class from sequence using data mining. In Proceedings of the Sixth International Conference on Knowledge Discovery and Data Mining, pp. 384-398. ACM Press, New York, 2000.
-
(2000)
Proceedings of the Sixth International Conference on Knowledge Discovery and Data Mining
, pp. 384-398
-
-
King, R.D.1
Karwath, A.2
Clare, A.3
Dehaspe, L.4
-
57
-
-
0000875752
-
Accurate prediction of protein functional class in the M.tuberculosis and E.coli genomes using data mining
-
R.D. King, A. Karwath, A. Clare, and L. Dehaspe. Accurate prediction of protein functional class in the M.tuberculosis and E.coli genomes using data mining. Yeast (Comparative and Functional Genomics, 17: 283-293, 2000.
-
(2000)
Yeast (Comparative and Functional Genomics
, vol.17
, pp. 283-293
-
-
King, R.D.1
Karwath, A.2
Clare, A.3
Dehaspe, L.4
-
60
-
-
84867654629
-
Agents learning in a three-valued logical setting
-
A. Panayiotopoulos (ed.), in conjunction with Machine Learning and Applications, Advanced Course on Artificial Intelligence (ACAI-99), Chania, Greece
-
E. Lamma, F. Riguzzi, and L. M. Pereira. Agents learning in a three-valued logical setting. In A. Panayiotopoulos (ed.), Proceedings of the Workshop on Machine Learning and Intelligent Agents, in conjunction with Machine Learning and Applications, Advanced Course on Artificial Intelligence (ACAI-99), Chania, Greece, 1999.
-
(1999)
Proceedings of the Workshop on Machine Learning and Intelligent Agents
-
-
Lamma, E.1
Riguzzi, F.2
Pereira, L.M.3
-
61
-
-
0033906996
-
Strategies in combined learning via logic programs
-
E. Lamma, F. Riguzzi, and L. M. Pereira. Strategies in combined learning via Logic Programs. Machine Learning, 38(1/2): 63-87, 2000.
-
(2000)
Machine Learning
, vol.38
, Issue.1-2
, pp. 63-87
-
-
Lamma, E.1
Riguzzi, F.2
Pereira, L.M.3
-
62
-
-
84950502571
-
Learning nonrecursive definitions of relations with LINUS
-
Y. Kodratoff (ed.), Lecture Notes in Artificial Intelligence. Springer-Verlag
-
N. Lavrač, S. Džeroski, and M. Grobelnik. Learning nonrecursive definitions of relations with LINUS. In Y. Kodratoff (ed.) Proceedings of the Fifth European Working Session on Learning, Lecture Notes in Artificial Intelligence 482, pp. 265-281. Springer-Verlag, 1991.
-
(1991)
Proceedings of the Fifth European Working Session on Learning
, vol.482
, pp. 265-281
-
-
Lavrač, N.1
Džeroski, S.2
Grobelnik, M.3
-
65
-
-
85008021624
-
An extended transformation approach to inductive logic programming
-
N. Lavrač and P.A. Flach. An extended transformation approach to Inductive Logic Programming. ACM Transactions on Computational Logic, 2(4): 458-494, 2001.
-
(2001)
ACM Transactions on Computational Logic
, vol.2
, Issue.4
, pp. 458-494
-
-
Lavrač, N.1
Flach, P.A.2
-
67
-
-
0013157568
-
Programming in an integrated functional and logic programming language
-
J.W. Lloyd. Programming in an integrated functional and logic programming language. Journal of Functional and Logic Programming, 1999(3).
-
(1999)
Journal of Functional and Logic Programming
, Issue.3
-
-
Lloyd, J.W.1
-
68
-
-
1642589871
-
Proof procedures for logic programming
-
D.M. Gabbay, C.J. Hogger, and J.A. Robinson (eds.), Oxford University Press
-
D.W. Loveland and G. Nadathur. Proof procedures for logic programming. Handbook of Logic in Artificial Intelligence and Logic Programming, Vol. 5, D.M. Gabbay, C.J. Hogger, and J.A. Robinson (eds.), Oxford University Press, pp. 163-234, 1998.
-
(1998)
Handbook of Logic in Artificial Intelligence and Logic Programming
, vol.5
, pp. 163-234
-
-
Loveland, D.W.1
Nadathur, G.2
-
69
-
-
2442612280
-
To the international computing community: A new East-West challenge
-
Oxford,UK
-
D. Michie, S. Muggleton, D. Page, and A. Srinivasan. To the international computing community: A new East-West challenge. Technical report, Oxford University Computing laboratory, Oxford,UK, 1994.
-
(1994)
Technical Report, Oxford University Computing Laboratory
-
-
Michie, D.1
Muggleton, S.2
Page, D.3
Srinivasan, A.4
-
71
-
-
0031235612
-
Does machine learning really work?
-
T.M. Mitchell. Does machine learning really work? AI Magazine 18 (3): 11-20, 1997.
-
(1997)
AI Magazine
, vol.18
, Issue.3
, pp. 11-20
-
-
Mitchell, T.M.1
-
72
-
-
0345500652
-
Using inductive logic programming to learn classification rules that identify glaucomatous eyes
-
N. Lavrač, E. Keravnou, and B. Zupan (eds.), Kluwer
-
F. Mizoguchi, H. Ohwada, M. Daidoji, and S. Shirato. Using inductive logic programming to learn classification rules that identify glaucomatous eyes. In N. Lavrač, E. Keravnou, and B. Zupan (eds.), Intelligent Data Analysis in Medicine and Pharmacology, pp. 227-242. Kluwer, 1997.
-
(1997)
Intelligent Data Analysis in Medicine and Pharmacology
, pp. 227-242
-
-
Mizoguchi, F.1
Ohwada, H.2
Daidoji, M.3
Shirato, S.4
-
73
-
-
0001868096
-
Induction of first-order decision lists: Results on learning the past tense of English verbs
-
R.J. Mooney and M.E. Califf. Induction of first-order decision lists: Results on learning the past tense of English verbs. Journal of Artificial Intelligence Research 3: 1-24, 1995.
-
(1995)
Journal of Artificial Intelligence Research
, vol.3
, pp. 1-24
-
-
Mooney, R.J.1
Califf, M.E.2
-
74
-
-
48849099371
-
Learning of qualitative models
-
I. Bratko and N. Lavrač (eds.), Sigma Press
-
I. Mozetič. Learning of qualitative models. In I. Bratko and N. Lavrač (eds.) Progress in Machine Learning, pp. 201-217. Sigma Press, 1987.
-
(1987)
Progress in Machine Learning
, pp. 201-217
-
-
Mozetič, I.1
-
75
-
-
0000640432
-
Inductive logic programming
-
Also in [76], pp. 3-27
-
S. Muggleton. Inductive Logic Programming. New Generation Computing, 8(4): 295-317, 1991. Also in [76], pp. 3-27.
-
(1991)
New Generation Computing
, vol.8
, Issue.4
, pp. 295-317
-
-
Muggleton, S.1
-
79
-
-
0028429573
-
Inductive logic programming: Theory and methods
-
S.Muggleton and L. De Raedt. Inductive Logic Programming: theory and methods. Journal of Logic Programming, 19/20: 629-679, 1994.
-
(1994)
Journal of Logic Programming
, vol.19-20
, pp. 629-679
-
-
Muggleton, S.1
De Raedt, L.2
-
80
-
-
77951503082
-
Inverse entailment and progol
-
S. Muggleton. Inverse entailment and Progol. New Generation Computing, 13: 245-286, 1995.
-
(1995)
New Generation Computing
, vol.13
, pp. 245-286
-
-
Muggleton, S.1
-
81
-
-
84867632330
-
-
C. Nédellec, C. Rouveirol, H. Adé, F. Bergadano, and B. Tausend. Declarative bias in Inductive Logic Programming. In [18], pp. 82-103.
-
Declarative Bias in Inductive Logic Programming.
, Issue.18
, pp. 82-103
-
-
Nédellec, C.1
Rouveirol, C.2
Adé, H.3
Bergadano, F.4
Tausend, B.5
-
82
-
-
84867804745
-
ILP: Just do it
-
J.W. Lloyd (ed.), Lecture Notes in Artificial Intelligence. Springer-Verlag
-
D. Page. ILP: Just do it. In J.W. Lloyd (ed.), Proceedings of the First International Conference on Computational Logic, Lecture Notes in Artificial Intelligence 1861, pp. 25-40. Springer-Verlag, 2000.
-
(2000)
Proceedings of the First International Conference on Computational Logic
, vol.1861
, pp. 25-40
-
-
Page, D.1
-
83
-
-
0001602577
-
A note on inductive generalisation
-
B. Meltzer and D. Michie (eds.). North-Holland
-
G. Plotkin. A note on inductive generalisation. Machine Intelligence 5, B. Meltzer and D. Michie (eds.), pp. 153-163. North-Holland, 1970.
-
(1970)
Machine Intelligence
, vol.5
, pp. 153-163
-
-
Plotkin, G.1
-
84
-
-
0003203117
-
A further note on inductive generalisation
-
B. Meltzer and D. Michie (eds.). North-Holland
-
G. Plotkin. A further note on inductive generalisation. Machine Intelligence 6, B. Meltzer and D. Michie (eds.), pp. 101-124. North-Holland, 1971.
-
(1971)
Machine Intelligence
, vol.6
, pp. 101-124
-
-
Plotkin, G.1
-
85
-
-
0035283313
-
Robust classification for imprecise environments
-
F. Provost and T. Fawcett. Robust classification for imprecise environments. Machine Learning 42(3): 203-231, 2001.
-
(2001)
Machine Learning
, vol.42
, Issue.3
, pp. 203-231
-
-
Provost, F.1
Fawcett, T.2
-
86
-
-
0001172265
-
Learning logical definitions from relations
-
J.R. Quinlan. Learning logical definitions from relations. Machine Learning, 5(3): 239-266, 1990.
-
(1990)
Machine Learning
, vol.5
, Issue.3
, pp. 239-266
-
-
Quinlan, J.R.1
-
88
-
-
0012171475
-
Discovery of multivalued dependencies from relations
-
I. Savnik and P.A. Flach. Discovery of multivalued dependencies from relations. Intelligent Data Analysis, 4(3,4): 195-211, 2000.
-
(2000)
Intelligent Data Analysis
, vol.4
, Issue.3-4
, pp. 195-211
-
-
Savnik, I.1
Flach, P.A.2
-
93
-
-
0342280994
-
Mutagenesis: ILP experiments in a non-determinate biological domain
-
S. Wrobel (ed.), GMD-Studien 237
-
A. Srinivasan, S. Muggleton, R.D. King, and M.J.E. Sternberg. Mutagenesis: ILP experiments in a non-determinate biological domain. In S. Wrobel (ed.), Proceedings of the Fourth International Workshop on Inductive Logic Programming, GMD-Studien 237, pp. 217-232, 1994.
-
(1994)
Proceedings of the Fourth International Workshop on Inductive Logic Programming
, pp. 217-232
-
-
Srinivasan, A.1
Muggleton, S.2
King, R.D.3
Sternberg, M.J.E.4
-
94
-
-
0007654173
-
Carcinogenesis prediction using inductive logic programming
-
N. Lavrač, E. Keravnou, and B. Zupan (eds.), Kluwer
-
A. Srinivasan, R.D. King, S. Muggleton, and M.J.E. Sternberg. Carcinogenesis prediction using inductive logic programming. In N. Lavrač, E. Keravnou, and B. Zupan (eds.), Intelligent Data Analysis in Medicine and Pharmacology, pp. 243-260. Kluwer, 1997.
-
(1997)
Intelligent Data Analysis in Medicine and Pharmacology
, pp. 243-260
-
-
Srinivasan, A.1
King, R.D.2
Muggleton, S.3
Sternberg, M.J.E.4
-
96
-
-
0021518106
-
A theory of the learnable
-
L. Valiant. A theory of the learnable. Communications of the ACM 27: 1134-1142, 1984.
-
(1984)
Communications of the ACM
, vol.27
, pp. 1134-1142
-
-
Valiant, L.1
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