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Note: Links lead to the DBLP on the Web. Sally A. Goldman Yan Zhou , Sally A. Goldman: Democratic Co-Learning. ICTAI 2004 : 594-602 Sally A. Goldman, Stephen D. Scott : Multiple-Instance Learning of Real-Valued Geometric Patterns. Ann. Math. Artif. Intell. 39 (3): 259-290 (2003) Sally A. Goldman, Stephen Kwek , Stephen D. Scott : Learning from examples with unspecified attribute values. Inf. Comput. 180 (2): 82-100 (2003) Qi Zhang , Sally A. Goldman, Wei Yu , Jason Fritts : Content-Based Image Retrieval Using Multiple-Instance Learning. ICML 2002 : 682-689 Sally A. Goldman: Special Issue on COLT 2000 - Guest Editor's Foreword. J. Comput. Syst. Sci. 64 (1): 1 (2002) Daniel R. Dooly , Qi Zhang , Sally A. Goldman, Robert A. Amar : Multiple-Instance Learning of Real-Valued Data. Journal of Machine Learning Research 3 : 651-678 (2002) Sally A. Goldman, Stephen Kwek : On learning unions of pattern languages and tree patterns in the mistake bound model. Theor. Comput. Sci. 288 (2): 237-254 (2002) Daniel R. Dooly , Sally A. Goldman, Stephen Kwek : Real-Valued Multiple-Instance Learning with Queries. ALT 2001 : 167-180 Robert A. Amar , Daniel R. Dooly , Sally A. Goldman, Qi Zhang : Multiple-Instance Learning of Real-Valued Data. ICML 2001 : 3-10 Qi Zhang , Sally A. Goldman: EM-DD: An Improved Multiple-Instance Learning Technique. NIPS 2001 : 1073-1080 Daniel R. Dooly , Sally A. Goldman, Stephen D. Scott : On-line analysis of the TCP acknowledgment delay problem. J. ACM 48 (2): 243-273 (2001) Sally A. Goldman, Stephen Kwek , Stephen D. Scott : Agnostic Learning of Geometric Patterns. J. Comput. Syst. Sci. 62 (1): 123-151 (2001) Nicolò Cesa-Bianchi , Sally A. Goldman: Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28 - July 1, 2000, Palo Alto, California Morgan Kaufmann 2000 Sally A. Goldman, Yan Zhou : Enhancing Supervised Learning with Unlabeled Data. ICML 2000 : 327-334 Sally A. Goldman, Jyoti Parwatikar , Subhash Suri : Online Scheduling with Hard Deadlines. J. Algorithms 34 (2): 370-389 (2000) Sally A. Goldman, Stephen Kwek : On Learning Unions of Pattern Languages and Tree Patterns. ATL 1999 : 347-363 Sally A. Goldman, Stephen D. Scott : A Theoretical and Empirical Study of a Noise-Tolerant Algorithm to Learn Geometric Patterns. Machine Learning 37 (1): 5-49 (1999) Daniel R. Dooly , Sally A. Goldman, Stephen D. Scott : TCP Dynamic Acknowledgment Delay: Theory and Practice (Extended Abstract). STOC 1998 : 389-398 Nader H. Bshouty , Sally A. Goldman, H. David Mathias : Noise-Tolerant Parallel Learning of Geometric Concepts. Inf. Comput. 147 (1): 89-110 (1998) Nader H. Bshouty , Sally A. Goldman, H. David Mathias , Subhash Suri , Hisao Tamaki : Noise-Tolerant Distribution-Free Learning of General Geometric Concepts. J. ACM 45 (5): 863-890 (1998) Avrim Blum , Prasad Chalasani , Sally A. Goldman, Donna K. Slonim : Learning with Unreliable Boundary Queries. J. Comput. Syst. Sci. 56 (2): 209-222 (1998) Nader H. Bshouty , Paul W. Goldberg , Sally A. Goldman, H. David Mathias : Exact Learning of Discretized Geometric Concepts. SIAM J. Comput. 28 (2): 674-699 (1998) Sally A. Goldman, Stephen Kwek , Stephen D. Scott : Learning from Examples with Unspecified Attribute Values (Extended Abstract). COLT 1997 : 231-242 Sally A. Goldman, Stephen Kwek , Stephen D. Scott : Agnostic Learning of Geometric Patterns (Extended Abstract). COLT 1997 : 325-333 Sally A. Goldman, Jyoti Parwatikar , Subhash Suri : On-line Scheduling with Hard Deadlines (Extended Abstract). WADS 1997 : 258-271 Sally A. Goldman, Stephen D. Scott : A Theoretical and Empirical Study of a Noise-Tolerant Algorithm to Learn Geormetric Patterns. ICML 1996 : 191-199 Nader H. Bshouty , Sally A. Goldman, H. David Mathias , Subhash Suri , Hisao Tamaki : Noise-Tolerant Distribution-Free Learning of General Geometric Concepts. STOC 1996 : 151-160 Sally A. Goldman, H. David Mathias : Teaching a Smarter Learner. J. Comput. Syst. Sci. 52 (2): 255-267 (1996) Nader H. Bshouty , Sally A. Goldman, Thomas R. Hancock , Sleiman Matar : Asking Questions to Minimize Errors. J. Comput. Syst. Sci. 52 (2): 268-286 (1996) Michael Frazier , Sally A. Goldman, Nina Mishra , Leonard Pitt : Learning from a Consistently Ignorant Teacher. J. Comput. Syst. Sci. 52 (3): 471-492 (1996) Paul W. Goldberg , Sally A. Goldman, Stephen D. Scott : PAC Learning of One-Dimensional Patterns. Machine Learning 25 (1): 51-70 (1996) Nader H. Bshouty , Sally A. Goldman, H. David Mathias : Noise-Tolerant Parallel Learning of Geometric Concepts. COLT 1995 : 345-352 Avrim Blum , Prasad Chalasani , Sally A. Goldman, Donna K. Slonim : Learning with Unreliable Boundary Queries. COLT 1995 : 98-107 Sally A. Goldman, Robert H. Sloan : Can PAC Learning Algorithms Tolerate Random Attribute Noise? Algorithmica 14 (1): 70-84 (1995) Sally A. Goldman, Michael J. Kearns , Robert E. Schapire : On the Sample Complexity of Weakly Learning Inf. Comput. 117 (2): 276-287 (1995) Sally A. Goldman, Michael J. Kearns : On the Complexity of Teaching. J. Comput. Syst. Sci. 50 (1): 20-31 (1995) Sally A. Goldman: Guest Editor's Introduction. Machine Learning 18 (2-3): 127-129 (1995) Sally A. Goldman, Manfred K. Warmuth : Learning Binary Relations Using Weighted Majority Voting. Machine Learning 20 (3): 245-271 (1995) Paul W. Goldberg , Sally A. Goldman, H. David Mathias : Learning Unions of Boxes with Membership and Equivalence Queries. COLT 1994 : 198-207 Paul W. Goldberg , Sally A. Goldman: Learning One-Dimensional Geometric Patterns Under One-Sided Random Misclassification Noise. COLT 1994 : 246-255 Michael Frazier , Sally A. Goldman, Nina Mishra , Leonard Pitt : Learning from a Consistently Ignorant Teacher. COLT 1994 : 328-339 Sally A. Goldman, Robert H. Sloan : The Power of Self-Directed Learning. Machine Learning 14 (1): 271-294 (1994) Nader H. Bshouty , Sally A. Goldman, Thomas R. Hancock , Sleiman Matar : Asking Questions to Minimize Errors. COLT 1993 : 41-50 Sally A. Goldman, Manfred K. Warmuth : Learning Binary Relations Using Weighted Majority Voting. COLT 1993 : 453-462 Sally A. Goldman, H. David Mathias : Teaching a Smart Learner. COLT 1993 : 67-76 Sally A. Goldman, Michael J. Kearns , Robert E. Schapire : Exact Identification of Read-Once Formulas Using Fixed Points of Amplification Functions. SIAM J. Comput. 22 (4): 705-726 (1993) Sally A. Goldman, Ronald L. Rivest , Robert E. Schapire : Learning Binary Relations and Total Orders. SIAM J. Comput. 22 (5): 1006-1034 (1993) Sally A. Goldman, H. David Mathias : Learning k -Term DNF Formulas with an Incomplete Membership Oracle. COLT 1992 : 77-84 Sally A. Goldman, Michael J. Kearns : On the Complexity of Teaching. COLT 1991 : 303-314 Sally A. Goldman, Michael J. Kearns , Robert E. Schapire : On the Sample Complexity of Weak Learning. COLT 1990 : 217-231 Sally A. Goldman, Michael J. Kearns , Robert E. Schapire : Exact Identification of Circuits Using Fixed Points of Amplification Functions (Abstract). COLT 1990 : 388 Sally A. Goldman, Michael J. Kearns , Robert E. Schapire : Exact Identification of Circuits Using Fixed Points of Amplification Functions (Extended Abstract) FOCS 1990 : 193-202 Sally A. Goldman, Ronald L. Rivest , Robert E. Schapire : Learning Binary Relations and Total Orders (Extended Abstract) FOCS 1989 : 46-51 Sally A. Goldman: A Space Efficient Greedy Triangulation Algorithm. Inf. Process. Lett. 31 (4): 191-196 (1989) Sally A. Goldman, Ronald L. Rivest : A non-iterative maximum entropy algorithm. UAI 1986 : 133-148 Kenneth J. Goldman , Sally A. Goldman, Paris C. Kanellakis , Stanley B. Zdonik : ISIS: Interface for a Semantic Information System. SIGMOD Conference 1985 : 328-342 1 [ 48 ] [ 51 ] 2 [ 24 ] [ 36 ] 3 [ 14 ] [ 25 ] [ 28 ] [ 30 ] [ 35 ] [ 37 ] [ 38 ] 4 [ 44 ] 5 [ 24 ] [ 36 ] 6 [ 39 ] [ 46 ] [ 48 ] [ 49 ] [ 51 ] 7 [ 16 ] [ 27 ] 8 [ 53 ] 9 [ 17 ] [ 18 ] [ 26 ] [ 35 ] 10 [ 1 ] 11 [ 14 ] [ 28 ] 12 [ 1 ] 13 [ 5 ] [ 6 ] [ 7 ] [ 8 ] [ 11 ] [ 21 ] [ 22 ] 14 [ 33 ] [ 34 ] [ 41 ] [ 45 ] [ 49 ] [ 50 ] [ 54 ] 15 [ 14 ] [ 28 ] 16 [ 9 ] [ 12 ] [ 18 ] [ 25 ] [ 29 ] [ 30 ] [ 35 ] [ 37 ] [ 38 ] 17 [ 16 ] [ 27 ] 18 [ 32 ] [ 42 ] 19 [ 16 ] [ 27 ] 20 [ 2 ] [ 4 ] [ 10 ] 21 [ 4 ] [ 5 ] [ 6 ] [ 7 ] [ 10 ] [ 11 ] [ 22 ] 22 [ 26 ] [ 31 ] [ 33 ] [ 34 ] [ 39 ] [ 40 ] [ 45 ] [ 46 ] [ 54 ] [ 55 ] 23 [ 15 ] [ 23 ] 24 [ 24 ] [ 36 ] 25 [ 30 ] [ 32 ] [ 37 ] [ 42 ] 26 [ 30 ] [ 37 ] 27 [ 13 ] [ 19 ] 28 [ 53 ] 29 [ 1 ] 30 [ 47 ] [ 48 ] [ 51 ] [ 53 ] 31 [ 43 ] [ 56 ]  ©2006 Association for Computing Machinery |
