| The use of MMR, diversity-based reranking for reordering documents and producing summaries J Carbonell, J Goldstein Proceedings of the 21st annual international ACM SIGIR conference on …, 1998 | 2762 | 1998 |
| An artificial intelligence approach RS Mitchell, JG Michalski, TM Carbonell Springer, Berlin, 2013 | 2529 | 2013 |
| Topic detection and tracking pilot study final report J Allan, JG Carbonell, G Doddington, J Yamron, Y Yang Carnegie Mellon University, 1998 | 1322 | 1998 |
| A study of retrospective and on-line event detection Y Yang, T Pierce, J Carbonell Proceedings of the 21st annual international ACM SIGIR conference on …, 1998 | 908 | 1998 |
| Derivational analogy: A theory of reconstructive problem solving and expertise acquisition. JG Carbonell CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF COMPUTER SCIENCE, 1985 | 816 | 1985 |
| Learning by analogy: Formulating and generalizing plans from past experience JG Carbonell Machine learning, 137-161, 1983 | 696 | 1983 |
| Summarizing text documents: sentence selection and evaluation metrics J Goldstein, M Kantrowitz, V Mittal, J Carbonell Proceedings of the 22nd annual international ACM SIGIR conference on …, 1999 | 620 | 1999 |
| Temporal collaborative filtering with bayesian probabilistic tensor factorization L Xiong, X Chen, TK Huang, J Schneider, JG Carbonell Proceedings of the 2010 SIAM international conference on data mining, 211-222, 2010 | 548 | 2010 |
| Integrating planning and learning: The PRODIGY architecture M Veloso, J Carbonell, A Perez, D Borrajo, E Fink, J Blythe Journal of Experimental & Theoretical Artificial Intelligence 7 (1), 81-120, 1995 | 535 | 1995 |
| An overview of machine learning JG Carbonell, RS Michalski, TM Mitchell Machine learning, 3-23, 1983 | 508 | 1983 |
| Learning approaches for detecting and tracking news events Y Yang, JG Carbonell, RD Brown, T Pierce, BT Archibald, X Liu IEEE Intelligent Systems and Their Applications 14 (4), 32-43, 1999 | 477 | 1999 |
| Multi-document summarization by sentence extraction J Goldstein, V Mittal, J Carbonell, M Kantrowitz Proceedings of the 2000 NAACL-ANLP Workshop on Automatic summarization, 40-48, 2000 | 436 | 2000 |
| Explanation-based learning: A problem solving perspective S Minton, JG Carbonell, CA Knoblock, DR Kuokka, O Etzioni, Y Gil Artificial Intelligence 40 (1-3), 63-118, 1989 | 384 | 1989 |
| Prodigy: An integrated architecture for planning and learning JG Carbonell, CA Knoblock, S Minton Architectures for intelligence, 255-292, 2014 | 322 | 2014 |
| Derivational analogy in PRODIGY: Automating case acquisition, storage, and utilization MM Veloso, JG Carbonell Case-Based Learning, 55-84, 1993 | 313 | 1993 |
| Subjective understanding: computer models of belief systems. JG Carbonell YALE UNIV NEW HAVEN CONN DEPT OF COMPUTER SCIENCE, 1979 | 312 | 1979 |
| Topic-conditioned novelty detection Y Yang, J Zhang, J Carbonell, C Jin Proceedings of the eighth ACM SIGKDD international conference on Knowledge …, 2002 | 308 | 2002 |
| Xlnet: Generalized autoregressive pretraining for language understanding Z Yang, Z Dai, Y Yang, J Carbonell, RR Salakhutdinov, QV Le Advances in neural information processing systems, 5754-5764, 2019 | 307 | 2019 |
| Machine learning: A multistrategy approach RS Michalski, G Tecuci Morgan Kaufmann, 1994 | 304* | 1994 |
| Smoothing proximal gradient method for general structured sparse regression X Chen, Q Lin, S Kim, JG Carbonell, EP Xing The Annals of Applied Statistics 6 (2), 719-752, 2012 | 298 | 2012 |
Yiming YangProfessor of Computer Science, Carnegie Mellon UniversityEmail verificata su cs.cmu.edu
