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David B. Leake
David Leake
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- affiliation: Indiana University, Bloomington, USA
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2020 – today
- 2024
- [c115]Zachary Wilkerson, David Leake, Vibhas Vats, David Crandall:
Extracting Indexing Features for CBR from Deep Neural Networks: A Transfer Learning Approach. ICCBR 2024: 143-158 - [c114]Xiaomeng Ye, David Leake, Yu Wang, Ziwei Zhao, David Crandall:
Towards Network Implementation of CBR: Case Study of a Neural Network K-NN Algorithm. ICCBR 2024: 354-370 - [c113]Kaitlynne Wilkerson, David Leake:
On Implementing Case-Based Reasoning with Large Language Models. ICCBR 2024: 404-417 - [i2]Ziwei Zhao, David Leake, Xiaomeng Ye, David J. Crandall:
Case-Enhanced Vision Transformer: Improving Explanations of Image Similarity with a ViT-based Similarity Metric. CoRR abs/2407.16981 (2024) - 2023
- [j41]Richard Granger, David Leake, Christopher K. Riesbeck:
In Memoriam: Roger C. Schank, 1946-2023. AI Mag. 44(3): 343-344 (2023) - [c112]David Leake, Zachary Wilkerson, Vibhas Vats, Karan Acharya, David J. Crandall:
Examining the Impact of Network Architecture on Extracted Feature Quality for CBR. ICCBR 2023: 3-18 - [c111]Esteban Marquer, Fadi Badra, Marie-Jeanne Lesot, Miguel Couceiro, David Leake:
Less is Better: An Energy-Based Approach to Case Base Competence. ICCBR Workshops 2023: 27-42 - [c110]Lawrence Gates, David Leake, Kaitlynne Wilkerson:
Cases Are King: A User Study of Case Presentation to Explain CBR Decisions. ICCBR 2023: 153-168 - [c109]David Leake, Brian Schack:
Towards Addressing Problem-Distribution Drift with Case Discovery. ICCBR 2023: 244-259 - [c108]Kristian J. Hammond, David B. Leake:
Large Language Models Need Symbolic AI. NeSy 2023: 204-209 - [p5]David Leake, Zachary Wilkerson, Xiaomeng Ye, David J. Crandall:
Enhancing Case-Based Reasoning with Neural Networks. Compendium of Neurosymbolic Artificial Intelligence 2023: 387-409 - 2022
- [c107]David Leake, Zachary Wilkerson, David Crandall:
Extracting Case Indices from Convolutional Neural Networks: A Comparative Study. ICCBR 2022: 81-95 - [c106]Xiaomeng Ye, David Leake, David Crandall:
Case Adaptation with Neural Networks: Capabilities and Limitations. ICCBR 2022: 143-158 - [c105]Ziwei Zhao, David Leake, Xiaomeng Ye, David J. Crandall:
Generating Counterfactual Images: Towards a C2C-VAE Approach. ICCBR Workshops 2022: 189-194 - [c104]David Leake:
Case-based Explanation: Making the Implicit Explicit. ICCBR Workshops 2022: 195-200 - [c103]Zachary Wilkerson, David Leake, David Crandall:
Leveraging SHAP and CBR for Dimensionaltiy Reduction on the Psychology Prediction Dataset. ICCBR Workshops 2022: 236-240 - [c102]Xiaomeng Ye, Ziwei Zhao, David Leake, David Crandall:
Generation and Evaluation of Creative Images from Limited Data: A Class-to-Class VAE Approach. ICCC 2022: 314-323 - 2021
- [c101]David Leake, Xiaomeng Ye, David J. Crandall:
Supporting Case-Based Reasoning with Neural Networks: An Illustration for Case Adaptation. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering 2021 - [c100]Lawrence Gates, David Leake:
Evaluating CBR Explanation Capabilities: Survey and Next Steps. ICCBR Workshops 2021: 40-51 - [c99]David Leake, Xiaomeng Ye:
Harmonizing Case Retrieval and Adaptation with Alternating Optimization. ICCBR 2021: 125-139 - [c98]Zachary Wilkerson, David Leake, David J. Crandall:
On Combining Knowledge-Engineered and Network-Extracted Features for Retrieval. ICCBR 2021: 248-262 - [c97]Xiaomeng Ye, David Leake, Vahid Jalali, David J. Crandall:
Learning Adaptations for Case-Based Classification: A Neural Network Approach. ICCBR 2021: 279-293 - [i1]Xiaomeng Ye, Ziwei Zhao, David Leake, Xizi Wang, David J. Crandall:
Applying the Case Difference Heuristic to Learn Adaptations from Deep Network Features. CoRR abs/2107.07095 (2021) - 2020
- [c96]Xiaomeng Ye, David Leake, William Huibregtse, Mehmet M. Dalkilic:
Applying Class-to-Class Siamese Networks to Explain Classifications with Supportive and Contrastive Cases. ICCBR 2020: 245-260 - [c95]David Leake, Xiaomeng Ye:
Learning to Improve Efficiency for Adaptation Paths. ICCBR 2020: 325-340 - [c94]David Leake, David J. Crandall:
On Bringing Case-Based Reasoning Methodology to Deep Learning. ICCBR 2020: 343-348
2010 – 2019
- 2019
- [c93]Lawrence Gates, Caleb Kisby, David Leake:
CBR Confidence as a Basis for Confidence in Black Box Systems. ICCBR 2019: 95-109 - [c92]David Leake, Xiaomeng Ye:
On Combining Case Adaptation Rules. ICCBR 2019: 204-218 - [c91]Katherine Metcalf, David Leake:
Unsupervised Hierarchical Temporal Abstraction by Simultaneously Learning Expectations and Representations. IJCAI 2019: 3144-3150 - 2018
- [c90]Vahid Jalali, David Leake:
Harnessing Hundreds of Millions of Cases: Case-Based Prediction at Industrial Scale. ICCBR 2018: 153-169 - [c89]David Leake, Brian Schack:
Exploration vs. Exploitation in Case-Base Maintenance: Leveraging Competence-Based Deletion with Ghost Cases. ICCBR 2018: 202-218 - [c88]Katherine Metcalf, David Leake:
Embedded Word Representations for Rich Indexing: A Case Study for Medical Records. ICCBR 2018: 264-280 - 2017
- [j40]Vahid Jalali, David Leake, Najmeh Forouzandehmehr:
Learning and applying adaptation rules for categorical features: An ensemble approach. AI Commun. 30(3-4): 193-205 (2017) - [c87]Devendra Singh Dhami, David Leake, Sriraam Natarajan:
Knowledge-Based Morphological Classification of Galaxies from Vision Features. AAAI Workshops 2017 - [c86]Katherine Metcalf, David Leake:
Modelling Unsupervised Event Segmentation: Learning Event Boundaries from Prediction Errors. CogSci 2017 - [c85]Vahid Jalali, David Leake:
Scaling Up Ensemble of Adaptations for Classification by Approximate Nearest Neighbor Retrieval. ICCBR 2017: 154-169 - [c84]Yang Zhang, Su Zhang, David Leake:
Maintenance for Case Streams: A Streaming Approach to Competence-Based Deletion. ICCBR 2017: 420-434 - [c83]Vahid Jalali, David Leake, Najmeh Forouzandehmehr:
Learning and Applying Case Adaptation Rules for Classification: An Ensemble Approach. IJCAI 2017: 4874-4878 - 2016
- [j39]David B. Leake:
After Seventeen Years and 70 Issues ... AI Mag. 37(2): 3-4 (2016) - [j38]David B. Leake:
Passing the Torch. AI Mag. 37(3): 3-4 (2016) - [j37]David B. Leake, Barry Smyth, Rosina Weber:
Guest editors' introduction: special issue on case-based reasoning. J. Intell. Inf. Syst. 46(2): 235-236 (2016) - [j36]Vahid Jalali, David Leake:
Enhancing case-based regression with automatically-generated ensembles of adaptations. J. Intell. Inf. Syst. 46(2): 237-258 (2016) - [j35]Carlos M. Lorenzetti, Ana Gabriela Maguitman, David Leake, Filippo Menczer, Thomas Reichherzer:
Mining for Topics to Suggest Knowledge Model Extensions. ACM Trans. Knowl. Discov. Data 11(2): 23:1-23:30 (2016) - [c82]Katherine Metcalf, David B. Leake:
A Computational Method for Extracting, Representing, and Predicting Social Closeness. ECAI 2016: 1176-1184 - [c81]Vahid Jalali, David B. Leake, Najmeh Forouzandehmehr:
Ensemble of Adaptations for Classification: Learning Adaptation Rules for Categorical Features. ICCBR 2016: 186-202 - [c80]Yang Zhang, Su Zhang, David Leake:
Case-Base Maintenance: A Streaming Approach. ICCBR Workshops 2016: 222-231 - [c79]David Leake, Brian Schack:
Adaptation-Guided Feature Deletion: Testing Recoverability to Guide Case Compression. ICCBR 2016: 234-248 - 2015
- [c78]Katherine Metcalf, David Leake:
Investigating Methods and Representations for Reasoning About Social Context and Relative Social Power. CONTEXT 2015: 385-397 - [c77]Vahid Jalali, David B. Leake:
CBR Meets Big Data: A Case Study of Large-Scale Adaptation Rule Generation. ICCBR 2015: 181-196 - [c76]David Leake, Brian Schack:
Flexible Feature Deletion: Compacting Case Bases by Selectively Compressing Case Contents. ICCBR 2015: 212-227 - [c75]Raksha Kumaraswamy, Phillip Odom, Kristian Kersting, David Leake, Sriraam Natarajan:
Transfer Learning via Relational Type Matching. ICDM 2015: 811-816 - 2014
- [j34]Joseph Kendall-Morwick, David B. Leake:
Facilitating representation and retrieval of structured cases: Principles and toolkit. Inf. Syst. 40: 106-114 (2014) - [j33]David B. Leake, Ana Gabriela Maguitman, Thomas Reichherzer:
Experience-based support for human-centered knowledge modeling. Knowl. Based Syst. 68: 77-87 (2014) - [c74]Vahid Jalali, David Leake:
Adaptation-Guided Case Base Maintenance. AAAI 2014: 1875-1881 - [c73]Vahid Jalali, David Leake:
An Ensemble Approach to Adaptation-Guided Retrieval. FLAIRS 2014 - [c72]Vahid Jalali, David Leake:
On Retention of Adaptation Rules. ICCBR 2014: 200-214 - [p4]David B. Leake, Vahid Jalali:
Context and Case-Based Reasoning. Context in Computing 2014: 473-490 - [e15]Zhongzhi Shi, Zhaohui Wu, David B. Leake, Uli Sattler:
Intelligent Information Processing VII - 8th IFIP TC 12 International Conference, IIP 2014, Hangzhou, China, October 17-20, 2014, Proceedings. IFIP Advances in Information and Communication Technology 432, Springer 2014, ISBN 978-3-662-44979-0 [contents] - 2013
- [j32]David Leake:
Announcing the Digital Edition of AI Magazine. AI Mag. 34(2): 8 (2013) - [j31]David Leake:
Announcing the New App for AI Magazine. AI Mag. 34(4): 9- (2013) - [c71]Vahid Jalali, David Leake:
A Context-Aware Approach to Selecting Adaptations for Case-Based Reasoning. CONTEXT 2013: 101-114 - [c70]Vahid Jalali, David Leake:
An Ensemble Approach to Instance-Based Regression Using Stretched Neighborhoods. FLAIRS 2013 - [c69]Vahid Jalali, David Leake:
On Deriving Adaptation Rule Confidence from the Rule Generation Process. ICCBR 2013: 179-187 - [c68]Vahid Jalali, David Leake:
Extending Case Adaptation with Automatically-Generated Ensembles of Adaptation Rules. ICCBR 2013: 188-202 - 2012
- [j30]David B. Leake:
The Diversity of AI. AI Mag. 33(1): 9 (2012) - [c67]Scott Jensen, Miao Chen, Xiaozhong Liu, Beth Plale, David Leake:
Mining classifications from social-ecological databases. ASIST 2012: 1-4 - [c66]Scott Jensen, Beth Plale, Xiaozhong Liu, Miao Chen, David B. Leake, Julie England:
Generalized representation and mapping for social-ecological data: Freeing data from the database. eScience 2012: 1-8 - [c65]Vahid Jalali, David Leake:
Customizing Question Selection in Conversational Case-Based Reasoning. FLAIRS 2012 - [c64]Vahid Jalali, David Leake:
Custom Accessibility-Based CCBR Question Selection by Ongoing User Classification. ICCBR 2012: 196-210 - [e14]Zhongzhi Shi, David B. Leake, Sunil Vadera:
Intelligent Information Processing VI - 7th IFIP TC 12 International Conference, IIP 2012, Guilin, China, October 12-15, 2012. Proceedings. IFIP Advances in Information and Communication Technology 385, Springer 2012, ISBN 978-3-642-32890-9 [contents] - 2011
- [c63]You-Wei Cheah, Beth Plale, Joseph Kendall-Morwick, David B. Leake, Lavanya Ramakrishnan:
A Noisy 10GB Provenance Database. Business Process Management Workshops (2) 2011: 370-381 - [c62]Thomas Roth-Berghofer, Nava Tintarev, David B. Leake:
Organizing Committee / Preface. ExaCt 2011 - [c61]David Leake, Mark Wilson:
How Many Cases Do You Need? Assessing and Predicting Case-Base Coverage. ICCBR 2011: 92-106 - [c60]David B. Leake, Jay H. Powell:
Enhancing Case Adaptation with Introspective Reasoning and Web Mining. IJCAI 2011: 2680-2685 - [p3]Josep Lluís Arcos, Oguz Mülâyim, David B. Leake:
Using Introspective Reasoning to Improve CBR System Performance. Metareasoning 2011: 167-182 - [e13]Thomas Roth-Berghofer, Nava Tintarev, David B. Leake:
Explanation-aware Computing, Papers from the 2011 IJCAI Workshop, Barcelona, Spain, July 16-17, 2011. 2011 [contents] - 2010
- [c59]Thomas Roth-Berghofer, Nava Tintarev, David B. Leake, Daniel Bahls:
Organizing Committee / Preface. ExaCt 2010 - [c58]David B. Leake, Jay H. Powell:
A General Introspective Reasoning Approach to Web Search for Case Adaptation. ICCBR 2010: 186-200 - [c57]David B. Leake:
Case-Based Reasoning Tomorrow: Provenance, the Web, and Cases in the Future of Intelligent Information Processing. Intelligent Information Processing 2010: 1 - [e12]Thomas Roth-Berghofer, Nava Tintarev, David B. Leake, Daniel Bahls:
Explanation-aware Computing, Papers from the 2010 ECAI Workshop, Lisbon, Portugal, August 16, 2010. University of Lisbon, Portugal 2010 [contents] - [e11]Zhongzhi Shi, Sunil Vadera, Agnar Aamodt, David B. Leake:
Intelligent Information Processing V - 6th IFIP TC 12 International Conference, IIP 2010, Manchester, UK, October 13-16, 2010. Proceedings. IFIP Advances in Information and Communication Technology 340, Springer 2010, ISBN 978-3-642-16326-5 [contents]
2000 – 2009
- 2009
- [c56]Thomas Roth-Berghofer, Nava Tintarev, David B. Leake:
Organizing Committee / Preface. ExaCt 2009 - [c55]David B. Leake, Joseph Kendall-Morwick:
Four Heads Are Better than One: Combining Suggestions for Case Adaptation. ICCBR 2009: 165-179 - [c54]Eran Chinthaka, Jaliya Ekanayake, David B. Leake, Beth Plale:
CBR Based Workflow Composition Assistant. SERVICES I 2009: 352-355 - [e10]Thomas Roth-Berghofer, Nava Tintarev, David B. Leake:
Explanation-aware Computing, Papers from the 2009 IJCAI Workshop, Pasadena, California , USA, July 11-12, 2009. 2009 [contents] - [e9]Zhongzhi Shi, Eunika Mercier-Laurent, David B. Leake:
Intelligent Information Processing IV, 5th IFIP International Conference on Intelligent Information Processing, October 19-22, 2008, Beijing, China. IFIP Advances in Information and Communication Technology 288, Springer 2009, ISBN 978-0-387-87684-9 [contents] - 2008
- [j29]Anders Kofod-Petersen, Jörg Cassens, David B. Leake, Stefan Schulz:
Report on the 2007 Workshop on Modeling and Reasoning in Context. AI Mag. 29(1): 97-98 (2008) - [j28]David B. Leake, James Gary:
AI Magazine Poster: The AI Landscape. AI Mag. 29(2): 3-4 (2008) - [c53]Steven Bogaerts, David B. Leake:
Formal and Experimental Foundations of a New Rank Quality Measure. ECCBR 2008: 74-88 - [c52]David B. Leake, Scott A. Dial:
Using Case Provenance to Propagate Feedback to Cases and Adaptations. ECCBR 2008: 255-268 - [c51]David B. Leake, Joseph Kendall-Morwick:
Towards Case-Based Support for e-Science Workflow Generation by Mining Provenance. ECCBR 2008: 269-283 - [c50]David B. Leake, Jay H. Powell:
Knowledge Planning and Learned Personalization for Web-Based Case Adaptation. ECCBR 2008: 284-298 - [c49]Thomas Roth-Berghofer, Stefan Schulz, David B. Leake, Daniel Bahls:
Organizing Committee / Preface. ExaCt 2008 - [c48]David B. Leake:
Provenance and Case-Based Reasoning. FLAIRS 2008: 20 - [p2]David B. Leake, Thomas Reichherzer:
Knowledge-Based Computation. Wiley Encyclopedia of Computer Science and Engineering 2008 - [e8]Thomas Roth-Berghofer, Stefan Schulz, David B. Leake, Daniel Bahls:
Explanation-aware Computing, Papers from the 2008 ECAI Workshop, Patras, Greece, July 21-22, 2008. University of Patras. 2008 [contents] - 2007
- [j27]Sarabjot Singh Anand, Daniel Bahls, Catherina Burghart, Mark H. Burstein, Huajun Chen, John Collins, Thomas G. Dietterich, Jon Doyle, Chris Drummond, William Elazmeh, Christopher W. Geib, Judy Goldsmith, Hans W. Guesgen, Jim Hendler, Dietmar Jannach, Nathalie Japkowicz, Ulrich Junker, Gal A. Kaminka, Alfred Kobsa, Jérôme Lang, David B. Leake, Lundy Lewis, Gerard Ligozat, Sofus A. Macskassy, Drew V. McDermott, Ted Metzler, Bamshad Mobasher, Ullas Nambiar, Zaiqing Nie, Klas Orsvärn, Barry O'Sullivan, David V. Pynadath, Jochen Renz, Rita V. Rodríguez, Thomas Roth-Berghofer, Stefan Schulz, Rudi Studer, Yimin Wang, Michael P. Wellman:
AAAI-07 Workshop Reports. AI Mag. 28(4): 119-128 (2007) - [c47]Thomas Roth-Berghofer, Stefan Schulz, Daniel Bahls, David B. Leake:
Organizing Committee / Preface. ExaCt 2007 - [c46]David B. Leake, Matthew Whitehead:
Case Provenance: The Value of Remembering Case Sources. ICCBR 2007: 194-208 - [c45]David B. Leake, Jay H. Powell:
Mining Large-Scale Knowledge Sources for Case Adaptation Knowledge. ICCBR 2007: 209-223 - [e7]Thomas Roth-Berghofer, Stefan Schulz, Daniel Bahls, David B. Leake:
Explanation-Aware Computing, Papers from the 2007 AAAI Workshop, Vancouver, British Columbia, Canada, July 22-23, 2007. AAAI Technical Report WS-07-06, AAAI Press 2007, ISBN 978-1-57735-333-1 [contents] - 2006
- [j26]David B. Leake:
Editorial Introduction. AI Mag. 27(4): 3 (2006) - [j25]Wolfgang Achtner, Esma Aïmeur, Sarabjot Singh Anand, Douglas E. Appelt, Naveen Ashish, Tiffany Barnes, Joseph E. Beck, M. Bernardine Dias, Prashant Doshi, Chris Drummond, William Elazmeh, Ariel Felner, Dayne Freitag, Hector Geffner, Christopher W. Geib, Richard Goodwin, Robert C. Holte, Frank Hutter, Fair Isaac, Nathalie Japkowicz, Gal A. Kaminka, Sven Koenig, Michail G. Lagoudakis, David B. Leake, Lundy Lewis, Hugo Liu, Ted Metzler, Rada Mihalcea, Bamshad Mobasher, Pascal Poupart, David V. Pynadath, Thomas Roth-Berghofer, Wheeler Ruml, Stefan Schulz, Sven Schwarz, Stephanie Seneff, Amit P. Sheth, Ron Sun, Michael Thielscher, Afzal Upal, Jason D. Williams, Steve J. Young, Dmitry Zelenko:
Reports on the Twenty-First National Conference on Artificial Intelligence (AAAI-06) Workshop Program. AI Mag. 27(4): 92-102 (2006) - [c44]Steven Bogaerts, David B. Leake:
What Evaluation Criteria Are Right for CCBR? Considering Rank Quality. ECCBR 2006: 385-399 - [c43]Steven Bogaerts, David B. Leake:
Focusing AI Students' Attention: A Framework-Based Approach to Guiding Impasse-Driven Learning. FLAIRS 2006: 186-191 - [p1]David B. Leake, Ana Gabriela Maguitman, Thomas Reichherzer:
Cases, Context, and Comfort: Opportunities for Case-Based Reasoning in Smart Homes. Designing Smart Homes 2006: 109-131 - [e6]Thomas Roth-Berghofer, Stefan Schulz, David B. Leake:
Modeling and Retrieval of Context, Second International Workshop, MRC 2005, Edinburgh, UK, July 31 - August 1, 2005, Revised Selected Papers. Lecture Notes in Computer Science 3946, Springer 2006, ISBN 3-540-33587-0 [contents] - 2005
- [j24]David B. Leake:
Happy Anniversary, AAAI and AI Magazine! AI Mag. 26(4): 1 (2005) - [j23]David B. Leake, David McSherry:
Introduction to the Special Issue on Explanation in Case-Based Reasoning. Artif. Intell. Rev. 24(2): 103-108 (2005) - [j22]Ramón López de Mántaras, David McSherry, Derek G. Bridge, David B. Leake, Barry Smyth, Susan Craw, Boi Faltings, Mary Lou Maher, Michael T. Cox, Kenneth D. Forbus, Mark T. Keane, Agnar Aamodt, Ian D. Watson:
Retrieval, reuse, revision and retention in case-based reasoning. Knowl. Eng. Rev. 20(3): 215-240 (2005) - [c42]David B. Leake, Ana Gabriela Maguitman, Thomas Reichherzer:
Exploiting Rich Context: An Incremental Approach to Context-Based Web Search. CONTEXT 2005: 254-267 - [c41]Steven Bogaerts, David B. Leake:
Increasing AI Project Effectiveness with Reusable Code Frameworks: A Case Study Using IUCBRF. FLAIRS 2005: 2-7 - [c40]David B. Leake, Steven Bogaerts, Michael Evans, Rick McMullen, Michael Oder, Alejandro Valerio:
Using Cases to Support Divergent Roles in Distributed Collaboration. FLAIRS 2005: 117-122 - [c39]Stefan Schulz, David B. Leake, Thomas Roth-Berghofer:
Preface. MRC@IJCAI 2005 - [c38]Ana Gabriela Maguitman, David B. Leake, Thomas Reichherzer:
Suggesting novel but related topics: towards context-based support for knowledge model extension. IUI 2005: 207-214 - [e5]Anind K. Dey, Boicho N. Kokinov, David B. Leake, Roy M. Turner:
Modeling and Using Context, 5th International and Interdisciplinary Conference, CONTEXT 2005, Paris, France, July 5-8, 2005, Proceedings. Lecture Notes in Computer Science 3554, Springer 2005, ISBN 3-540-26924-X [contents] - [e4]Thomas Roth-Berghofer, Stefan Schulz, David B. Leake:
Proceedings of the IJCAI-05 Workshop on Modeling and Retrieval of Context Edinburgh, July 31 - August 1, 2005. CEUR Workshop Proceedings 146, CEUR-WS.org 2005 [contents] - 2004
- [j21]David B. Leake:
The Seventh International Conference on Intelligent User Interfaces (IUI-2003). AI Mag. 24(4): 131-132 (2004) - [j20]