David Leake

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 40

Top Topics

Approximate Nearest Neighbor

Image Similarity

Top Venues

ICCBR Workshops

Publications

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 (2024)
Zachary Wilkerson, David Leake, Vibhas Vats, David Crandall
Extracting Indexing Features for CBR from Deep Neural Networks: A Transfer Learning Approach. ICCBR (2024)
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)
Kaitlynne Wilkerson, David Leake
On Implementing Case-Based Reasoning with Large Language Models. ICCBR (2024)
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)
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)
Richard Granger, David Leake, Christopher K. Riesbeck
In Memoriam: Roger C. Schank, 1946-2023. AI Mag. 44 (3) (2023)
David Leake, Brian Schack
Towards Addressing Problem-Distribution Drift with Case Discovery. ICCBR (2023)
Lawrence Gates, David Leake, Kaitlynne Wilkerson
Cases Are King: A User Study of Case Presentation to Explain CBR Decisions. ICCBR (2023)
Zachary Wilkerson, David Leake, David Crandall
Leveraging SHAP and CBR for Dimensionaltiy Reduction on the Psychology Prediction Dataset. ICCBR Workshops (2022)
Ziwei Zhao, David Leake, Xiaomeng Ye, David J. Crandall
Generating Counterfactual Images: Towards a C2C-VAE Approach. ICCBR Workshops (2022)
Xiaomeng Ye, David Leake, David J. Crandall
Case Adaptation with Neural Networks: Capabilities and Limitations. ICCBR (2022)
David Leake
Case-based Explanation: Making the Implicit Explicit. ICCBR Workshops (2022)
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)
David Leake, Zachary Wilkerson, David J. Crandall
Extracting Case Indices from Convolutional Neural Networks: A Comparative Study. ICCBR (2022)
Lawrence Gates, David Leake
Evaluating CBR Explanation Capabilities: Survey and Next Steps. ICCBR Workshops (2021)
David Leake, Xiaomeng Ye
Harmonizing Case Retrieval and Adaptation with Alternating Optimization. ICCBR (2021)
Xiaomeng Ye, Ziwei Zhao, David Leake, Xizi Wang, David J. Crandall
Applying the Case Difference Heuristic to Learn Adaptations from Deep Network Features. CoRR (2021)
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)
Xiaomeng Ye, David Leake, Vahid Jalali, David J. Crandall
Learning Adaptations for Case-Based Classification: A Neural Network Approach. ICCBR (2021)
Zachary Wilkerson, David Leake, David J. Crandall
On Combining Knowledge-Engineered and Network-Extracted Features for Retrieval. ICCBR (2021)
David Leake, David J. Crandall
On Bringing Case-Based Reasoning Methodology to Deep Learning. ICCBR (2020)
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)
David Leake, Xiaomeng Ye
Learning to Improve Efficiency for Adaptation Paths. ICCBR (2020)
David Leake, Xiaomeng Ye
On Combining Case Adaptation Rules. ICCBR (2019)
Lawrence Gates, Caleb Kisby, David Leake
CBR Confidence as a Basis for Confidence in Black Box Systems. ICCBR (2019)
Katherine Metcalf, David Leake
Unsupervised Hierarchical Temporal Abstraction by Simultaneously Learning Expectations and Representations. IJCAI (2019)
David Leake, Brian Schack
Exploration vs. Exploitation in Case-Base Maintenance: Leveraging Competence-Based Deletion with Ghost Cases. ICCBR (2018)
Katherine Metcalf, David Leake
Embedded Word Representations for Rich Indexing: A Case Study for Medical Records. ICCBR (2018)
Vahid Jalali, David Leake
Harnessing Hundreds of Millions of Cases: Case-Based Prediction at Industrial Scale. ICCBR (2018)
Vahid Jalali, David Leake, Najmeh Forouzandehmehr
Learning and Applying Case Adaptation Rules for Classification: An Ensemble Approach. IJCAI (2017)
Vahid Jalali, David Leake
Scaling Up Ensemble of Adaptations for Classification by Approximate Nearest Neighbor Retrieval. ICCBR (2017)
Katherine Metcalf, David Leake
Modelling Unsupervised Event Segmentation: Learning Event Boundaries from Prediction Errors. CogSci (2017)
Yang Zhang, Su Zhang, David Leake
Maintenance for Case Streams: A Streaming Approach to Competence-Based Deletion. ICCBR (2017)
Vahid Jalali, David Leake, Najmeh Forouzandehmehr
Learning and applying adaptation rules for categorical features: An ensemble approach. AI Commun. 30 (3-4) (2017)
Devendra Singh Dhami, David Leake, Sriraam Natarajan
Knowledge-Based Morphological Classification of Galaxies from Vision Features. AAAI Workshops (2017)
David Leake, Brian Schack
Adaptation-Guided Feature Deletion: Testing Recoverability to Guide Case Compression. ICCBR (2016)
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) (2016)
Yang Zhang, Su Zhang, David Leake
Case-Base Maintenance: A Streaming Approach. ICCBR Workshops (2016)
Vahid Jalali, David Leake
Enhancing case-based regression with automatically-generated ensembles of adaptations. J. Intell. Inf. Syst. 46 (2) (2016)
Katherine Metcalf, David Leake
Investigating Methods and Representations for Reasoning About Social Context and Relative Social Power. CONTEXT (2015)
David Leake, Brian Schack
Flexible Feature Deletion: Compacting Case Bases by Selectively Compressing Case Contents. ICCBR (2015)
Raksha Kumaraswamy, Phillip Odom, Kristian Kersting, David Leake, Sriraam Natarajan
Transfer Learning via Relational Type Matching. ICDM (2015)
Vahid Jalali, David Leake
On Retention of Adaptation Rules. ICCBR (2014)
Vahid Jalali, David Leake
Adaptation-Guided Case Base Maintenance. AAAI (2014)
Vahid Jalali, David Leake
An Ensemble Approach to Adaptation-Guided Retrieval. FLAIRS Conference (2014)
David Leake
Announcing the Digital Edition of AI Magazine. AI Mag. 34 (2) (2013)
David Leake
Announcing the New App for AI Magazine. AI Mag. 34 (4) (2013)
Vahid Jalali, David Leake
An Ensemble Approach to Instance-Based Regression Using Stretched Neighborhoods. FLAIRS Conference (2013)
Vahid Jalali, David Leake
On Deriving Adaptation Rule Confidence from the Rule Generation Process. ICCBR (2013)
Vahid Jalali, David Leake
Extending Case Adaptation with Automatically-Generated Ensembles of Adaptation Rules. ICCBR (2013)
Vahid Jalali, David Leake
A Context-Aware Approach to Selecting Adaptations for Case-Based Reasoning. CONTEXT (2013)
Vahid Jalali, David Leake
Customizing Question Selection in Conversational Case-Based Reasoning. FLAIRS Conference (2012)
Scott Jensen, Miao Chen, Xiaozhong Liu, Beth Plale, David Leake
Mining classifications from social-ecological databases. ASIST (2012)
Vahid Jalali, David Leake
Custom Accessibility-Based CCBR Question Selection by Ongoing User Classification. ICCBR (2012)
David Leake, Mark Wilson
How Many Cases Do You Need? Assessing and Predicting Case-Base Coverage. ICCBR (2011)