ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1707.01212
  4. Cited By
Efficient Data Representation by Selecting Prototypes with Importance
  Weights
v1v2v3v4 (latest)

Efficient Data Representation by Selecting Prototypes with Importance Weights

5 July 2017
Karthik S. Gurumoorthy
Amit Dhurandhar
Guillermo Cecchi
Charu Aggarwal
ArXiv (abs)PDFHTML

Papers citing "Efficient Data Representation by Selecting Prototypes with Importance Weights"

10 / 10 papers shown
Explainable AI for clinical risk prediction: a survey of concepts,
  methods, and modalities
Explainable AI for clinical risk prediction: a survey of concepts, methods, and modalities
Munib Mesinovic
Peter Watkinson
Ting Zhu
FaML
300
9
0
16 Aug 2023
Analogies and Feature Attributions for Model Agnostic Explanation of
  Similarity Learners
Analogies and Feature Attributions for Model Agnostic Explanation of Similarity Learners
Karthikeyan N. Ramamurthy
Amit Dhurandhar
Dennis L. Wei
Zaid Bin Tariq
FAtt
280
3
0
02 Feb 2022
A Survey on the Explainability of Supervised Machine Learning
A Survey on the Explainability of Supervised Machine LearningJournal of Artificial Intelligence Research (JAIR), 2020
Nadia Burkart
Marco F. Huber
FaMLXAI
431
928
0
16 Nov 2020
Sequential Explanations with Mental Model-Based Policies
Sequential Explanations with Mental Model-Based Policies
A. Yeung
Shalmali Joshi
Joseph Jay Williams
Frank Rudzicz
FAttLRM
282
16
0
17 Jul 2020
Interpretable Counterfactual Explanations Guided by Prototypes
Interpretable Counterfactual Explanations Guided by Prototypes
A. V. Looveren
Janis Klaise
FAtt
450
460
0
03 Jul 2019
Model Agnostic Contrastive Explanations for Structured Data
Model Agnostic Contrastive Explanations for Structured Data
Amit Dhurandhar
Tejaswini Pedapati
Avinash Balakrishnan
Pin-Yu Chen
Karthikeyan Shanmugam
Ruchi Puri
FAtt
348
93
0
31 May 2019
Leveraging Latent Features for Local Explanations
Leveraging Latent Features for Local ExplanationsKnowledge Discovery and Data Mining (KDD), 2019
Ronny Luss
Pin-Yu Chen
Amit Dhurandhar
P. Sattigeri
Yunfeng Zhang
Karthikeyan Shanmugam
Chun-Chen Tu
FAtt
375
37
0
29 May 2019
Streaming Methods for Restricted Strongly Convex Functions with
  Applications to Prototype Selection
Streaming Methods for Restricted Strongly Convex Functions with Applications to Prototype Selection
Karthik S. Gurumoorthy
Amit Dhurandhar
160
0
0
21 Jul 2018
Explanations based on the Missing: Towards Contrastive Explanations with
  Pertinent Negatives
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives
Amit Dhurandhar
Pin-Yu Chen
Ronny Luss
Chun-Chen Tu
Pai-Shun Ting
Karthikeyan Shanmugam
Payel Das
FAtt
505
664
0
21 Feb 2018
TIP: Typifying the Interpretability of Procedures
TIP: Typifying the Interpretability of Procedures
Amit Dhurandhar
Vijay Iyengar
Ronny Luss
Karthikeyan Shanmugam
367
35
0
09 Jun 2017
1
Page 1 of 1