AI-secure / KNN-PVLDBLinks
Official Repo for "Efficient task-specific data valuation for nearest neighbor algorithms"
☆26Updated 5 years ago
Alternatives and similar repositories for KNN-PVLDB
Users that are interested in KNN-PVLDB are comparing it to the libraries listed below
Sorting:
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆41Updated 2 years ago
- [CVPR 2021] Scalability vs. Utility: Do We Have to Sacrifice One for the Other in Data Importance Quantification?☆33Updated 4 years ago
- PyTorch reimplementation of computing Shapley values via Truncated Monte Carlo sampling from "What is your data worth? Equitable Valuatio…☆27Updated 3 years ago
- ☆44Updated 5 years ago
- Distributional Shapley: A Distributional Framework for Data Valuation☆30Updated last year
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- ModelDiff: A Framework for Comparing Learning Algorithms☆59Updated 2 years ago
- This code reproduces the results of the paper, "Measuring Data Leakage in Machine-Learning Models with Fisher Information"☆50Updated 4 years ago
- Learning perturbation sets for robust machine learning☆65Updated 4 years ago
- ☆37Updated 2 years ago
- A simple algorithm to identify and correct for label shift.☆22Updated 7 years ago
- [ICML 2024] Codes for C-RAG: Certified Generation Risks for Retrieval-Augmented Language Models☆19Updated last year
- Quantile risk minimization☆24Updated last year
- Computationally friendly hyper-parameter search with DP-SGD☆26Updated 9 months ago
- Code and results accompanying our paper titled RLSbench: Domain Adaptation under Relaxed Label Shift☆35Updated 2 years ago
- Contains notebooks for the PAR tutorial at CVPR 2021.☆36Updated 4 years ago
- Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation", Haoxi…☆68Updated 3 years ago
- Parameter-Space Saliency Maps for Explainability☆23Updated 2 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆132Updated 5 years ago
- An amortized approach for calculating local Shapley value explanations☆100Updated last year
- ☆38Updated 4 years ago
- Measuring data importance over ML pipelines using the Shapley value.☆43Updated last month
- [NeurIPS 2020] Coresets for Robust Training of Neural Networks against Noisy Labels☆35Updated 4 years ago
- A collection of algorithms of counterfactual explanations.☆50Updated 4 years ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆36Updated last year
- Recycling diverse models☆45Updated 2 years ago
- Active and Sample-Efficient Model Evaluation☆24Updated 4 months ago
- OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)☆99Updated 8 months ago
- ☆38Updated 4 years ago
- Source code of "Hold me tight! Influence of discriminative features on deep network boundaries"☆21Updated 3 years ago