SOTAVerified

Data Valuation

Data valuation in machine learning tries to determine the worth of data, or data sets, for downstream tasks. Some methods are task-agnostic and consider datasets as a whole, mostly for decision making in data markets. These look at distributional distances between samples. More often, methods look at how individual points affect performance of specific machine learning models. They assign a scalar to each element of a training set which reflects its contribution to the final performance of some model trained on it. Some concepts of value depend on a specific model of interest, others are model-agnostic.

Concepts of the usefulness of a datum or its influence on the outcome of a prediction have a long history in statistics and ML, in particular through the notion of the influence function. However, it has only been recently that rigorous and practical notions of value for data, and in particular data-sets, have appeared in the ML literature, often based on concepts from collaborative game theory, but also from generalization estimates of neural networks, or optimal transport theory, among others.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 76–100 of 119 papers

TitleStatusHype
Exploring Data Redundancy in Real-world Image Classification through Data SelectionCode0
2D-Shapley: A Framework for Fragmented Data ValuationCode0
Data Selection for Fine-tuning Large Language Models Using Transferred Shapley ValuesCode0
Shapley Value on Probabilistic Classifiers—0
Cooperative IoT Data Sharing with Heterogeneity of Participants Based on Electricity Retail—0
New methods for new data? An overview and illustration of quantitative inductive methods for HRM research—0
Data valuation: The partial ordinal Shapley value for machine learningCode0
Scalable Data Point Valuation in Decentralized LearningCode0
GMValuator: Similarity-based Data Valuation for Generative Models—0
A Note on "Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms"Code0
Optimizing Data Shapley Interaction Calculation from O(2^n) to O(t n^2) for KNN models—0
Fairness-Aware Data Valuation for Supervised Learning—0
Towards Algorithmic Fairness by means of Instance-level Data Re-weighting based on Shapley ValuesCode0
A Note on "Towards Efficient Data Valuation Based on the Shapley Value''—0
IPProtect: protecting the intellectual property of visual datasets during data valuation—0
Probably Approximate Shapley Fairness with Applications in Machine LearningCode0
CS-Shapley: Class-wise Shapley Values for Data Valuation in ClassificationCode0
Variance reduced Shapley value estimation for trustworthy data valuationCode0
Towards More Efficient Data Valuation in Healthcare Federated Learning using Ensembling—0
To Store or Not? Online Data Selection for Federated Learning with Limited Storage—0
Fundamentals of Task-Agnostic Data Valuation—0
LIA: Privacy-Preserving Data Quality Evaluation in Federated Learning Using a Lazy Influence Approximation—0
Data Valuation for Offline Reinforcement Learning—0
CheckSel: Efficient and Accurate Data-valuation Through Online Checkpoint Selection—0
Incentivizing Collaboration in Machine Learning via Synthetic Data RewardsCode0
Show:102550
← PrevPage 4 of 5Next →

No leaderboard results yet.