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Found 8 papers, 2 papers with code
Cross-silo Federated Learning with Record-level Personalized Differential Privacy
Federated learning enhanced by differential privacy has emerged as a popular approach to better safeguard the privacy of client-side data by protecting clients' contributions during the training process.
Prompt Valuation Based on Shapley Values
Large language models (LLMs) excel on new tasks without additional training, simply by providing natural language prompts that demonstrate how the task should be performed.
Shapley Value on Probabilistic Classifiers
Data valuation has become an increasingly significant discipline in data science due to the economic value of data.
Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding
Knowledge Graph Embedding (KGE) is a fundamental technique that extracts expressive representation from knowledge graph (KG) to facilitate diverse downstream tasks.
Projected Federated Averaging with Heterogeneous Differential Privacy
The challenge is how to use such information without biasing the joint model.
PGLP: Customizable and Rigorous Location Privacy through Policy Graph
Third, we design a private location trace release framework that pipelines the detection of location exposure, policy graph repair, and private trajectory release with customizable and rigorous location privacy.
Cryptography and Security Computers and Society
Absolute Shapley Value
In cooperative game theory, the marginal contribution of each contributor to each coalition is a nonnegative value.
Visually-aware Recommendation with Aesthetic Features
While recent developments on visually-aware recommender systems have taken the product image into account, none of them has considered the aesthetic aspect.
