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Found 9 papers, 4 papers with code
ERM-KTP: Knowledge-Level Machine Unlearning via Knowledge Transfer
When receiving the unlearning requests, we transfer the knowledge of the non-target data points from the original model to the unlearned model and meanwhile prohibit the knowledge of the target data points via our proposed knowledge transfer and prohibition (KTP) method.
Revisiting Knowledge Distillation under Distribution Shift
Knowledge distillation transfers knowledge from large models into small models, and has recently made remarkable achievements.
SAME: Sample Reconstruction against Model Extraction Attacks
While deep learning models have shown significant performance across various domains, their deployment needs extensive resources and advanced computing infrastructure.
Explaining Adversarial Robustness of Neural Networks from Clustering Effect Perspective
The experimental evaluations manifest the superiority of SAT over other state-of-the-art AT mechanisms in defending against adversarial attacks against both output and intermediate layers.
Privacy Inference Attacks and Defenses in Cloud-based Deep Neural Network: A Survey
This survey presents the most recent findings of privacy attacks and defenses appeared in cloud-based neural network services.
A Two-phase Prototypical Network Model for Incremental Few-shot Relation Classification
Relation Classification (RC) plays an important role in natural language processing (NLP).
Modeling Compositionality with Dependency Graph for Dialogue Generation
Because of the compositionality of natural language, syntactic structure which contains the information about the relationship between words is a key factor for semantic understanding.
Deep Hierarchy Quantization Compression algorithm based on Dynamic Sampling
Unlike traditional distributed machine learning, federated learning stores data locally for training and then aggregates the models on the server, which solves the data security problem that may arise in traditional distributed machine learning.
Publicly Verifiable Databases With All Efficient Updating Operations
As a result, it remains an open problem how to construct an efficient (and publicly verifiable) VDB scheme that can support all updating operations regardless of the manner of insertion.
