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Found 16 papers, 2 papers with code
Enhancing Self-Attention with Knowledge-Assisted Attention Maps
Large-scale pre-trained language models have attracted extensive attentions in the research community and shown promising results on various tasks of natural language processing.
Novel models for fatigue life prediction under wideband random loads based on machine learning
Machine learning as a data-driven solution has been widely applied in the field of fatigue lifetime prediction.
Explore the Effect of Data Selection on Poison Efficiency in Backdoor Attacks
In this study, we focus on improving the poisoning efficiency of backdoor attacks from the sample selection perspective.
AutoHint: Automatic Prompt Optimization with Hint Generation
This paper presents AutoHint, a novel framework for automatic prompt engineering and optimization for Large Language Models (LLM).
A Proxy Attack-Free Strategy for Practically Improving the Poisoning Efficiency in Backdoor Attacks
To address these concerns, we present a Proxy attack-Free Strategy (PFS) designed to identify efficient poisoning samples based on the similarity between clean samples and their corresponding poisoning samples, as well as the diversity of the poisoning set.
Efficient Backdoor Attacks for Deep Neural Networks in Real-world Scenarios
However, existing backdoor attack methods make unrealistic assumptions, assuming that all training data comes from a single source and that attackers have full access to the training data.
A scalable approach for developing clinical risk prediction applications in different hospitals
We applied the model calibration process at four hospitals, and generated risk prediction models for delirium, sepsis and acute kidney injury (AKI) respectively at each of these hospitals.
AutoADR: Automatic Model Design for Ad Relevance
We add the model designed by AutoADR as a sub-model into the production Ad Relevance model.
Mixed Noise Removal with Pareto Prior
To address this problem, we exploit the Pareto distribution as the priori of the weighting matrix, based on which an accurate and robust weight estimator is proposed for mixed noise removal.
A Dual Sparse Decomposition Method for Image Denoising
This method makes a sub-dictionary decomposition on the over-complete dictionary in the sparse decomposition.
Sar image despeckling based on nonlocal similarity sparse decomposition
This method combines the nonlocal self-similarity partition and a proposed modified sparse decomposition.
Sparse Signal Subspace Decomposition Based on Adaptive Over-complete Dictionary
This method makes use of a novel criterion based on the occurrence frequency of atoms of the dictionary over the data set.
Principal Basis Analysis in Sparse Representation
This article introduces a new signal analysis method, which can be interpreted as a principal component analysis in sparse decomposition of the signal.
The Missing Ones: Key Ingredients Towards Effective Ambient Assisted Living Systems
Challenges in increasing the human participation in ambient assisted living are discussed in this paper and solutions to meet those challenges are also proposed.
Validation Rules for Assessing and Improving SKOS Mapping Quality
The Simple Knowledge Organization System (SKOS) is popular for expressing controlled vocabularies, such as taxonomies, classifications, etc., for their use in Semantic Web applications.
