6 accepted papers
Micromanipulation techniques struggle to achieve three-dimensional rotational control at the microscale without compromising biocompatibility or spatial flexibility. Conventional methods based on mechanical contact, optical forces, or confined microfluidics constrain dynamic reconfiguration and surg
Conformal prediction (CP) has gained prominence as a popular technique for uncertainty quantification in deep neural networks (DNNs), providing statistically rigorous uncertainty sets. However, existing CP methods fail to clarify the origins of predictive uncertainties. While neuron-level interpreta…
As a new paradigm to erase data from a model and protect user privacy, machine unlearning has drawn significant attention. However, existing studies on machine unlearning mainly focus on its effectiveness and efficiency, neglecting the security challenges introduced by this technique. In this paper,…
This paper focuses on a newly challenging setting in hard-label adversarial attacks on text data by taking the budget information into account. Although existing approaches can successfully generate adversarial examples in the hard-label setting, they follow an ideal assumption that the victim model…
Providing model explanations has gained significant popularity recently. In contrast with the traditional feature-level model explanations, concept-based explanations can provide explanations in the form of high-level human concepts. However, existing concept-based explanation methods implicitly fol…
In collaborative machine learning(CML), multiple agents pool their resources(e.g., data) together for a common learning task. In realistic CML settings where the agents are self-interested and not altruistic, they may be unwilling to share data or model information without adequate rewards. Furtherm…