Recently, an increasing number of laws have governed the useability of users' privacy. For
example, Article 17 of the General Data Protection Regulation (GDPR), the right to be …

Today, computer systems hold large amounts of personal data. Yet while such an
abundance of data allows breakthroughs in artificial intelligence, and especially machine …

Even before the perception or interaction with pathogens, plants rely on constitutively
guardian molecules, often specific to tissue or stage, with further expression after contact …

We study the problem of unlearning datapoints from a learnt model. The learner first
receives a dataset $ S $ drawn iid from an unknown distribution, and outputs a model …

Support vector ordinal regression (SVOR) is a popular method to tackle ordinal regression
problems. However, until now there were no effective algorithms proposed to address …

Abstract The ν-Support Vector Regression (ν-SVR) is an effective regression learning
algorithm, which has the advantage of using a parameter ν on controlling the number of …

With the growing demand for the right to be forgotten, there is an increasing need for
machine learning models to forget sensitive data and its impact. To address this, the …

With the greater emphasis on privacy and security in our society, the problem of graph
unlearning—revoking the influence of specific data on the trained GNN model, is drawing …

Cloud and Fog computing has emerged as a promising paradigm for the Internet of things
(IoT) and cyber–physical systems (CPS). One characteristic of CPS is the reciprocal …

Uncertainty and fuzziness generally exist in real-life data. Approximations are employed to
describe the uncertain information approximately in rough set theory. Certain and uncertain …