In this paper, we propose a multi-class classification method using kernel supports and a
dynamical system under differential privacy. For small datasets, kernel methods, such as …

We investigated the performance of parametric and non-parametric methods concerning the
in-sample pricing and out-of-sample prediction performances of index options. Comparisons …

Memory-based collaborative filtering (CF) makes recommendations based on a collection of
user preferences for items. The idea underlying this approach is that the interests of an …

Financial models with stochastic volatility or jumps play a critical role as alternative option
pricing models for the classical Black–Scholes model, which have the ability to fit different …

Sentiment analysis, which detects the subjectivity or polarity of documents, is one of the
fundamental tasks in text data analytics. Recently, the number of documents available online …

Recently, there has been much interest around multitask learning (MTL) problem with the
constraints that tasks should share a common sparsity profile. Such a problem can be …

As an important boundary-based clustering algorithm, support vector clustering (SVC) can
benefit many real applications owing to its capability of handling arbitrary cluster shapes …

Active learning, one of large and important branches in machine learning and data mining,
aims to build an accurate learning model with a relatively small number of labeled points …

Support vector clustering (SVC) is an important boundary-based clustering algorithm in
multiple applications for its capability of handling arbitrary cluster shapes. However, SVC's …

This study aims to alleviate the trade-off between utility and privacy of differentially private
clustering. Existing works focus on simple methods, which show poor performance for non …