Online convex optimization is a sequential prediction framework with the goal to track and adapt to the environment through evaluating proper convex loss functions. We study efficient particle filtering methods from the perspective of such framework. We formulate an efficient particle filtering methods for non-stationary environment by making connections with the online mirror descent algorithm...

Data quality is a recognized problem for high-throughput genomics platforms, as evinced by the proliferation of methods attempting to filter out lower quality data points. Different filtering methods lead to discordant results, raising the question, which methods are best? Astonishingly, little computational support is offered to analysts to decide which filtering methods are optimal for the re...

There are many recommendation systems available to provide users with personalized services. Among them, the most frequently used in electronic commerce is ‘collaborative filtering’, which is a technique that provides a process of filtering customer information for the preparation of profiles and making recommendations of products that are expected to be preferred by other users, based on such ...

This paper investigates the effect of prior feature selection in Support Vector Machine (SVM) text categorization. The input space was gradually increased by using mutual information (MI) filtering and part-of-speech (POS) filtering, which determine the portion of words that are appropriate for learning from the information-theoretic and the linguistic perspectives, respectively. We tested the ...

In view of the images polluted by mixed noise in actual image processing, in this paper, the hybrid filter algorithm combined by median filtering and wavelet transform is generalized to two-dimensional fractional wavelet domain, verified the effectiveness and advantages of hybrid filtering algorithm combined by median filtering and two-dimensional fractional wavelet transform. And put forward a...

The perfomance of a class of communication systems is investigated in a probabilistic framework. We investigate the bit error probability of the optimal as well as approximately optimal receivers. In general the latter turn out to be unavoidable due to the computational complexity of the former. We investigate a certain class of communication schemes including chaotic systems. Nonlinear filteri...

 Feature Selection “Tomography” Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable