Abstract High-dimensionality is a common hurdle in machine learning and pattern classification; mitigating its effects has attracted extensive research efforts. It been found recent NeurIPS paper that, when the data possesses low effective dimension, predictive performance of discriminative quadratic classifier with nuclear norm regularisation enjoys reduced (logarithmic) dependence on ambient ...

In this paper, we propose an adaptive p-persistent MAC scheme, named QDA-MAC (QoS differentiation based adaptive MAC scheme), for WLAN to maximize the channel utilization and provide the service differentiation among different traffic stations. Specifically, different from the previous works, the proposed scheme does not need to estimate the number of active stations for each priority class and...

We propose a new automaton model, called quantified data automata over words, that can model quantified invariants over linear data structures, and build poly-time active learning algorithms for them, where the learner is allowed to query the teacher with membership and equivalence queries. In order to express invariants in decidable logics, we invent a decidable subclass of QDAs, called elasti...

PURPOSE Use of accelerometers to assess physical activity (PA) is widespread in public health research, but their utility is often limited by the accuracy of data-processing techniques. We hypothesized that more sophisticated approaches to data processing could distinguish between activity types based on accelerometer data, providing a more accurate picture of PA. METHODS Using data from MTI ...

This paper explores “on-the-fly” data cleaning in the context of a user query. A novel Query-Driven Approach (QDA) is developed that performs a minimal number of cleaning steps that are only necessary to answer a given selection query correctly. The comprehensive empirical evaluation of the proposed approach demonstrates its significant advantage in terms of efficiency over traditional techniqu...

Identification of functional motifs in a DNA sequence is fundamentally a statistical pattern recognition problem. Discriminant analysis is widely used for solving such problems. This paper will review two basic parametric methods: LDA (linear discriminant analysis) and QDA (quadratic discriminant analysis). Their usage in recognition of splice sites and exons in the human genome will be demonst...

Supercritical carbon dioxide + ethanol (SC-CO2+EtOH) extraction, was employed as a deflavoring method to improve the sensory properties of pea flours. Furthermore, impacts particle size along with extraction on volatile profile and attributes flours were investigated using multiple approaches. These included headspace solid-phase microextraction-gas chromatography (HS-SPME-GC), GC-olfactometry ...

Gender determination is the first step for biological identification. With widespread use of machine learning algorithms (MLA) diagnosis, significance applying them also in gender studies has become apparent. This study therefore aimed at determining from parameters obtained out magnetic resonance images (MRI) cranio-cervical junction and cervical-spinal canal by using MLA. MRI craniocervical 1...