Background: Statistical mechanics results (Dauphin et al. (2014); Choromanska et al. (2015)) suggest that local minima with high error are exponentially rare in high dimensions. However, to prove low error guarantees for Multilayer Neural Networks (MNNs), previous works so far required either a heavily modified MNN model or training method, strong assumptions on the labels (e.g., “near” linear ...

A k nearest neighbor (kNN) classifier classifies a query instance to the most frequent class of its k nearest neighbors in the training instance space. For imbalanced class distribution, a query instance is often overwhelmed by majority class instances in its neighborhood and likely to be classified to the majority class. We propose to identify exemplar minority class training instances and gen...

The classical k nearest neighbor (k-nn) classification assumes that a fixed global metric is defined and searching for nearest neighbors is always based on this global metric. In the paper we present a model with local induction of a metric. Any test object induces a local metric from the neighborhood of this object and selects k nearest neighbors according to this locally induced metric. To in...

This work deals with the influence of neighborhood in simple rock–paper–scissors models biodiversity. We consider case three distinct species which evolve under standard rules mobility, reproduction and competition. The rule competition follows guidance game, prey being annihilated, leaving an empty site accordance May-Leonard proposal for predator use von Neumann neighborhood, but we mobility ...

Unlike traditional classification tasks, multilabel classification allows a sample to associate with more than one label. This generalization naturally arises the difficulty in classification. Similar to the single label classification task, neighborhood-based algorithms relying on the nearest neighbor have attracted lots of attention and some of them show positive results. In this paper, we pr...

Objective. The possible effect of blood pressure measurements per se on heart rate variability (HRV) was studied in the setting of concomitant ambulatory blood pressure monitoring (ABPM) and Holter ECG monitoring (HM). Methods. In 25 hypertensive patients (14 women and 11 men, mean age: 58.1 years), 24-hour combined ABPM and HM were performed. For every blood pressure measurement, 2-minute ECG ...

BACKGROUND In chronic Chagas disease (ChD), impairment of cardiac autonomic function bears prognostic implications. Phase‑rectification of RR-interval series isolates the sympathetic, acceleration phase (AC) and parasympathetic, deceleration phase (DC) influences on cardiac autonomic modulation. OBJECTIVE This study investigated heart rate variability (HRV) as a function of RR-interval to ass...

This work introduces Mutual Proximity, an unsupervised method which transforms arbitrary distances to similarities computed from the shared neighborhood of two data points. This reinterpretation aims to correct inconsistencies in the original distance space, like the hub phenomenon. Hubs are objects which appear unwontedly often as nearest neighbors in predominantly high-dimensional spaces. We ...

Electromyographic (EMG) signal provide a significant source of information for diagnosis, treatment and management of neuromuscular disorders.Neuromuscular diseases changes, the shape and characteristics of the motor unit action potentials (MUAPs). The MUAPs detected from myopathic patients are characterized by high frequency contents, low peak-to-peak amplitude and MUAPs neuropathic patients a...