Frequentist statistical methods, such as hypothesis testing, are standard practice in papers that provide benchmark comparisons. Unfortunately, these methods have often been misused, e.g., without testing for their test assumptions or controlling family-wise errors multiple group comparisons, among several other problems. Bayesian Data Analysis (BDA) addresses many of the previously mentioned s...

We propose a novel search-based approach for greedy coreference resolution, where the mentions are processed in order and added to previous coreference clusters. Our method is distinguished by the use of two functions to make each coreference decision: a pruning function that prunes bad coreference decisions from further consideration, and a scoring function that then selects the best among the...

We address the problem of designing surrogate losses for learning scoring functions in the context of label ranking. We extend to ranking problems a notion of orderpreserving losses previously introduced for multiclass classification, and show that these losses lead to consistent formulations with respect to a family of ranking evaluation metrics. An order-preserving loss can be tailored for a ...

We present a combinatorial method for discovering cis-regulatory modules in promoter sequences. Our approach combines “sliding window” approaches with a scoring function based on the so-called Tanimoto score. This allows to identify sets of binding sites that tend to occur preferentially in the vicinity of each other in a given set of promoter sequences belonging to co-expressed or orthologous ...

In this paper the performance of Multi-chaotic PSO algorithm is investigated using two shifted benchmark functions. The purpose of shifted benchmark functions is to simulate the time-variant real-world problems. The results of chaotic PSO are compared with canonical version of the algorithm. It is concluded that using the multi-chaotic approach can lead to better results in optimization of shif...

Test functions are important to validate and compare the performance of optimization algorithms. There have been many test or benchmark functions reported in the literature; however, there is no standard list or set of benchmark functions. Ideally, test functions should have diverse properties so that can be truly useful to test new algorithms in an unbiased way. For this purpose, we have revie...

a new meta-heuristic method, based on neuronal communication (nc), is introduced in this article. the neuronal communication illustrates how data is exchanged between neurons in neural system. actually, this pattern works efficiently in the nature. the present paper shows it is the same to find the global minimum. in addition, since few numbers of neurons participate in each step of the method,...