National gender quotas—policies that require a certain percentage of women candidates or legislators—are becoming more effective over time. Using data on 145 countries from 1990 to 2010, we document this trend with latent growth-curve models. Part of the explanation for increasing effectiveness is that countries have ratcheted up targets for women’s inclusion and that quotas are increasingly wr...

background: the phase change materials (pcms) have the appropriate properties for controlling heat strain. one of the well-known pcms is paraffin. this study aimed to design the cooling vest from the cheap commercial paraffin compound and evaluation of its effectiveness under laboratory hot conditions. methods: the cooling vest was made of the polyester fabric and it had 17 aluminum packs. the ...

In this research, we address the problem of retrieving services which fulfil users’ need expressed in query in free text. Our goal is to cope the term mismatch problems which affect the effectiveness of service retrieval models applied in prior research on text descriptionsbased service retrieval models. These problems are caused due to service descriptions are brief. Service providers use few ...

Two important components of a visual recognition system are representation and model. Both involves the selection and learning of the features that are indicative for recognition and discarding those features that are uninformative. This thesis, in its general form, proposes different techniques within the frameworks of two learning systems for representation and modeling. Namely, latent suppor...

Permutations and matchings are core building blocks in a variety of latent variable models, as they allow us to align, canonicalize, and sort data. Learning in such models is difficult, however, because exact marginalization over these combinatorial objects is intractable. In response, this paper introduces a collection of new methods for end-to-end learning in such models that approximate disc...

Unsupervised object matching (UOM) is a promising approach to cross-language natural language processing such as bilingual lexicon acquisition, parallel corpus construction, and cross-language text categorization, because it does not require labor-intensive linguistic resources. However, UOM only finds one-to-one correspondences from data sets with the same number of instances in source and tar...

This paper presents the recurrent estimation of distributions (RED) for modeling real-valued data in a semiparametric fashion. RED models make two novel uses of recurrent neural networks (RNNs) for density estimation of general real-valued data. First, RNNs are used to transform input covariates into a latent space to better capture conditional dependencies in inputs. After, an RNN is used to c...

Disentangling factors of variation has always been a challenging problem in representation learning. Existing algorithms suffer from many limitations, such as unpredictable disentangling factors, bad quality of generated images from encodings, lack of identity information, etc. In this paper, we proposed a supervised algorithm called DNA-GAN trying to disentangle different attributes of images....

Searching images from the World Wide Web in order to know what an object looks like is a very common task. The best response for such a task is to present the most typical image of the object. Existing web-based image search engines, however, return many results that are not typical. In this paper, we propose a method for obtaining typical images through estimating parameters of a generative mo...