This paper studies the problem of estimating geographical locations of images. To build reliable geographical estimators, an important question is to find distinguishable geographical clusters in the world. Those clusters cover general geographical regions and are not limited to landmarks. The geographical clusters provide more training samples and hence lead to better recognition accuracy. Pre...

We extend dynamic generalized structured component analysis (GSCA) to enhance its data-analytic capability in structural equation modeling of multi-subject time series data. Time series data of multiple subjects are typically hierarchically structured, where time points are nested within subjects who are in turn nested within a group. The proposed approach, named multilevel dynamic GSCA, accomm...

This paper develops a novel iterative framework for subspace clustering (SC) in a learned discriminative feature domain. This framework consists of two modules of fuzzy sparse SC and discriminative transformation learning. In the first module, fuzzy latent labels containing discriminative information and latent representations capturing the subspace structure will be simultaneously evaluated in...

The rapid development of social media services has facilitated the communication of opinions throughonlinenews, blogs,microblogs/tweets, instant-messages, and so forth. This article concentrates on the mining of readers’ emotions evoked by social media materials. Compared to the classical sentiment analysis from writers’ perspective, sentiment analysis of readers is sometimes more meaningful in...

In this paper we propose a robust probabilistic multivariate calibration (RPMC) model in an attempt to identify linear relationships between two sets of observed variables contaminated with outliers. Instead of the Gaussian assumptions that predominate in classical statistical models, RPMC is closely related with the multivariate Student's t-distribution over noises and latent variables. As a r...

Right to Information (RTI) Act, 2005 empowers citizens of India to access information from any governmental organization. Using this Act citizens can ask questions (through RTI applications/queries) to government offices and obtain answers. In this work we attempt to model RTI queries. Objective of modeling is to understand the latent patterns such as transparency and effectiveness of RTI Act i...

A large body of crowdsourcing research focuses on using techniques from artificial intelligence to improve estimates of latent answers to questions, assuming fixed (latent) worker quality. Recently, researchers have begun to investigate how best to actively improve worker quality through instruction (Basu & Christensen, 2013; Singla et al., 2014). However, none of the existing work considers th...

Restricted Boltzmann Machines (RBMs) are one of the fundamental building blocks of deep learning. Approximate maximum likelihood training of RBMs typically necessitates sampling from these models. In many training scenarios, computationally efficient Gibbs sampling procedures are crippled by poor mixing. In this work we propose a novel method of sampling from Boltzmann machines that demonstrate...