We present a scalable, generative framework for multi-label learning with missing labels. Our framework consists of a latent factor model for the binary label matrix, which is coupled with an exposure model to account for label missingness (i.e., whether a zero in the label matrix is indeed a zero or denotes a missing observation). The underlying latent factor model also assumes that the low-di...

ERP implementation projects have been encountered as very risky and complex, and frequently exhibit time and cost overruns. Therefore both a comparison of their efficiency, and especially an estimation of effort and costs associated with new projects are of high interest. Since ERP implementation differs from classical software development projects, as the main focus lies on adapting and custom...

The spatio-temporal analysis of residential fires could allow decision makers to plan effective resource allocations in fire management according to fire clustering levels in space and time. In this study, we provide guidelines for the use of various methods in detecting the differences in clustering patterns of fire and non-fire (i.e., background residential) locations and how these patterns c...

Computing value of information (VOI) is a crucial task in various aspects of decision-making under uncertainty, such as in meta-reasoning for search; in selecting measurements to make, prior to choosing a course of action; and in managing the exploration vs. exploitation tradeoff. Since such applications typically require numerous VOI computations during a single run, it is essential that VOI b...

As the proliferation of compressed video sequences in MPEG formats continues, the ability to perform video analysis directly in the compressed domain becomes increasingly attractive. The availability of motion vectors and pixel values in coded forms can indirectly provide motion and intensity information for object analysis, avoiding the need to re-perform motion estimation. Albeit that the emb...

This paper describes a stereo visual odometry system for volcanic fields which lack visual features on the ground. There are several technical problems in untextured terrain including the diversity of terrain appearance, the lack of welltracked features on surfaces, and the limited computational resources of onboard computers. This paper tries to address these problems and enable efficient and ...

Until now, existing camera pose estimation methods for the widely used square marker-based augmented reality (AR) are either highly sensitive to noise or much time consuming, and developers have to work hard to find the proper trade-off between computational speed and quality in mobile AR applications where computational resources are limited. The major difficulty is that only the 4 corner poin...

In this work a new approach for parameter estimation which is based upon decomposing the problem into two sub-problems is proposed, the first sub-problem generates an Artificial Neural Network (ANN) model from the given data and then the second sub-problem uses the ANN model to obtain an estimate of the parameters. The analytical derivates from the ANN model obtained from the first sub-problem ...

Many software cost estimation models suggest a one-size-fit-all effort distribution patterns as the basis of their guidelines for resource allocation on software development activities. This set of distribution percentages is generally developed from experiences with limited data support. In this paper, we will examine a set of real world data points and share our findings that uncover the sign...

Motion estimation is still the step in a video coding scheme that requires the largest part of the available computational resources. Many paths have been tried to reduce the computational complexity of the motion estimation step. Here we will describe how it can be reduced for log-search motion estimation by a simple change of search strategy. We will also examine how multiple search paths inf...