Artificial neural networks are a popular and effective machine learning technique. Great progress has been made on speeding up the expensive training phase of a neural networks, leading to highly specialized pieces of hardware, many based on GPU-type architectures, and more concurrent algorithms such as synthetic gradients. However, the training phase continues to be a bottleneck, where the tra...

We introduce the effectual topological complexity (ETC) of a [Formula: see text]-space text]. This is text]-equivariant homotopy invariant sitting in between effective pair text] and (regular) orbit space study ETC for spheres surfaces with antipodal involution, obtaining full computation case torus. allows us to prove vanishing twice nontrivial obstruction responsible fact that Klein bottle In...

The speed of iterative solvers for discretizations of partial differential equations (PDEs) is a significant bottleneck in the performance of codes designed to solve large-scale electromagnetic inverse problems. A single data inversion requires solving Maxwell’s equations dozens if not hundreds of times. An inherent difficulty in geophysical contexts is that the conductivity and permeability co...

This study examined the effectiveness of teaching methods used with a second language reading and writing unit. This investigation addressed discrepancies between assessment scores in the four communicative language skill areas of students in beginning-level Spanish classes at a suburban middle school. Accordingly, the purpose of this study was to explore how literacy-based practices that inclu...

The growing adoption of IT-systems for modeling and executing (business) processes or services has thrust the scientific investigation towards techniques and tools which support more complex forms of process analysis. Many of them, such as conformance checking, process alignment, mining and enhancement, rely on complete observation of past (tracked and logged) executions. In many real cases, ho...

We propose a new way of deriving policy gradient updates for reinforcement learning. Our technique, based on Fourier analysis, recasts integrals that arise with expected policy gradients as convolutions and turns them into multiplications. The obtained analytical solutions allow us to capture the low variance benefits of EPG in a broad range of settings. For the critic, we treat trigonometric a...

We characterize the feature superset of Collaborative Virtual Reality Environments (CVREs) out of existing implementations, and derive a novel component framework for transforming standalone VR tools into full-fledged multithreaded collaborative environments. The contributions of our approach rely on cost-effective techniques for loading graphics rendering, user interaction and network communic...

The design of an experiment can greatly affect its potential to produce statistically conclusive results. In this paper, we offer a method for increasing the statistical informativeness of an experiment through the use of adaptive design optimization. The problem to be solved in adaptive design optimization is identifying an experimental design under which one can infer the underlying model and...