Regression explanation and statistical autonomy

Vision-Based Navigation and Deep-Learning Explanation for Autonomy

In this thesis, we investigate vision-based techniques to support robot mobile autonomy in human environments, including also understanding the important image features with respect to a classification task. Given this wide goal of transparent vision-based autonomy, the work proceeds along three main fronts. Our first algorithm enables a UAV to visually localize and navigate with respect to CoB...

Autonomy-based multi-agent systems: statistical issues

This paper describes an autonomy-based multi-agent system and its application to simulations in the framework of collective robotics. Experimental results measured for a particular task, namely object regrouping, have two outcomes. First, they show that a form of implicit cooperation takes place in the system despite the absence of explicit cooperation protocol, but just in virtue of the design...

Asymmetry, abstraction and autonomy: justifying coarse-graining in statistical mechanics

Whilst the fundamental laws of physics are time-reversal invariant, most macroscopic processes are irreversible. Given that the fundamental laws are taken to underpin all other processes, how can the fundamental time-symmetry be reconciled with the asymmetry manifest elsewhere? In statistical mechanics, progress can be made with this question; what I dub the Zwanzig-Zeh-Wallace framework can be...

Wavelets for Regression and Other Statistical Problems

Why Is Linear Quantile Regression Empirically Successful: A Possible Explanation

Many quantities describing the physical world are related to each other. As a result, often, when we know the values of certain quantities x1, . . . , xn, we can reasonably well predict the value of some other quantity y. In many application, in addition to the resulting estimate for y, it is also desirable to predict how accurate is this approximate estimate, i.e., what is the probability dist...