Abstract: The seminar will focus on the scientific and innovation activities of two projects currently underway at the University of Southampton (i) QROWD is an innovation action sponsored by the Horizon2020 programme focused on integrating humans into the Big Data value chain, particularly for the case of smart urban transportation. We will examine two tools…
Abstract: The data society we live in offers unprecedented opportunities to exploit available data. The goal of _data mining_ is precisely to extract useful information from available data and assist in e.g., decision-making or event-prediction. In doing so, available data usually contain sensitive information about individuals, and releasing even _aggregate_ information about a set of…
Abstract: The Gaussian process (GP) is a probabilistic model for functions. Unique advantages of the GP are its generality, the fact training and prediction can be performed analytically, and its ability to represent uncertainty. In this talk, we first present the concept of a generative model to introduce the probabilistic perspective to Machine Learning, then,…
Abstract: Workshop that brings together all researchers and collaborators of the Millennium Institute for Foundational Research on Data (IMFD). The Flagship Projects will be presented, cross-cutting themes that seek to maximize the social impact of our center’s research areas. In addition, the cross-cutting principles of the institute’s work, their purpose and objective, and the challenges…
Abstract: Consider Markov Decision Processes (MDPs) and 2-player turn-based stochastic games on countably infinite game graphs, with objectives expressible by parity conditions (including special cases like reachability, safety, Buchi and co-Buchi objectives). We give an overview of results about the determinacy (for games) and about the memory requirements of epsilon-optimal and optimal strategies, respectively (for…
Abstract: We propose an algorithm based on infeasible irreducible subsystems (IIS) to solve general binary chance-constrained problems. By leveraging on the problem structure we are able to generate good quality upper bounds to the optimal value early in the algorithm, and the discrete domain is used to guide us efficiently in the search of solutions….
Abstract: Today we have access to a large amount of data, coming from different sources and presenting different characteristics. For example, we have multiple geographic representations: maps, satellite images, vector databases, among others. Users of geographic information systems need to combine and compare these heterogeneous representations of the same region. For example, to keep the…
Abstract: Self-determination (SD) disputes are some of the most common conflicts in the world. Around a third of the civil wars in the last decades relate to demands for increased autonomy or independence (Sambanis and Milanovic, 2014). While the literature has mainly focused on the most violent conflicts, such as civil wars, recent studies have…
Abstract: Coq is a very popular proof assistant, used in a variety of academic and industrial projects, for formalizing both computer science results as well as mathematical ones. Coq is based on a theoretically very clean model, the Calculus of Inductive Constructions, which allows to express all of mathematics in a constructive manner. Following the…
Abstract: With a new generation of large etendue (the product of field of view and mirror area) survey telescopes there is a growing need for astronomical alert processing systems. Astronomical alerts correspond to detected changes in the sky with an astrophysical origin. Astronomical alert processing systems involve the real–time processing of data for alert generation,…
Abstract: Many practical problems can be reduced recursively to smaller or simpler instances, down to the base cases. Most often, a straightforward implementation of such reduction fails to yield a solution running in reasonable time. In many cases it is Dynamic Programming which yields solutions of industrial value, based on an adequate tuning of the…
Abstract: An instance of the constraint satisfaction problem (CSP) is given by a family of constraints on overlapping sets of variables, and the goal is to assign values from a fixed domain to the variables so that all constraints are satisfied. In the optimization version, the goal is to maximize the number of satisfied constraints…
Abstract: The Propaganda Model (PM) discussed in Manufacturing Consent is a theory in political economy that states that the mass media are channels through which governments and major power groups pass down certain ideologies and mold a general consent according to their own interests. According to the authors, every piece of news has gone through…