Agenda Eventos

ABSTRACT. Information Retrieval and Recommender Systems have been frequently evaluated using indexes based on variants and extensions of precision-like measures. Likewise, approaches for diversity evaluation have been proposed. However, these measures are usually defined in terms of a set of high level content descriptors known as \textit{information nuggets} that are hard to obtain. We propose…

ABSTRACT: Latent Dirichlet Allocation (LDA) is a fundamental method in the text mining field. We propose strategies for topic and model selection based on LDA that exploits the semantic coherence of the topics inferred, boosting the quality of the models found. Then we study how our boosted topic models perform in ad-hoc information retrieval tasks….

Invited by IMFD, Sheila McIlraith will be present at the 2018 Chilean Computer Congress. Sheila McIlraith is a Professor in the Department of Computer Science, University of Toronto. Prior to joining U of T in 2004, McIlraith spent six years as a Research Scientist at Stanford University, and one year at Xerox PARC. McIlraith is…

Promover el ingreso de mujeres a carreras ligadas a la informática, así como visibilizar su quehacer e investigaciones en el área, son algunos de los objetivos del VII Chile WIC “Encuentro Chileno de Mujeres en Computación”, actividad organizada por la Universidad Técnica Federico Santa María -a través de su Departamento de Informática- junto con las…

Abstract: In Latin America, shopping malls seem to offer and open, safe and democratic version of the public space. However, it is often difficult to quantitatively measure whether they indeed foster, hinder or are neutral with respect to social inclusion. In this talk we present that, by using mobile phone network records, we can provide…

Abstract: Many optimization problems are NP-hard and therefore we do not expect to find algorithms for them that are efficient, i.e., run in polynomial time, and find the optimal solution for any given instance. Therefore, we are interested in approximation algorithms which are algorithms that run in polynomial time and provably find solutions that differ…

Abstract: Usualmente asumimos que en una democracia moderna las personas poseen acceso a derechos básicos de ciudadanía civil, política y social. Sin dicho acceso, la agencia democrática se vuelve problemática. En base a datos de la encuesta LAPOP, y al trabajo con más de 100 mil observaciones para el período 2012-2016, Juan Pablo Luna y…

Abstract: There is an increasingly pressing need, by several applications in diverse domains, for developing techniques able to index and mine very large collections of sequences, or data series. Examples of such applications come from social media analytics and internet service providers, as well as from a multitude of scientific domains. It is not unusual…

Abstract: Esta charla presentará tres principios básicos que rigen la creación y difusión del conocimiento: el principio de la experiencia, el principio de la similitud (relatedness), y el principio de la intensidad del conocimiento. Construyendo sobre estas ideas se discutirán estrategias y canales de difusión de conocimiento. Finalmente, se presentarán herramientas de integración, distribución, y visualización…

Abstract: El seminario versará sobre las actividades científicas y de innovación de dos proyectos actualmente en ejecución en la Universidad de Southampton (i) QROWD es una acción innovación patrocinada por el programa Horizon2020 enfocado en la integración de humanos en la cadena de valor de Big Data, en particular para el caso de transporte urbano…

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 que reúne a todos los investigadores y colaboradores del Instituto Milenio Fundamentos de los Datos. Se presentarán los Proyectos Emblemáticos, ejes transversales que buscan maximizar el impacto social de las áreas de investigación de nuestro centro. Además, se presentarán los principios transversales del trabajo del instituto, su sentido y objetivo, y los desafíos…

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 MDPs…

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….