Intelligent Systems Group

  • Increase font size
  • Default font size
  • Decrease font size
Intelligent Systems Group

Prizes -- Spanish Conference on Artificial Intelligence


Two members of our group, Momo Hernandez and Josu Ceberio, have been awarded with different prizes in the Spanish Conference on Artificial Intelligence:

The following work received the prize of the "best PhD student paper":

J. Hernandez, I. Inza, J.A. Lozano. "A novel weakly-supervised problem: learning from positive-unlabeled proportions" [link]

The following work received the prize of the "second best paper of the general conference":

J. Ceberio, B. Calvo, A. Mendiburu, J.A. Lozano. "Multi-objetivising the quadratic assignment problem by means of an elementary landscape decomposition". [link]

Congratulations! Zorionak!


Momo Hernández-González, PhD Thesis defense


Our group member Momo Hernández successfully defended his PhD on October the 23rd. The tribunal was composed of Concha Bielza (Polytechnic University of Madrid), Gavin Brown (University of Manchester) and Borja Calvo (University of the Basque Country). The PhD document can be found here. Congratulations Momo! ¡Felicidades! Zorionak!


New impact factor publication -- Pattern Recognition Letters


Our group members Momo Hernandez, Inaki Inza and Jose Antonio Lozano have recently published the following work:

"Weak supervision and other non-standard classification problems: a taxonomy". Pattern Recognition Letters.

Abstract: In recent years, different researchers in the machine learning community have presented new classification frameworks which go beyond the standard supervised classification in different aspects. Specifically, a wide spectrum of novel frameworks that use partially labeled data in the construction of classifiers has been studied. With the objective of drawing up a description of the state-of-the-art, three identifying characteristics of these novel frameworks have been considered: (1) the relationship between instances and labels of a problem, which may be beyond the one-instance one-label standard, (2) the possible provision of partial class information for the training examples, and (3) the possible provision of partial class information also for the examples in the prediction stage. These three ideas have been formulated as axes of a comprehensive taxonomy that organizes the state-of-the-art. The proposed organization allows us both to understand similarities/differences among the different classification problems already presented in the literature as well as to discover unexplored frameworks that might be seen as further challenges and research opportunities. A representative set of state-of-the-art problems has been used to illustrate the novel taxonomy and support the discussion.


The behaviour of frogs to design novel search metaheuristics


The web, specialized in the divulgation of science, references the work of our group member Borja Calvo and our colleague Christian Blum, where the authors find inspiration in the behaviour of a species of japanese frogs in order to design an optimization algorithm. The work is explained in the following publication:

Christian Blum, Borja Calvo, Maria J. Blesa. “FrogCOL and FrogMIS: new decentralized algorithms for finding large independent sets in graphs”. Swarm Intelligence 9 (2): 205-227, 2015.


Divulgative talk on data mining and big data -- "Deia" newspaper


29th September, 2015 -- Our group member Inaki Inza gave a talk titled "From data mining to big data" in a divulgative scientific meeting around the "big data" discipline organized by the newspaper "Deia". The meeting was the introduction for the awards of the "Best initiatives on social media", organized the the newspaper "Deia". Information about the event can be found here and in the following link of the newspaper.


New impact factor publications


Our members Carlos Pérez-Miguel, Alexander Mendiburu and José Miguel-Alonso have recently published the following two works:

"Competition-based failure-aware scheluding for high-throughput computing systems on peer-to-peer networks". Cluster Computing.

Abstract: in a High-Throughput Computing (HTC) system, system failures and churning pose an important performance limitation. The time used by tasks running in a node that suddenly fails (or abandons the system) constitutes a waste of resources. These aborted tasks are usually reinserted into the system for automatic re-execution, causing additional overheads. This problem has been partially addressed via fault tolerant techniques such as checkpointing and replication. However, these solutions cause additional overheads. In this work, we present several failure-aware scheduling policies that aim to reduce the waste of resources by means of mechanisms to match the submitted tasks with the best node to run it, taking into consideration the (predicted) duration of the task and the (expected) survival time of the nodes. Experimentation through simulation, in the context of an HTC system built on top of a peer-to-peer network, confirms that our policies, compared to several state-of-the-art alternatives, result in a more effective distribution of workload whose consequence is a higher task throughput.

"Modeling the availability of Cassandra". Journal of Parallel and Distributed Computing.

Abstract: Peer-to-Peer systems have been introduced as an alternative to the traditional client–server scheme. Distributed Hash Tables, a type of structured Peer-to-Peer system, have been designed for massive storage purposes. In this work we model the behavior of a DHT based system, Cassandra, with focus on its fault tolerance capabilities, and more specifically, on its availability when facing two different situations: (1) transient failures, those in which a node goes off-line for a while and returns on-line maintaining its data, and (2) memory-less failures, those in which a node goes off-line and returns with no data. First, we introduce two analytical models (one for each scenario) that provide approximations to the behavior of Cassandra under different configurations, and secondly, in order to validate our models, we complete a set of experiments over a real Cassandra cluster. Experimental results confirm the validity of the proposed models of the availability of Cassandra. We also provide some examples of how these models can be used to optimize the availability configuration of Cassandra-based applications.

  • «
  •  Start 
  •  Prev 
  •  1 
  •  2 
  •  3 
  •  4 
  •  5 
  •  6 
  •  7 
  •  8 
  •  Next 
  •  End 
  • »

Page 1 of 8