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Novel Ordering-based Approaches for Causal Structure Learning in the Presence of Unobserved Variables

Related publications (71)

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Joint Image and Word Sense Discrimination For Image Retrieval

Aurélien Lucchi

We study the task of learning to rank images given a text query, a problem that is complicated by the issue of multiple senses. That is, the senses of interest are typically the visually distinct concepts that a user wishes to retrieve. In this paper, we p ...

2012

Diffusion Adaptation Strategies for Distributed Optimization and Learning Over Networks

Ali H. Sayed

We propose an adaptive diffusion mechanism to optimize global cost functions in a distributed manner over a network of nodes. The cost function is assumed to consist of a collection of individual components. Diffusion adaptation allows the nodes to coopera ...

IEEE2012

Transfer Learning by Sharing Support Vectors

Pascal Fua, Carlos Joaquin Becker, Vitaly Henry Ablavsky

Machine Learning techniques play an increasingly vital role in the analysis of Biomedical imagery, as in all other areas of Computer Vision. However, in this specific context, they suffer from the fact that experimental conditions and protocols change ofte ...

2012

Information Processing and Structure of Dynamical Networks

Ali Ajdari Rad

Networks are everywhere and we are confronted with many networks in our daily life. Networks such as Internet, World Wide Web, social, biological and economical networks have been subject to extensive studies in the last decade. The volume of publications ...

EPFL2011

Content Preference Estimation In Online Social Networks: Message Passing Versus Sparse Reconstruction On Graphs

We design two different strategies for computing the unknown content preferences in an online social network based on a small set of nodes in the corresponding social graph for which this information is available ahead of time. The techniques take advantag ...

2011

Space crossing numbers

We define the crossing number for an embedding of a graph G into R^3, and prove a lower bound on it which almost implies the classical crossing lemma. We also give sharp bounds on the space crossing numbers of pseudo-random graphs. ...

2011

Semi-Supervised Learning with Spectral Graph Wavelets

Pierre Vandergheynst, David Shuman, Mohammadjavad Faraji

We consider the transductive learning problem when the labels belong to a continuous space. Through the use of spectral graph wavelets, we explore the benefits of multiresolution analysis on a graph constructed from the labeled and unlabeled data. The spec ...

2011

Uncertainty Feature Optimization: an implicit paradigm for problems with noisy data

Michel Bierlaire, Matteo Salani, Niklaus Eggenberg

Optimization problems with noisy data solved using stochastic programming or robust optimization approaches require the explicit characterization of an uncertainty set U that models the nature of the noise. Such approaches depend on the modeling of the unc ...

2011

Degraded two-message multicast over graphs

Christina Fragouli, Shirin Saeedi Bidokhti

We consider communication of two degraded mes- sage sets over graphs where a common source sends two prioritized messages (a common and a private message) to several receivers. All receivers require the common message and a subset of the receivers require ...

2011

Degraded two-message multicast over graphs

Christina Fragouli, Shirin Saeedi Bidokhti

In this work we consider a graph G where a common source sends two messages W1 and W2 to several receivers D1, D2, . . . , DK. The first two receivers D1 and D2 would like to receive message W1, while receivers D3, . . . , DK would like to receive both mes ...

2011