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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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Robust Principal Component Analysis on Graphs

Pierre Vandergheynst, Michael Bronstein, Xavier Bresson, Nauman Shahid, Vasilis Kalofolias

Principal Component Analysis (PCA) is the most widely used tool for linear dimensionality reduction and clustering. Still it is highly sensitive to outliers and does not scale well with respect to the number of data samples. Robust PCA solves the first iss ...

2015

Prioritized Random MAC Optimization via Graph-based Analysis

Pascal Frossard, Laura Toni

Motivated by the analogy between successive interference cancellation and iterative belief-propagation on erasure channels, irregular repetition slotted ALOHA (IRSA) strategies have received a lot of attention in the design of medium access control protoco ...

Institute of Electrical and Electronics Engineers2015

Point localization in Multi-camera system

Alireza Ghasemi, Soumyabrata Dev

Point localization in multi-camera setups has been widely studied in computer vision. Recently, in finite-resolution camera settings, a consistent and optimal point localization algorithm called SHARP has been proposed, under the assumption of noiseless ca ...

pas d'éditeur2015

Learning with tensors: a framework based on convex optimization and spectral regularization

Quoc Tran Dinh

We present a framework based on convex optimization and spectral regularization to perform learning when feature observations are multidimensional arrays (tensors). We give a mathematical characterization of spectral penalties for tensors and analyze a uni ...

Springer2014

Form-Finding Of Interlaced Space Structures

Yves Weinand, Seyed Sina Nabaei, Olivier Baverel

By Interlaced Space Structures (ISS) we mean a coupled system of naturally curved flexible panels/strips interlaced together according to a design pattern. We are looking for a physically-based and efficient form-finding procedure in order to interactively ...

Int Center Numerical Methods Engineering2014

Form-finding Of Interlaced Space Structures

Yves Weinand, Seyed Sina Nabaei, Olivier Baverel

2014

Bootstrap Percolation in Power-Law Random Graphs

Léo Hamed Amini

A bootstrap percolation process on a graph is an "infection" process which evolves in rounds. Initially, there is a subset of infected nodes and in each subsequent round each uninfected node which has at least infected neighbours becomes infected and remai ...

Springer2014

Learning Categories from Few Examples with Multi Model Knowledge Transfer

Barbara Caputo, Tatiana Tommasi

Learning a visual object category from few samples is a compelling and challenging problem. In several real-world applications collecting many annotated data is costly and not always possible. However a small training set does not allow to cover the high i ...

Idiap2013

Adaptation and learning over complex networks [From the Guest Editors]

Ali H. Sayed

The topic of this special issue deals with a subject matter that has been receiving immense attention from various research communities, and not only within the signal processing community. Discusses research and development in the area of the adaption and ...

IEEE2013

Graph-Based Information Processing

Amin Karbasi

We live in a world characterized by massive information transfer and real-time communication. The demand for efficient yet low-complexity algorithms is widespread across different fields, including machine learning, signal processing and communications. Mo ...

EPFL2012