Publications related to Counting and Sampling from Markov Equivalent DAGs Using Clique Trees

Scalable analysis of linear networked systems via chordal decomposition

This paper introduces a chordal decomposition approach for scalable analysis of linear networked systems, including stability, H 2 and H ∞ performance. Our main strategy is to exploit any sparsity within these analysis problems and use chordal decompositio ...

IEEE2018

Exploring Selection Bias by Causal Frailty Models

Mats Julius Stensrud

Counter-intuitive associations appear frequently in epidemiology, and these results are often debated. In particular, several scenarios are characterized by a general risk factor that appears protective in particular subpopulations, for example, individual ...

2017

Lower Bounds on Active Learning for Graphical Model Selection

Volkan Cevher, Jonathan Mark Scarlett

We consider the problem of estimating the underlying graph associated with a Markov random field, with the added twist that the decoding algorithm can iteratively choose which subsets of nodes to sample based on the previous samples, resulting in an active ...

2017

Safe Adaptive Importance Sampling

Martin Jaggi, Sebastian Urban Stich, Anant Raj

Importance sampling has become an indispensable strategy to speed up optimization algorithms for large-scale applications. Improved adaptive variants - using importance values defined by the complete gradient information which changes during optimization - ...

2017

Can chance cause cancer? A causal consideration

Mats Julius Stensrud

The role of randomness, environment and genetics in cancer development is debated. We approach the discussion by using the potential outcomes framework for causal inference. By briefly considering the underlying assumptions, we suggest that the antagonisin ...

2017

Handheld reflectance acquisition of paintings

Martin Vetterli, Sabine Süsstrunk, Loïc Arnaud Baboulaz, Damien Firmenich, Niranjan Thanikachalam

Relightable photographs are alternatives to traditional photographs as they provide a richer viewing experience. However, the complex acquisition systems of existing techniques have restricted its usage to specialized setups. We introduce an easy-to-use an ...

Ieee-Inst Electrical Electronics Engineers Inc2017

LUT Mapping and Optimization for Majority-Inverter Graphs

Giovanni De Micheli, Mathias Soeken, Pierre-Emmanuel Julien Marc Gaillardon, Luca Gaetano Amarù, Winston Jason Haaswijk

A Majority-Inverter Graph (MIG) is a directed acyclic graph in which every vertex represents a three-input majority operation and edges may be complemented to indicate operand inversion. MIGs have algebraic and Boolean properties that enable efficie ...

2016

On the Zarankiewicz problem for intersection hypergraphs

János Pach

Let d and t be fixed positive integers, and let denote the complete d-partite hypergraph with t vertices in each of its parts, whose hyperedges are the d-tuples of the vertex set with precisely one element from each part. According to a fundamental theorem ...

Academic Press Inc Elsevier Science2016

AiiDA: automated interactive infrastructure and database for computational science

Nicola Marzari, Giovanni Pizzi, Boris Kozinsky, Andrea Cepellotti, Riccardo Sabatini

Computational science has seen in the last decades a spectacular rise in the scope, breadth, and depth of its efforts. Notwithstanding this prevalence and impact, it is often still performed using the renaissance model of individual artisans gathered in a ...

Elsevier Science Bv2016

Random sampling of bandlimited signals on graphs

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

We study the problem of sampling

k

-bandlimited signals on graphs. We propose two sampling strategies that consist in selecting a small subset of nodes at random. The first strategy is non-adaptive, \ie, independent of the graph structure, and its perform ...

2015

Counting and Sampling from Markov Equivalent DAGs Using Clique Trees

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Scalable analysis of linear networked systems via chordal decomposition

Exploring Selection Bias by Causal Frailty Models

Lower Bounds on Active Learning for Graphical Model Selection

Safe Adaptive Importance Sampling

Can chance cause cancer? A causal consideration

Handheld reflectance acquisition of paintings

LUT Mapping and Optimization for Majority-Inverter Graphs

On the Zarankiewicz problem for intersection hypergraphs

AiiDA: automated interactive infrastructure and database for computational science

Random sampling of bandlimited signals on graphs

AiiDA: automated interactive infrastructure and database for computational science

Handheld reflectance acquisition of paintings

Random sampling of bandlimited signals on graphs

Safe Adaptive Importance Sampling

Scalable analysis of linear networked systems via chordal decomposition

Exploring Selection Bias by Causal Frailty Models

Lower Bounds on Active Learning for Graphical Model Selection

On the Zarankiewicz problem for intersection hypergraphs

Can chance cause cancer? A causal consideration

LUT Mapping and Optimization for Majority-Inverter Graphs