AIGM15
5th Workshop on Algorithmic issues for Inference in Graphical Models (AIGM)
Date and location
September 28, 2015
Salle du Conseil, Turing Aisle (floor 8 / 7ieme étage)
Université Paris Descartes,
45 rue des Saints-Père
Paris, France.
Registration
Registration is free but each participant should register here
Context, motivations
Most real (e.g. biological) complex systems are formed or modelled by elementary objects that locally interact with each other. Local properties can often be measured, assessed or partially observed. On the other hand, global properties that stem from these local interactions are difficult to comprehend. It is now acknowledged that a mathematical modelling is an adequate framework to understand, to be able to control or to predict the behaviour of complex systems, such as gene regulatory networks or contact networks in epidemiology.
More precisely, graphical models (GM), which are formed by variables linked to each other by deterministic or stochastic relationships, allow researchers to model dependencies in possibly high-dimensional heterogeneous data and to capture uncertainty. Analysis, optimal control, inference or prediction about complex systems benefit from the formalisation proposed by GM. To achieve such tasks, a key factor is to be able to answer general queries: what is the probability to observe such events in this situation ? Which model best represents my data ? What is the most acceptable solution to a query of interest that satisfies a list of given constraints ? In many situations, an exact resolution cannot be achieved either because of computational limits, or because of the intractability of the problem; hence approximate methods are needed.
Objectives
The aim of this workshop is to bridge the gap between Statistics and Artificial Intelligence communities where approximate inference methods for GM are developped. We are primarily interested in algorithmic aspects of probabilistic (e.g. Markov random fields, Bayesian networks, influence diagrams), deterministic (e.g. Constraint Satisfaction Problems, SAT, weighted variants, Generalized Additive Independence models) or hybrid (e.g. Markov logic networks) models.
We expect both:
- reviews that analyze similarities and differences betwen approaches developped by computer scientists and statisticians in these areas and
- original research works which propose new algorithms and show their performance on data sets as compared to state-of-the-art methods.
Invited speakers
- Tamir Hazan, Department of Computer Science, University of Haifa, Israel
- Christophe Gonzales, LIP6, Université Paris 6
- Karteek Alahari, Inria Grenoble - Rhône-Alpes - LEAR team
Program
- 8h45 – 9h00: coffee and welcome
- 9h00 – 10h00: Tamir Hazan, On the likelihood of randomly perturbed max-solutions (slides)
- 10h00 – 10h30: Clément Viricel, David Simoncini, David Allouche, Simon de Givry, Sophie Barbe, Thomas Schiex, Approximate Counting with Deterministic Guarantees for Binding Affinity Computation (slides)
- 10h30 – 11h00:Anne-Marie George, Abdul Razak, Nic Wilson, Multi-Objective Constraint Optimization with Lexicographic Preference Models (slides)
- 11h00 - 11h15: break
- 11h15 – 12h10: Christophe Gonzales, Non-stationary Dynamic Bayesian Network Learning (slides)
- 12h50 – 14h: lunch break
- 14h00 – 14h30: Sarah Ouadah, Stéphane Robin, Loïc Schwaller, Corinne Vacher, Inference of the interactions within the pathobiome of Erysiphe alphitoides (slides)
- 14h30 – 15h30: Karteek Alahari, Efficient Inference Algorithms for Scene Understanding Problems (slides)
- 15h30 – 16h00: Alexandre Albore, Nathalie Peyrard, Régis Sabbadin, Florent Techteil-Königsburgch , Coupling Markov Random Fields and Automated Planning for Online Decision-Making to Map Spatial Phenomena (slides)
Call for paper
Topics include, but are not limited to:
- answering queries in GMs (MAP/MPM/MPE, satisfaction, optimization...),
- evaluation of the normalisation constant of a Markov random field,
- solution counting in deterministic GM or enumeration of k-best solutions,
- decision variable optimisation (optimisation within deterministic or mixed deterministic/stochastic GM),
- variational methods,
- Monte-Carlo methods,
- bounds for approximate inference,
- stochastic satisfiability (SAT) and stochastic constraint programming (CP),
- bridge between probabilistic and logic formalisms
We will consider papers from 1 to 2 pages
Contributions (pdf files) can be submitted no later than the 12th of June, by sending an email to the organisation committee.
Important dates
- Submission deadline: June 12, 2015.
- Notification to authors: July 3, 2015.
- Submission of final version: July 17, 2015.
- Meeting date: September 28, 2015.
Organisation committee
Simon de Givry, Nathalie Peyrard, Régis Sabbadin, Thomas Schiex (MIA-T, INRA Toulouse, France) and Stéphane Robin (AgroParisTech, Paris, France).
Contact
For paper submission or enquiries about the meeting, please contact the organisation committee.
Links to past workshops
- AIGM 2014.
- AIGM 2013.
- AIGM 2012.
- ECCS 2010 workshop on 'Graphical models for reasoning on biological systems: computational challenges'.
Sponsorship
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