All Years Seminars
[INMA] 2017-11-02 (11:00) : Graph embeddings and community detection -- a control theoretic perspective
At Euler building (room A002)
Speaker :
Schaub, Michael
Abstract :
Community detection, the task of partitioning a network into groups of nodes similar to each other according to some criterion, has received enormous attention in the past decade.
Many different notions of what constitutes a good community exist in the literature, some based on finding groups with high edge-density, a small cut between the different groups, or by assuming a particular (generative) model for the structure of the network as a whole.
In this talk we focus on a dynamical notion of community structure: we think of our system under study as a network of coupled dynamical units, and aim to find groups of nodes which influence the system in a coherent way for a particular time-scale.
Previous work, focusing on diffusion processes, has shown that such a perspective can indeed be fruitful, and that notions such as Modularity, spectral clustering and various other well-known graph partitioning heuristics can be recovered using this point of view.
In this talk we reconsider such a dynamical approach towards community detection using a more control-theoretic perspective.
This enables us not only to consider more general system descriptions, such as networks with both positive and negative edges, but also reveals interesting connections to ideas used in dimensionality reduction and graph embeddings.
More importantly, however, it also allows us to connect to concepts considered in Control Theory, such as controllability and observability Gramians, thereby offering a fresh perspective on the problems of community detection and graph embeddings.
[INMA] 2017-10-17 (14:00) : Welcome seminar
At Euler building (room A.002)
Speaker :
First-year PhD students (UCL)
Abstract :
In this seminar, the new PhD students in INMA will introduce themselves and their research topic: Dynamic networks in neuroscience (Benjamin Chiêm), Global Riemannian optimization for tensor decomposition (Guillaume Olikier), Cyber-Physical Systems control : new optimization techniques (Guillaume Berger), Behavioural and modelling study of rapid control during complex movements in humans (Antoine De Comité), Finger pad mechanics during dexterous object manipulation (Félicien Schiltz), Predictive maintenance for proton therapy machines (Boris Dehem).
[INMA] 2017-10-10 (14:00) : Exploring community-based and peer-to-peer electricity markets
At Euler building (room A.002)
Speaker :
Pierre Pinson (Technical University of Denmark)
Abstract :
The deployment of distributed renewable generation capacities, new ICT capabilities, as well as a more proactive role of consumers, are all motivating rethinking electricity markets in a more distributed and consumer-centric fashion. After motivating the design of various forms of consumer-centric electricity markets, we will focus on two alternative constructs (which could actually be unified) consisting in community-based and peer-to-peer electricity markets. The mathematical framework for these markets will be described, with focus on negotiation and clearing algorithms in a distributed and decentralized setup. Opportunities and challenges related to these markets, both mathematical and related to real-world applications, will be discussed.
[INMA] 2017-09-26 (14:00) : Impulse response constrained LS-SVM modelling for MIMO Hammerstein system identification
At Euler building (room A.002)
Speaker :
Ricardo Castro-Garcia (KU Leuven)
Abstract :
Hammerstein systems are commonly found in many different areas. From chemical processes to power amplifiers, this type of structures have been used for decades in the system identification community. In this presentation we introduce a new method for modeling MIMO Hammerstein systems through an impulse response constrained LS-SVM formulation. One of the main advantages of this method is its flexibility concerning the class of problems it can model and that no previous knowledge about the underlying nonlinearities is required except for very mild assumptions.
[INMA] 2017-09-11 (14:00) : Achieving budget-optimality with adaptive schemes in crowdsourcing
At Euler building (room A.002)
Speaker :
Sewoong Oh (University of Illinois at Urbana-Champaign)
Abstract :
Crowdsourcing platforms provide marketplaces where task requesters can pay to get labels on their data. Such markets
have emerged recently as popular venues for collecting annotations that are crucial in training machine learning models
in various applications. However, as jobs are tedious and payments are low, errors are common in such crowdsourced labels.
A common strategy to overcome such noise in the answers is to add redundancy by getting multiple answers for each task
and aggregating them using some methods such as majority voting. For such a system, there is a fundamental question of
interest: how can we maximize the accuracy given a fixed budget on how many responses we can collect on the crowdsourcing
system.
We characterize this fundamental trade-off between the budget (how many answers the requester can collect in total) and
the accuracy in the estimated labels. In particular, we ask whether adaptive task assignment schemes lead to a more
efficient trade-off between the accuracy and the budget.
Adaptive schemes, where tasks are assigned adaptively based on the data collected thus far, are widely used in practical
crowdsourcing systems to efficiently use a given fixed budget. However, existing theoretical analyses of crowdsourcing
systems suggest that the gain of adaptive task assignments is minimal. To bridge this gap, we investigate this question
under a strictly more general probabilistic model, which has been recently introduced to model practical crowdsourced
annotations. Under this generalized Dawid-Skene model, we characterize the fundamental trade-off between budget and accuracy.
I will present a novel adaptive task assignment scheme that matches this fundamental limit. This allows us to quantify the
fundamental gap between adaptive and non-adaptive schemes, by comparing the trade-off with the one for non-adaptive schemes.
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