Archive

Neuroinformatics “combines neuroscience and the information sciences to develop and apply advanced tools for a major advancement in understanding the structure and function of the brain.” After introducing the speaker’s neuroinformatics research group, we will address issues related to the use and misuse of independent component analysis. Departing from the traditionally simple evoked response paradigm, into the more natural neurocinematics one, also the neuronal responses...

Unsupervised Learning of probabilistic structured models presents a fundamental tradeoff between richness of captured constraints and correlations versus efficiency and tractability of inference. In this thesis, we propose a new learning framework called Posterior Regularization that incorporates side-information into unsupervised estimation in the form of constraints on the model’s posteriors. The underlying model remains unchanged, but the learning method changes. During learning, our method is...

As robots leave research labs to operate more often in human-inhabited, larger environments, cooperation between sensor networks and mobile robots becomes crucial. For example, in urban scenarios, employing mobile robots is a need to augment the limited sensor coverage and improve detection and tracking accuracy. The fusion of sensory information between fixed surveillance cameras and each robot, with the goal of maximizing the amount and...

In this talk I will present an overview of some of the past and current lines of research in reinforcement learning (RL), as well as some of the challenges that research in this area has faced in the last decades. I will describe a range of recent results that may bring significant advances on some of these fundamental research challenges, and yet rely on the...

After introducing myself and where I come from, in this talk I will focus on 3 projects I have been working in the last year. The first one is a novel pattern matching algorithm, based on the well known Dynamic Time Warping. The presented algorithm can be used to find real-valued subsequences within a longer sequence, without prior knowledge of their start-end points. I have...

The ability to adapt to changing environment autonomously will be essential for future robots. While this need is well-recognized, most machine learning research focuses largely on perception and static data sets. Instead, future robots need to interact with the environment to generate the data that is needed to foster real-time adaptation based on all information collected in previous interactions and observations. In other words, we...

Geographic Information Retrieval systems rely on the identification of place names in documents to determine the region about which they are relevant. Extracting location names from text is a common Natural Language Processing task, a simple approach is to used manually coded rules supported with dictionaries of place names or gazetteers. Despite these methods achieving good results, the rules are usually too restrictive and very...

Automotive electronic is full of challenges. Engine controller units, executing millions of line code & performing decision making influenced by several parameters, is one of the most complex embedded device being used. In this presentation we explore the possibility of how machine learning tools can enable the process of making ECU modeling and design validation easier and smarter. A data acquisition system is another essential...

Energy efficiency is presently a buzzword that has created new challenges and opportunities over several markets and industries. Buildings consumptions are known to be responsible for over 30% of the overall energy consumption in the world. Reducing facilities consumptions has been recently considered as a main priority no just because of the referred weight but also due to its optimization potential. In fact, unexpected collaborations like...

We take inspiration from recent research on sentiment analysis that interprets text based on the subjective attitude of the author.  We consider related tasks where a piece of text is interpreted to predict some extrinsic, real-valued outcome of interest that can be observed in non-text data.  Examples include: The interpretation of an annual financial report from a company to its shareholders is the risk incurred...