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Lundi 2 Juillet
Heure: |
14:00 - 15:00 |
Lieu: |
Salle B107, bâtiment B, Université de Villetaneuse |
Résumé: |
Multi-Arabic Dialect Applications and Resources |
Description: |
Nizar Habash We present the Multi-Arabic Dialect Applications and Resources (MADAR) Project. MADAR is an effort to build parallel resources for 25 Arab city dialects including lexicons, parallel corpora, and orthographic and morphological annotation guidelines. The created resources have been used to develop dialect identification and machine translation applications. We discuss the challenges facing Arabic dialect modeling, as well as our solutions and results. |
Mercredi 4 Juillet
Heure: |
14:00 - 15:00 |
Lieu: |
Salle B107, bâtiment B, Université de Villetaneuse |
Résumé: |
Cost Efficient Prediction of Wine Quality - A Machine Learning Approach |
Description: |
Razvan Andonie The quality of wines can be assessed both from chemical/biological tests and sensory tests (which rely mainly on human experts). Determining which is the subset of tests to be used is a difficult problem. Each test has its own contribution for predicting the quality of wines and, in addition, its own cost. We use our own database, consisting of 32 wine characteristics applied to 180 wine samples. In addition we use wine quality labels assigned by a wine expert. To the extent of our knowledge, this is the first study of this kind on wines from Washington State, and also the first wine study in general to include cost minimization of the measurements as a goal. Our approach is based on two stages. First, we identify reasonably good classifiers (from a given set of classifiers). Next, we search for the optimal subset of features to maximize the performance of the best classifier and also minimize the overall cost of the measurements. As a result, through our method we can answer queries like ``the best performing subset of tests for a given threshold cost'. |
Jeudi 5 Juillet
Heure: |
12:15 - 13:30 |
Lieu: |
Amphi Copernic, Institut Galilée, Université de Villetaneuse |
Résumé: |
Towards more Autonomous Robots |
Description: |
Eduardo Morales With the increasing incorporation of robots into daily life activities, autonomy and interaction with non expert users play a central role in robotics research. In this talk, I will describe two developments towards this aim. First I will describe how a robot can autonomously extract information from Internet to decide where to find an unknown object and how to learn on-line a recognition model. In the second part of the talk I will describe how a non-expert user can train a robot to perform simple tasks combining programming by demonstration, reinforcement learning and user's feedback. |
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