Janvier 2017 - Lisa_teatalk - mailman.iro.umontreal.ca

[TeaTalk] Prof. Hervé Lombaert, Feb 3, 13:30, AA6214
by Dzmitry Bahdanau 04 Fév '17

04 Fév '17

Hi all, You are invited to attend the talk by Prof. Hervé Lombaert this Friday, Feb 3, at 13:30, room AA6214. *Title:* Spectral Matching & Learning of Surface Data - Example on Brain Surfaces *Abstract:* How to analyze complex shapes, such as of the highly folded surface of the brain? In this talk, I will show how spectral representations of shapes can benefit learning problems where data lives on surfaces. Key operations, such as segmentation and registration, typically need a common mapping of surfaces, often obtained via slow and complex mesh deformations in a Euclidean space. Here, we exploit spectral coordinates derived from the Laplacian eigenfunctions of shapes and also address the inherent instability of spectral shape decompositions. Spectral coordinates have the advantage over Euclidean coordinates, to be geometry aware and to parameterize surfaces explicitly. This change of paradigm, from Euclidean to spectral representations, enables a classifier to be applied *directly* on surface data, via spectral coordinates. The talk will focus, first, on spectral representations of shapes, with an example on brain surface matching, and second, on the learning of surface data, with an example on automatic brain surface parcellation. *Speaker's bio: *Hervé Lombaert is a Starting Research Scientist at Inria Sophia-Antipolis, France, and Associate Professor at ETS, Montreal - with research interests in Statistics on Shapes, Data & Medical Images. He had the chance to work in multiple centers, including Microsoft Research (Cambridge, UK), Siemens Corporate Research (Princeton, NJ), Inria Sophia-Antipolis (France), McGill University (Canada), and Polytechnique Montreal (Canada). He is also a recipient of the François Erbsmann Prize, a top prize in Medical Image Analysis, earned the select NSERC Postdoctoral Fellowship and the FQRNT Étudiant-Chercheur Étoile - more at [ http://cim.mcgill.ca/~lombaert] Best, Dima

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[TeaTalk] Talks by Çağlar Gülçehre and Vincent Dumoulin
by Dzmitry Bahdanau 27 Jan '17

27 Jan '17

Hi all, Next Friday (27.01) at 1:30pm, room 6214, we will have not just one, but two tea-talk presentations by Çağlar and Vincent, both MILA students. Please come in great numbers! Speaker 1: Çağlar Gülçehre Title: TARDIS: an RNN with Wormhole Connections Abstract: In this talk, I will discuss a new memory augmented model which we have been working on with Sarath and Yoshua since last summer. Basically we revisit the idea of memory augmented models and investigate some of their aspects theoretically and propose a new model. The presentation will be about an ongoing work(although the arXiv paper will be out soon). Basically, we revisit the idea of memory augmented models and investigate some of their aspects theoretically and propose a new model. In this paper, we propose a novel memory augmented neural network model called TARDIS (Temporal Automatic Relation Discovery in Sequences). Our model (TARDIS) has an RNN controller which modifies an external memory component where it can store a selective set of embeddings of its own previous hidden states and revisit them as and when needed. In terms of the memory structure, our proposed model is similar to Dynamic Neural Turing Machines ~(D-NTM), but both read and write operations are simpler and more efficient. TARDIS uses discrete addressing for read/write operations which helps to substantially reduce the vanishing gradient problem with very long sequences. We evaluate our models on different long-term dependency tasks and report competitive results in all of them. Speaker 2: Vincent Dumoulin Title: A Learned Representation for Artistic Style Abstract: In this work (done while interning at Google Brain and submitted to ICLR2017) we investigate the construction of a single, scalable deep network that can parsimoniously capture the artistic style of a diversity of paintings. We demonstrate that such a network generalizes across a diversity of artistic styles by reducing a painting to a point in an embedding space. Importantly, this model permits a user to explore new painting styles by arbitrarily combining the styles learned from individual paintings. Best, Dima

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Fwd: Colloque DIRO, jeudi 26 janvier, Pooyan Fazli (Cleveland State U.)
by Yoshua Bengio 21 Jan '17

21 Jan '17

More robotics + machine learning next Thursday, another job talk. ---------- Forwarded message ---------- From: Pierre McKenzie <mckenzie(a)iro.umontreal.ca> Date: 2017-01-20 11:55 GMT-05:00 Subject: Colloque DIRO, jeudi 26 janvier, Pooyan Fazli (Cleveland State U.) To: seminaires(a)iro.umontreal.ca *Distributed Robotics: Algorithms and Applications * par * Pooyan Fazli * Cleveland State University *Jeudi 26 janvier, 15:30-16:30*, *Salle 6214*, Pavillon André-Aisenstadt Université de Montréal, 2920 Chemin de la Tour Café avant 15:00-15:30 *Cette présentation sera donnée en anglais.* *Résumé:* Future robots will have to work in dynamic, uncertain, adversarial, and multi-goal environments. Thus, the integration of the advanced physical and cognitive systems required by the next generation of robots is a challenging task. It is not feasible to design a ‘universal’ robot capable of working across a wide range of applications. The robots of today are examples of the challenges of cost, long training period, and limited functionality, which will apply to robots of the near future as well. Given these challenges, multi-robot systems may be more suitable than single-robot systems in many real world applications. In this talk, I shall discuss two challenging problems in distributed robotics: 1) Service robots frequently face similar tasks. However, they are still not able to share their knowledge efficiently on how to accomplish those tasks. We introduce a new framework, which allows remote and heterogeneous robots to share plans and instructions on the tasks assigned to them. We demonstrate the feasibility of the framework with experiments between two geographically distributed robots and analyze the performance of the framework quantitatively. 2) In distributed coverage, a team of robots is deployed to move around a target area to perform sensing, monitoring, data collection, search, or distributed servicing tasks. We focus on the problem of multi-robot coverage and patrolling of the boundaries of a target area and the structures inside it. Events may occur at any position on the boundaries, and the goal of the robot team is to maximize the total detection reward of the events. To this end, we introduce an online, distributed algorithm, in which each robot autonomously learns the event distribution on the boundaries and then plans accordingly to visit the most promising parts of the target area. We also investigate how robots’ visual range and communication among the robots affect the performance of the robot team in the coverage problem. *Biographie:* Pooyan Fazli is an assistant professor and the founding director of the People and Robots Laboratory (PeRL) in the Electrical Engineering and Computer Science Department at Cleveland State University. He received his Ph.D. in Computer Science from the University of British Columbia and his M.Sc. and B.Sc. in Computer Science from Amirkabir University of Technology. Prior to joining CSU, he was a postdoctoral fellow in the CORAL Research Group at Carnegie Mellon University and in the Laboratory for Computational Intelligence at the University of British Columbia. His research focuses on artificial intelligence, autonomous robots, multi-robot systems, human-robot teams/interaction, machine learning, and robot vision and perception.

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[TeaTalk] Talk by Professor Brendan Frey on 'Using Machine Learning to Detect and Treat Genetic Disease'
by Junyoung Chung 20 Jan '17

20 Jan '17

Hi everyone, we will have our first tea talk on this Friday. Please NOTE that this tea talk is scheduled at **13:30-14:30** in **AA6214**. We are in a transition process of moving the tea talk time slot from 11:00-1200 to 13:30-14:30. Professor Brendan Frey from U of T will tell us about his work on applying machine learning to detect and treat genetic disease. If anyone is interested in meeting with Brendan, please tell Dima or me, we will host a short meeting after his talk. Who : Professor Brendan Frey When : 20/1/2017 13:30-14:30 Where: AA6214 Title: Using Machine Learning to Detect and Treat Genetic Disease Abstract: Diseases and corresponding treatments often have to do with genetic modifications, such as changing a T to a G at a particular location within DNA. In 2015, my University of Toronto group spun out a startup, Deep Genomics, which is using machine learning to model how these changes impact cellular processes involved in disease, such as cancer and neurological disorders. For example, to train our splicing model, we are using 9661 different datasets, each with a number of training cases that varies from 8 million to 220 million. In this talk, I'll describe some of the machine learning challenges that, if solved, will completely change the field of medicine, save hundreds of thousands of lives, and improve the quality of life for hundreds of millions of people. Biography: Brendan Frey is the CEO and Co-Founder of Deep Genomics and a Professor in Engineering and Computer Science at the University of Toronto. He has made fundamental contributions in the areas of machine learning and genome biology, and is widely known for his work on using machine learning to understand how genetic variation leads to disease. Dr. Frey has received numerous distinctions and is a Fellow of the Royal Society of Canada, a Senior Fellow of the Canadian Institute for Advanced Research, and a John C. Polanyi Fellow. He recently co-founded a University of Toronto spinoff, Deep Genomics, which is using machine learning to bring about a new approach to genomic medicine. Dr. Frey has consulted for several industrial research and development laboratories in Canada, the United States and England, and has served on the Technical Advisory Board of Microsoft Research. His former students and postdoctoral fellows include professors, industrial researchers and developers at universities and industrial laboratories from across Canada, the United States and Europe. Best, --Junyoung

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New student orientation this Friday
by Junyoung Chung 11 Jan '17

11 Jan '17

Hi everyone, we will not have a tea talk on this Friday, but instead there will be an orientation for new students at 11AM, AA3195. Best, --Junyoung

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