IVADO

Journée des femmes en informatique du DIRO
2016-03-16 09:00 - 17:00 (America/New_York) | Université de Montréal, Pavillon André-Aisenstadt, Pavillon André-Aisenstadt, Montréal, QC, H3T 1J4, Canada
Conférence, réseautage:
Intéressée par une carrière en informatique ? Le 16 mars 2016, venez rencontrer des informaticiennes passionnées et inspirantes, chercheuses et employées de grandes compagnies telles que Google ou Ubisoft, à l’occasion de la Journée des Femmes en informatique du DIRO.
Date de l’évènement : mercredi 16 mars 2016, de 09h00 à 17h00
Emplacement : Université de Montréal, Pavillon André-Aisenstadt (Montréal)
Prix : Gratuit, repas inclus !
Pour plus d’informations sur l’évènement:
Page officiel de l’évènement

Un voyage de 40 ans en science des données et technologie, de l'académique à l'industrie (en anglais)
2016-03-11 10:45 - 12:00 | Université de Montréal, Pavillon André-Aisenstadt, Pavillon André-Aisenstadt, Montréal, QC, H3T 1J4, Canada
Présentation de Philippe Collard – Président, Le Link Inc., Canada
Over the course of the past 40 years, I have been witness to and an actor of an amazing transformation in what we called “technology”. My first exposure to this world was when I wrote my first program for an an IBM 360 on punch cards. I was later involved in medical imaging (where we were first exposed to “big data”). Then went on to work for NASA on climate science in the 90s. And I have been involved in more technology ventures since then from the industry side.
I have now more power in my pocket in my iPhone 6 than I had at my disposal when I tried to analyse cloud images on Cray computers 20 years ago. What has been this journey? What did I learn from it? and how should we look at technology today? What about artificial intelligence? what about big data? what about virtual reality? how do we make sense of it all, sorting through what is real, what could become real, what probably will never be and what is hype? Follow me on a time travel trip: from the past to the future.
SÉMINAIRE DU GERAD
11 Mars 2016 10h45 – 12h00
Salle 4488
Pavillon André-Aisenstadt
Campus de l’Université de Montréal
2920, chemin de la Tour Montréal QC H3T 1J4 Canada

Opportunités et limites de l'apprentissage automatique (machine-learning) pour les sciences appliquées (en anglais)
2016-02-26 14:00 - 15:00 | Université de Montréal, Pavillon André-Aisenstadt, Pavillon André-Aisenstadt, Montréal, QC, H3T 1J4, Canada
Présentation de Mohammad Attarian Shandiz – Université McGill, Canada
Modern methods in machine learning have provided many opportunities for solving complex problems in applied science. Hence, for a data scientist is essential to be familiar with the most important and current fields of research in machine learning and data mining. In this talk, the most significant fields of research in machine learning and data mining are introduced based on the survey in the database of scientific journals. Subsequently, various applications of machine learning for some challenging problems in medicine, finance and engineering are discussed. Lastly, the results of optimized classifiers for a classification problem in the field of lithium-ion batteries are presented. Ensemble methods including random forests and extremely randomized trees provided the highest accuracy of prediction among other methods for the classification based on the Monte Carlo cross validation tests.
Séminaire du GERAD
26 FÉV. 2016 14H00 – 15H00
Salle 4488
Pavillon André-Aisenstadt
Campus de l’Université de Montréal
2920, chemin de la Tour Montréal QC H3T 1J4 Canada

Optimiser les infrastructures du Cloud de Google (en anglais)
2016-02-19 10:45 - 12:00 | Université de Montréal, Pavillon André-Aisenstadt, Pavillon André-Aisenstadt, Montréal, QC, H3T 1J4, Canada
Conférence de Brian Eck – Google, États-Unis
Google’s Cloud infrastructure consists of the servers, network, datacenters and software that run all of Google’s services like Search, Gmail and Youtube as well as it’s fast growing external business, Google Cloud Platform. We’ll discuss three case studies in optimizing this infrastructure, covering challenges not only in solving the analytical problems but also in solving the business problems to reach real implementation and impact. Case studies will include some subset of:

Optimizing build frequency for adding capacity to the network,
Analyzing scenarios of metro network topology to inform strategy, including cost implications of adjusting forecasts,
Building ‘forecast tolerant’ networks that buffer for fault-tolerance and forecast variation,
Low-cost methods of physical grooming on a city-level fiber infrastructure,
Reducing stranded compute resources through simulation,
Increasing resource utilization through statistical oversubscription.

Séminaire du GERAD
Le 19 Février 2016 de 10H45 – 12H00
Salle 4488
Pavillon André-Aisenstadt
Campus de l’Université de Montréal
2920, chemin de la Tour Montréal QC H3T 1J4 Canada

Big data & mixed-integer (nonlinear) programming
2016-01-22 16:00 - 17:00 | UQÀM, Pavillon Président-Kennedy, Salle PK 5115, 201, avenue du Président-Kennedy, Montreal, québec, Canada
Andrea Lodi – Professeur titulaire, Département de mathématiques et de génie industriel, Polytechnique Montréal, Canada
Conférence en anglais
In this talk I review a couple of applications on Big Data that I personally like and I try to explain my point of view as a Mathematical Optimizer — especially concerned with discrete (integer) decisions — on the subject. I advocate a tight integration of Data Mining, Machine Learning and Mathematical Optimization (among others) to deal with the challenges of decision-making in Data Science. Those challenges are the core of the mission of the Canada Excellence Research Chair in “Data Science for Real-time Decision Making” that I hold.

GERAD: Reverse Stackelberg games: Theory and applications in traffic control
2016-01-18 10:00 - 12:00 | Université de Montréal, Pavillon André-Aisenstadt, Pavillon André-Aisenstadt, Montréal, QC, H3T 1J4, Canada

Yoshua Bengio: Intelligence Artificielle Et Apprentissage Profond
2015-09-10 | Université de Montréal, Pavillon André-Aisenstadt, Pavillon André-Aisenstadt, Montréal, QC, H3T 1J4, Canada
Conférence de Yoshua Bengio, professeur en Intelligence artificielle, titulaire au Département d’informatique et de recherche opérationnelle de l’Université de Montréal.
