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X-WR-CALDESC:Events for IVADO
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DTSTART:20190310T070000
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DTSTART;TZID=America/New_York:20190530T080000
DTEND;TZID=America/New_York:20190601T170000
DTSTAMP:20260412T235901
CREATED:20181010T184709Z
LAST-MODIFIED:20181010T185314Z
UID:10177-1559203200-1559408400@vieux.ivado.ca
SUMMARY:Fourth international conference on health care systems engineering (HCSE 2019)
DESCRIPTION:HCSE 2019 provides an opportunity to discuss operations management issues in health care delivery systems. Scientists and practitioners will have the opportunity to discuss about new ideas\, methods and technologies for improving the operation of health care organizations. The event will take place in the mother and child university hospital CHU Saint-Justine of Montréal (with hospital tour) and each session will be co-chaired by a discussant coming from the clinical practice. HCSE 2019 is the fourth edition of the HCSE conferences\, coming for the first time in North America. \n 
URL:https://vieux.ivado.ca/en/events/fourth-international-conference-on-health-care-systems-engineering-hcse-2019/
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20190603T080000
DTEND;TZID=America/New_York:20190606T170000
DTSTAMP:20260412T235901
CREATED:20190311T161537Z
LAST-MODIFIED:20200127T162140Z
UID:11539-1559548800-1559840400@vieux.ivado.ca
SUMMARY:IVADO-Mila Summer School on Bias in AI
DESCRIPTION:Algorithms\, and the data they process\, play an increasingly important role in decisions with significant consequences for human welfare. While algorithmic decision-making processes have the potential to lead to fairer and more objective decisions\, emerging research suggests that they can also lead to unequal and unfair treatments and outcomes for certain groups or individuals. \nThis Summer School is an attempt to engage multi-disciplinary teams of researchers and practitioners to explore the social and technical dimensions of bias\, discrimination and fairness in machine learning and algorithm design. The course focuses specifically (although not exclusively) on gender\, race and socioeconomic based bias and data-driven predictive models leading to decisions. \nA basic understanding of machine learning is strongly recommended. \nObjectives\n\nUnderstanding bias and discrimination\nExploring the harms from bias in machine learning (discriminatory effects of algorithmic decision-making) \nIdentifying the sources of bias and discrimination in machine learning \nMitigating bias in machine learning (strategies for addressing bias)\nRecommendations to guide the ethical development and evaluation of algorithms\n\nConfirmed Speakers\n\nBehrouz Babaki\, IVADO Post-Doc at Polytechnique Montreal\nFernando Diaz\, Principal Researcher and lead of the Montreal FATE Research Group at Microsoft\nMarc-Antoine Dilhac\, Professor of Philosophy at the Université de Montréal\, Chair Holder – Canada Research Chair in Public Ethics and Political Theory\, Leader of the Montreal Declaration Responsible AI Development Committee\nLuc Faucher\, Professor of Philosophy at the Université du Québec à Montréal\nGolnoosh Farnadi\, IVADO Post-Doc at Polytechnique Montreal\nMoritz Hardt\, Assistant Professor\, Department of Electrical Engineering and Computer Sciences at the University of California\, Berkeley\nEmre Kiciman\, Principal Researcher at Microsoft Research AI\nMargaret Mitchell\, Senior Research Scientist\, Google Research and Machine Intelligence\nPetra Molnar\, Lawyer and Researcher\, International Human Rights Program\, University of Toronto Faculty of Law\nDeborah Raji\, Engineering Science Student at the University of Toronto\nTania Saba\, Professor of Industrial Relations at Université de Montréal\, Chair Holder – BMO Diversity and Governance\, Université de Montréal\nPedro Saleiro\, Post-doc\, Aequitas\, Center for Data Science and Public Policy\, University of Chicago\nCynthia Savard Saucier\, Director UX at Shopify and author of Author of Tragic Design (O’Reilly)\nNicolas Vermeys\, Professor of Law at the Université de Montréal and Assistant Director of the Cyberjustice Laboratory\nRC Woodmass\, Founder of Queerit and Product Designer at Crescendo\nResearch Interns at Mila and co-founders of Biasly AI: Andrea Eunbee Jang\, Yasmeen Hitti and Carolyne Pelletier\n\nPreliminary Program\nDay 1: Bias and inclusion in AI\n\nOpening remarks\nKeynote and Introduction\nUnderstanding bias and discrimination\nAI and social justice\nThe tech diversity problem\nIntroduction to Machine Learning and automated decision-making (optional)\n\nDay 2: Fairness in pre-processing\n\nIntroduction\nBloc 1: Fairness in pre-processing (fairness in data)\n\nTechnical session\nCase studies\nHands-on\n\n\n\nDay 3: Fairness in processing and post-processing\n\nBloc 2: Fairness in processing/Fairness in design\n\nTechnical session\nCase studies\n\n\nBloc 3: Fairness in post-processing/Fairness in decision\n\nTechnical session\nCase studies\n\n\n\nDay 4 – Governance\, recommendations and future directions\n\nCommunity-driven initiatives:\n\nMontreal Declaration for a Responsible Development of Artificial Intelligence\nOther initiatives (TBD)\n\n\nBias in the private sector: Challenges and recommendations\nBias in the public sector: Challenges and recommendations\nClosing Panel discussion\n\nRegistration\nRegistration will open on March 11th at 12h00. \n\nGovernment and industry employees: $1500\nNon-profit organization (NPO): $400\nStudent: $200\n\nIVADO also offers fee waivers to eligible students\, which covers the registration fee for the Summer School. To be eligible\, please fill the following form available in English or French before March 29\, 2019. \nOrganizing Committee\n\nJihane Lamouri\, Diversity coordinator\, IVADO\nGolnoosh Farnadi\, Postdoc researcher\, IVADO\nMartin Gibert\, Ethics researcher\, IVADO\nBrian Moore\, Training coordinator\, IVADO\n\nContact\nFor any inquiries\, please contact us at formations@ivado.ca. \nRegistration >>
URL:https://vieux.ivado.ca/en/events/ivado-mila-summer-school-on-bias-in-ai/
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20190609
DTEND;VALUE=DATE:20190610
DTSTAMP:20260412T235901
CREATED:20190610T133250Z
LAST-MODIFIED:20200106T130952Z
UID:13757-1560038400-1560124799@vieux.ivado.ca
SUMMARY:Salon International de la Femme Noire
DESCRIPTION:The Salon International de la Femme Noire\n\n\n\n\n\n\n\n\n\nis a Montreal platform whose mission is to celebrate Black women and their influence over time and generations. This major event will instill self-esteem\, and give the impetus for self-improvement that every Black woman needs to fulfill her ambitions. \nIt’s an interactive space: \n\nTo discover the universe of the Black and mixed-race woman through her eyes;\nTo discuss the place of the Black and mixed-race woman of yesterday\, today and the future;\nTo share news on topics of interest to Black and mixed race women\n\nIt’s a space to get resources: \n\nTo meet the needs of Black and mixed-race women considering their cultural and socio-economic situation;\nTo access targeted services;\nTo support the success of their social integration.\n\nIt’s more than an event\, it’s a movement! \n\nIVADO is proud to sponsor this event!
URL:https://vieux.ivado.ca/en/events/salon-international-de-la-femme-noire/
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20190610
DTEND;VALUE=DATE:20190615
DTSTAMP:20260412T235901
CREATED:20190610T190138Z
LAST-MODIFIED:20190610T190607Z
UID:13830-1560124800-1560556799@vieux.ivado.ca
SUMMARY:Fin-ML/IVADO Workshop on finance and insurance\, members only
DESCRIPTION:Summary\nThe Fin-ML/IVADO Workshop is a one-week practical training in machine learning\, applied to concrete problems in finance and insurance. This workshop will consist of theory in the morning\, followed by problem-solving workshops in finance and insurance in the afternoon. \nThe workshop will be held in English. Participants will have to bring their laptops for the practical part\, no special installation is required. \n\n\n\n\nObjectives\n\nTrain professionals in new technologies in data science\, machine learning and operations research;\nDevelop an understanding of the challenges and issues of data science applied to a specific field;\nLearn to use computer tools to solve concrete problems;\nFoster knowledge sharing and facilitate networking among specialists in a particular field;\nEncourage interdisciplinary knowledge sharing.\n\n\n\n\n\n\n\n\n\n\n\nPrerequisites\nBasic knowledge of mathematics and programming (ideally Python) is strongly recommended. \n\n\n\n\nOrganizers\n\nManuel Morales\, Université de Montréal\nRheia Khalaf\, Université de Montréal / IVADO\nBrian Moore\, IVADO\n\n\n\n\n\nContact\nFor any inquiries\, please contact us at formations@ivado.ca. \n\n\n\n\n\n\n\n\nDates and place\nJune 10-14\, 2019: The workshop will be held in French at HEC Montréal (PWC\, Côte Ste-Catherine). \n\n\nPrerequisites\nBasic knowledge of mathematics and programming (ideally Python) is strongly recommended. \n\n\n\n\nOrganizers\n\nManuel Morales\, Université de Montréal\nRheia Khalaf\, Université de Montréal / IVADO\nBrian Moore\, IVADO\n\n\n\n\n\nContact\nFor any inquiries\, please contact us at formations@ivado.ca. \nMore info >>
URL:https://vieux.ivado.ca/en/events/atelier-finance-et-assurance-fin-ml-ivado-en-francais-membres-seulement/
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BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20190610T080000
DTEND;TZID=America/Toronto:20190610T170000
DTSTAMP:20260412T235901
CREATED:20190610T173351Z
LAST-MODIFIED:20200205T153448Z
UID:13803-1560153600-1560186000@vieux.ivado.ca
SUMMARY:IVADO/Mila Deep Learning School (5th edition)
DESCRIPTION:Summary\nDeep learning is a machine learning technique that has significantly improved previous results in computer vision\, speech recognition\, machine translation and other areas. Many other areas are affected by this new technology\, or will be. In response to the interest generated by this technology\, and in response to training needs\, IVADO and Mila are offering a full week of training in English from September 9 to 13\, 2019 in Montréal. IVADO and Mila are also partnering with the UBC Data Science Institute to offer this training in Vancouver from December 2 to 6\, 2019. \n\n\n\n\nTarget audience\nThe content of this school is mainly aimed at industry professionals and SMEs with basic knowledge of mathematics and programming (engineers\, computer scientists\, statisticians\, technical project managers\, product managers\, systems engineers\, etc.)\, but professors and graduate students in science or engineering (mainly those who are not yet familiar with deep learning) may also find it interesting. \n\n\n\n\nPrerequisites\nA minimal knowledge of programming (ideally Python) and basic knowledge in mathematics (linear algebra\, statistics) is desirable. \n\n\n\n\nObjectives\nAt the end of the training week\, participants should be able to: \n\nUnderstand the basics and terminology related to deep learning\nUnderstand the methodology for carrying out a project in deep learning\nIdentify the types of neural networks to use to solve different types of problems\nGet familiar with deep learning libraries through practical and tutorial sessions\n\nMore info >>
URL:https://vieux.ivado.ca/en/events/13795/
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