Artificial Intelligence
Building intelligent machines that complement human reasoning and extend what people can do.
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Research talks: Learning for interpretability
Speakers: Hanwang Zhang, Professor, Nanyang Technological University Yuwang Wang, Senior Researcher, Microsoft Research Asia Shujian Yu, Professor, UiT – The Arctic University of Norway One of the critical shortcomings of big data-driven deep learning is…
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Research talks: AI for software development
This session will showcase a future in which AI automates much of the tedious and error-prone collaborative software development tasks. We take a broad, end-to-end view of software development that consists of not only coding…
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Research talk: Challenges and opportunities in causal machine learning
This talk will highlight the big challenges in causal ML research and present our vision for development and use of causal ML technology for real-world decision making. Microsoft Researchers will focus on what’s needed to…
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Practical tips for productivity & wellbeing: Transitioning across the work-life boundary
Learn more about the 2021 Microsoft Research Summit: https://Aka.ms/researchsummit
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Research talk: Safe reinforcement learning using advantage-based intervention
Many sequential decision problems involve finding a policy that maximizes total reward while obeying safety constraints. Although much recent research has focused on the development of safe reinforcement learning (RL) algorithms that produce a safe…
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Research talk: Domain-specific pretraining for vertical search
Information overload is a prevalent challenge in many high-value domains. Search in biomedicine, and many other vertical domains, is challenging due to the scarcity of direct supervision from click logs. Self-supervised learning has emerged as…
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Lightning talks: Advances in fairness in AI: From research to practice
Over the past few years, we’ve seen that artificial intelligence (AI) and machine learning (ML) provide us with new opportunities, but they also raise new challenges. Most notably, these challenges have highlighted the various ways…
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Panel: The future of reinforcement learning
This panel brings together a variety of experts from industry and academia to discuss the question, what is the future of reinforcement learning? Reinforcement learning is an important research area in AI currently, and it…
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Tutorial: Best practices for prioritizing fairness in AI systems
As artificial intelligence (AI) continues to transform people’s lives, new opportunities raise new challenges. Most notably, when we assess the societal impact of AI systems, it’s important to be aware of their benefits, which we…
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Demo: Generating formally proven low-level parsers with EverParse
Speaker: Aseem Rastogi, Principal Researcher, Microsoft Research India DARPA and MITRE estimate that 80 percent of software security vulnerabilities have incorrect input validation as their root cause. In such scenarios, attackers provide malformed input, which,…
