Outracing Champion Gran Turismo Drivers With Deep Reinforcement Learning
Explore deep reinforcement learning techniques used to train AI agents that outperform world-class e-sports drivers in Gran Turismo racing simulations.
Navigating the Tradeoff Between Privacy and Fairness in Machine Learning
Explore the intersection of privacy and fairness in ML, addressing challenges and research-based solutions for regulated industries.
Transforming the Retail Industry with Transformers
Explore how transformers and language models revolutionize retail data processing, overcoming challenges in deployment and automation for improved business outcomes.
Artificial Intelligence and Digital Pathology: Making the Most of Limited Annotated Data
Explore semi-supervised and self-supervised approaches for efficient use of limited medical imaging datasets in AI, focusing on digital pathology applications.
2022 AI Index Report Briefing - Key Trends in Artificial Intelligence
Explore key AI trends from the 2022 AI Index Report, covering research, technical advancements, ethics, economics, policy, and education in this insightful briefing.
Where's the Road? The Challenge of Autonomous Driving Perception in Winter
Explore challenges and advancements in autonomous driving during harsh Canadian winters, focusing on perception tasks and all-weather autonomy solutions.
Using AI Governance to Safely Scale AI with Speed
Discover strategies for implementing AI governance to scale AI safely and efficiently. Learn to balance innovation with transparency, trust, and control in AI projects and models.
Obtaining Answers from Social Media Data Using Neural Databases
Explore neural databases leveraging NLP transformers to answer queries over text, freeing us from reliance on traditional database schemas for social media content analysis.
Scaling Deep Learning Model Training
Learn techniques for scaling deep learning model training across distributed systems, reducing training time from days to hours while maintaining cost efficiency.
Towards Machine Intelligence Capable of Nobel-Caliber Science
Explore AI-driven scientific discovery, its challenges, and potential for Nobel-caliber breakthroughs. Learn about key AI/ML areas, recent progress, and human-machine collaboration in advancing scientific innovation.
Trade-off Between Optimality and Explainability in Machine Learning Models
Explore the trade-off between model explainability and accuracy in AI/ML, focusing on counterfactual explainability and optimization challenges in high-risk applications.
Leadership of Responsible AI - The Case for Inclusive Tech
Explore leadership in responsible AI, focusing on inclusive tech. Learn about algorithmic bias, its societal impacts, and strategies for ethical AI implementation in the digital age.
Exploring the Role of Machine Learning in Solving the Climate Crisis - Opportunities, Challenges, and Successes
Discover AI's potential in combating climate change. Explore applications in wildfire prediction, financial decision-making, and supply chain emissions tracking. Learn from experts about opportunities and challenges in this critical field.
Leveraging Computer Vision and Machine Learning for Visual Inspection in Railway Systems
Explore innovative computer vision and machine learning solutions for automated visual inspection in railway systems, enhancing operational efficiency and reducing maintenance time.
Practical Individual Fairness Algorithms in Machine Learning
Explore algorithmic fairness in machine learning, focusing on Distributional Individual Fairness. Learn to train certifiably fair models using transport-based regularization for various ML tasks.
Opening the Machine Learning Black Box in Regulated Industries
Explore techniques for making machine learning models explainable and compliant in regulated industries like finance and insurance. Learn to bridge the gap between ML and regulatory requirements.
L'Oréal Canada's Bespoke Data Science Strategy Framework
Discover L'Oréal Canada's data science strategy framework. Learn to assess maturity, identify high-value projects, build ML teams, and implement effective practices in retail and e-commerce.
Introduction to SciPhy Reinforcement Learning - Part 1
Explore SciPhy RL: a neural network-based method for solving stochastic optimal control problems in continuous time, with applications and high-dimensional examples.
Boosting Retail Margins: Price Optimization with Machine Learning
Discover how machine learning revolutionizes price optimization in retail, boosting gross margins by 28%. Learn algorithms and techniques that led to significant revenue gains in a luxury retail experiment.
DynaTask: A New Open Source Approach for AI Benchmarking
Explore DynaTask, a novel open-source AI benchmarking paradigm using dynamic adversarial data collection to evaluate and assess AI model vulnerabilities to human deception.
Black Loans Matter: Algorithms for Racial Justice in Financial Services
Explore AI fairness in lending, focusing on subgroup discrimination and proposing Distributionally Robust Fairness with SenSR algorithm to combat racial bias in financial services.