AI & Ethics
Banning Face Surveillance - Evan Selinger, Professor, RIT
Banning Face Surveillance - Evan Selinger, Professor, RIT
Abstract: Facial recognition technology is the most dangerous surveillance apparatus ever invented, posing substantial threats to civil liberties, privacy, and democratic accountability. In the United States, it is so underregulated as ...
Seminar
BMIAI Seminar - A Marauder's Map of Security and Privacy in Machine Learning - Nicolas Papernot
BMIAI Seminar - A Marauder's Map of Security and Privacy in Machine Learning - Nicolas Papernot
Abstract: There is growing recognition that machine learning (ML) exposes new security and privacy vulnerabilities in software systems, yet the technical community's understanding of the nature and extent of these vulnerabilities remain...
AI & Fundamentals
Machine Learning for Modelling and Decision Making in Complex Physical Domains - Mark Crowley, Assistant Professor, Waterloo
Machine Learning for Modelling and Decision Making in Complex Physical Domains - Mark Crowley, Assistant Professor, Waterloo
Abstract: My lab at the University of Waterloo carries out work on a variety of topics within Artificial Intelligence and Machine Learning with a focus on using real world problems to discover computational challenges for modelling of u...
AI & Fundamentals
Polynomial acceleration of Gibbs sampling (from probability distributions) - Colin Fox, Associate Professor, University of Otago
Polynomial acceleration of Gibbs sampling (from probability distributions) - Colin Fox, Associate Professor, University of Otago
Abstract: The standard Gibbs sampler (a.k.a. Glauber dynamics and local heat-bath thermalization) is essentially identical to Gauss-Seidel iteration, when applied to Gaussian target distributions. This explains the slow (geometric) conv...
AI & Fundamentals
Neural Stochastic Differential Equations for Irregularly-Sampled Time Series - David Duvenaud, Assistant Professor, U of T
Neural Stochastic Differential Equations for Irregularly-Sampled Time Series - David Duvenaud, Assistant Professor, U of T
Abstract: Much real-world data is sampled at irregular intervals, but most time series models require regularly-sampled data. Continuous-time state-space models can handle address this problem, but until now only linear-Gaussian or dete...
AI & Fundamentals
On Conditional Generative Adversarial Networks: Iterative Generation and Holistic Evaluation - Graham Taylor, Associate Professor, University of Guelph
On Conditional Generative Adversarial Networks: Iterative Generation and Holistic Evaluation - Graham Taylor, Associate Professor, University of Guelph
Abstract: Conditional Generative Adversarial Networks (cGANs) are finding increasingly widespread use in many application domains, most notably text-to-image synthesis. In this talk, I will address two outstanding limitations of this pa...
AI & Fundamentals
Domes to Drones: Self-Supervised Active Triangulation for 3D Human Pose Reconstruction - Cristian Sminchisescu, Professor, Lund University / Google Zurich
Domes to Drones: Self-Supervised Active Triangulation for 3D Human Pose Reconstruction - Cristian Sminchisescu, Professor, Lund University / Google Zurich
Abstract: Existing state-of-the-art estimation systems can detect 2d poses of multiple people in images quite reliably. In contrast, 3d pose estimation from a single image is ill-posed due to occlusion and depth ambiguities. Assuming ac...
AI & Fundamentals
Embodied Learning as a Path to Intelligent Machines - Sergey Levine, Assistant Professor, UC Berkeley
Embodied Learning as a Path to Intelligent Machines - Sergey Levine, Assistant Professor, UC Berkeley
Abstract: We've seen machine learning methods succeed in domains where hand-designed methods have proven insufficient: visual perception in open-world environments, speech and text recognition, machine translation, and a range of other ...
AI & Fundamentals
Imagination Inspired Vision - Mohamed H. Elhoseiny, Assistant Professor, KAUST
Imagination Inspired Vision - Mohamed H. Elhoseiny, Assistant Professor, KAUST
Abstract: Imagination is one of the key properties of human intelligence that enables us not only to learn new concepts quickly and efficiently but also to generate creative products like art and music. My research has focused on develo...
AI & Fundamentals
Recent Advances in Neural Architecture Search - Frank Hutter, Professor, University of Freiburg
Recent Advances in Neural Architecture Search - Frank Hutter, Professor, University of Freiburg
Abstract: Deep learning has removed the need for manual feature engineering but still requires a lot of manual work on architecture design. Neural architecture search (NAS) can be seen as the logical next step in representation learning...