Continuous Algorithms - Sampling and Optimization in High Dimension
Explore high-dimensional sampling and optimization techniques, including cutting plane methods, interior-point algorithms, and Riemannian Hamiltonian Monte Carlo, with insights on complexity and open problems.
Random Tessellation Forests: Overcoming the Curse of Dimensionality
Explore random tessellation forests in machine learning, overcoming dimensionality challenges through innovative partitioning methods and directional distributions for improved statistical performance.
New Directions in Property Testing
Explore recent advancements in property testing algorithms, including new problems and frameworks connected to machine learning theory and high-dimensional data analysis.
Smoothed Analysis in Unsupervised Learning via Decoupling
Explore smoothed analysis in unsupervised learning, focusing on tensor decomposition, high-dimensional data, and robust subspace recovery. Gain insights into condition number bounds and perturbation techniques.
Tools of High Dimensional Data - Lecture 3
Explore tools for analyzing high-dimensional data in genetics and evolution. Learn techniques to understand complex genetic architectures and their role in adaptive processes.
Discovery in High Dimensions - 2008
Explore statistical methods for uncovering hidden structures in high-dimensional data from various fields, including genetics, astronomy, and consumer behavior.
Giving Language a Voice Through AI | Sana Shams | TEDxSICAS DHA Youth
Mrs. Sana Shams explores how artificial intelligence can support language diversity and digital inclusion. Drawing from her own experiences, she discusses building speech-based chatbots for citizen services and regional collaborations that made computing accessible in 11 local languages. Her talk hi