Engineering the Future of Medicine - The Turing Lectures
Explore cutting-edge machine learning applications in biomedical data interpretation, from cellular analysis to surgical skill assessment, with renowned engineer René Vidal.
Linear Algebra Basics for Computer Vision - Lecture 2
Explore essential linear algebra concepts including vectors, matrices, transformations, and SVD, with practical applications in computer vision and machine learning.
How Neural Networks Learn Features from Data
Uncover the mechanism behind neural networks' feature learning through the average gradient outer product (AGOP). Explore its applications in various architectures and its role in developing interpretable models for scientific use.
Unsupervised Learning
Explore key unsupervised learning techniques including clustering, dimensionality reduction, and generative models. Gain insights into real-world applications like recommendation systems and image compression.
Machine Learning
Comprehensive introduction to key machine learning concepts, algorithms, and applications, covering testing, error metrics, recommendation systems, and various classification methods.
LoRA - Low Rank Adaptation for Parameter Efficient Fine-Tuning
Dive into parameter-efficient fine-tuning with LoRA, exploring low-rank matrices, adapters, and techniques to optimize neural network storage and performance while maintaining accuracy.
The Effect of Parametrization on Nonconvex Optimization Landscapes - Seminar
Explore the relationship between optimization landscapes in parametrized problems. Gain insights into applications like low-rank matrix optimization, semidefinite programming, and neural network training.
KDD 2020: Robust Deep Learning Methods for Anomaly Detection
Explore robust deep learning techniques for anomaly detection, focusing on auto-encoders and their applications in video surveillance and image analysis.
Building Robust and Scalable Recommendation Engines for Online Food Delivery
Unlock the power of recommendation engines for food delivery. Learn data preprocessing, feature engineering, and scalable algorithms to create personalized recommendations using the DHRD dataset.
Hilbert Schemes of Plane Curve Singularities and Matrix Factorizations
Explore connections between algebraic geometry and topology through plane curve singularities, Hilbert schemes, and matrix factorizations in this advanced mathematics lecture.
Analytic Shape Reconstruction of a Planar Conductivity Inclusion
Explore mathematical techniques for reconstructing planar conductivity inclusions using generalized polarization tensors and Riemann mapping coefficients in this advanced applied mathematics seminar.
Efficient Decentralized Federated Singular Vector Decomposition
Innovative system for efficient decentralized federated SVD, enhancing privacy and performance in distributed applications. Outperforms existing methods with significant speed improvements and larger throughput.
Categorification of Donaldson-Thomas Invariants
Explore categorification of Donaldson-Thomas invariants through derived foliations, extending BBDJS construction with a sheaf of 2-periodic dg-categories modeled on matrix factorizations.
LU-Decomposition of a Matrix - Linear Algebra Explained
Explore LU-Decomposition in linear algebra: definition, applications for solving systems, step-by-step process, and examples. Master this powerful technique for efficient matrix analysis.
PLU-Decomposition of a Matrix Explained - Linear Algebra
Explore PLU-decomposition of matrices, its applications in solving linear systems, and step-by-step process for finding LU decomposition and PLU factorization in linear algebra.
Soergel Bimodules, Matrix Factorizations and Hilbert Schemes
Explore Soergel bimodules, matrix factorizations, and Hilbert schemes in quantum topology, focusing on representation theory applications.
The Linear Algebra of Large Language Models
Explorez les fondements mathématiques des modèles de langage à grande échelle et leur lien avec l'algèbre linéaire avancée.
Matrix Factorization and Applications to Bulk and Single Cell Omic Datasets
Explore matrix factorization techniques for analyzing bulk and single-cell omic datasets, with applications in computational genomics and bioinformatics.
Parameter Efficient Fine-Tuning with Multiple LoRA Adapters for Large Language Models
Dive into parameter efficient fine-tuning with LoRA adapters, exploring matrix factorization, SVD, and advanced configurations for optimizing large language models.
LoRA: Low-Rank Adaptation for Parameter-Efficient Large Language Model Fine-Tuning
Discover how LoRA enables efficient fine-tuning of large language models through low-rank adaptation, from fundamental concepts to practical implementation in transformer architectures.
Matrix Factorization Techniques for Recommender Systems
Explore matrix factorization techniques for building effective recommender systems, covering key concepts and practical implementation strategies.