Lecture

Gaussian Mixture Models: Applications in Recommender Systems

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

In course

MATH-512: Optimization on manifolds

We develop, analyze and implement numerical algorithms to solve optimization problems of the form min f(x) where x is a point on a smooth manifold. To this end, we first study differential and Riemannian geometry (with a focus dictated by computational con ...

Description

This lecture covers the applications of Gaussian Mixture Models (GMM) in recommender systems, focusing on topics such as structure from motion (SfM), simultaneous localization and mapping (SLAM), and examples from real-world applications like the Roomba robot. The instructor discusses the use of GMM for image credit and its role in surfacing personalized recommendations.

In MOOC

Introduction to optimization on smooth manifolds: first order methods

Optimization on manifolds is the result of smooth geometry and optimization merging into one elegant modern framework. We start the course at "What is a manifold?", and give the students a firm understanding of submanifolds embedded in real space. This covers numerous applications in engineering and the sciences. All definitions and theorems are motivated to build time-tested optimization algorithms. The math is precise, to promote understanding and enable computation. We build our way up to Riemannian g

Instructor

Nicolas Boumal

Teaching & PhD PhD Students Andreea-Alexandra Musat Past EPFL PhD Students Christopher Criscitiello, Quentin Rebjock Courses Continuous optimization MATH-329 This course introduces students to continuous, nonlinear optimization. We study the theory of optimization with continuous variables (with full proofs), and we analyze and implement important algorithms to solve constrained and unconstrained problems. Linear Algebra MATH-111(e) The purpose of the course is to introduce

Official source

Related concepts (18)

Recommender system

A recommender system, or a recommendation system (sometimes replacing 'system' with a synonym such as platform or engine), is a subclass of information filtering system that provide suggestions for items that are most pertinent to a particular user. Typically, the suggestions refer to various decision-making processes, such as what product to purchase, what music to listen to, or what online news to read. Recommender systems are particularly useful when an individual needs to choose an item from a potentially overwhelming number of items that a service may offer.

Roomba

Roomba is a series of autonomous robotic vacuum cleaners made by the company iRobot. Introduced in September 2002, they have a set of sensors that enable them to navigate the floor area of a home. These sensors can detect the presence of obstacles, particularly dirty spots on the floor, and steep drops (e.g., to avoid falling down stairs). As of 2022, iRobot markets models of their 600, i, j, Combo and s9 series, while continuing to provide support and sell accessories for their previous series.

IRobot

iRobot Corporation is an American technology company that designs and builds consumer robots. It was founded in 1990 by three members of MIT's Artificial Intelligence Lab, who designed robots for space exploration and military defense. The company's products include a range of autonomous home vacuum cleaners (Roomba), floor moppers (Braava), and other autonomous cleaning devices. In August 2022, Amazon.com, Inc. announced its intent to acquire iRobot for US$1.

Robotic mapping

Robotic mapping is a discipline related to computer vision and cartography. The goal for an autonomous robot is to be able to construct (or use) a map (outdoor use) or floor plan (indoor use) and to localize itself and its recharging bases or beacons in it. Robotic mapping is that branch which deals with the study and application of ability to localize itself in a map / plan and sometimes to construct the map or floor plan by the autonomous robot. Evolutionarily shaped blind action may suffice to keep some animals alive.

Robotic vacuum cleaner

A robotic vacuum cleaner, sometimes called a robovac or a roomba as a generic trademark, is an autonomous robotic vacuum cleaner which has a limited vacuum floor cleaning system combined with sensors and robotic drives with programmable controllers and cleaning routines. Early designs included manual operation via remote control and a "self-drive" mode which allowed the machine to clean autonomously. Marketing materials for robotic vacuums frequently cite low noise, ease of use, and autonomous cleaning as main advantages.

Related lectures (1)

Vision-based robotic perception