Mathematics and Applied Mathematics
At the heart of our project lies the Restricted Boltzmann Machine, a type of neural network particularly adept at uncovering hidden patterns in data. In the culinary world, ingredients form complex relationships, creating a web of flavors and textures. Our goal is to untangle this web and discover how ingredients
Introduction In the realm of machine learning, managing large datasets efficiently is often a critical task. PyTorch, known for its flexibility and ease of use, offers robust tools for this purpose. This article aims to guide you through constructing a data pipeline that not only manages memory efficiently by streaming
The dataset is a rich compilation of recipes, spanning a wide range of cuisines and styles. It offers a unique perspective on what makes a recipe more than just a list of ingredients and steps. With over 500k recipes, it’s a deep dive into the culinary world, providing data enthusiasts,
The famous QR factorization algorithm can be BLAS-3 optimized. Using the Woodbury matrix identity, we implement a block-based Rank-Revealing QR and point out a connection between pivot selection and object detection.
Many strategies in Machine Learning involve the iterative search of a solution space Ω. We begin with an initial solution ω₀ and update ωₙ to minimize an objective function f(x)
There are k! substitution ciphers for an alphabet with k letters—too many for an exhaustive search. With a frequency-based approach adapted to the graph of alphabetic ciphers, we redefine the act of deciphering as a sampling problem suitable for a Metropolis-Hastings random walk. A substitution cipher is thus solvable with