“The book provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. These include a discussion of the computational complexity of learning and the concepts of convexity and stabilit...
Various methods have been developed in the machine learning and system identification literature77,78 and used in computational neuroscience20,79 to capitalize on the fact that in the small vicinity of a point, the manifold can be approximated by a linear hyperplane tangential to it at that point...
on local paragraphs sources = ["Computational complexity theory is a branch of the theory of computation in theoretical computer " "science that focuses on classifying computational problems according to their inherent difficulty, " "and relating those classes to each other. A computational problem is...
With the advent of massive data sets, much of the computational science and engineering community has moved toward data-intensive approaches in regression and classification. However, these present significant challenges due to increasing size, complexity, and dimensionality of the problems. In particular...
The program is divided into six courses, with the first two covering theory and basic algorithmic techniques before moving on to advanced algorithms and complexity. It includes the following topics: Using data structures to solve a variety of problems ...
Number theory Graph theory Type theory Category theory Numerical analysis Information theory Combinatorics Boolean algebra Theory of computation Automata theory Computability theory Computational complexity theory Quantum computing theory Algorithms, data structures ...
In: International Conference on the Theory and Application of Cryptology and Information Security, pp. 409–437, November 2017 Google Scholar Chillotti, I., Gama, N., Georgieva, M., Izabachène, M.: Faster packed homomorphic operations and efficient circuit bootstrapping for TFHE, pp. 377...
It also includes a 4-month internship with a company in a data-related sector, like Microsoft or Facebook. Besides, you have a chance to join Data Camps, which take place one day every week. During these sessions, students work on data science cases in collaboration with companies. As ...
This book is a collection of 59 independent articles that build on a basic understanding of Python to teach Pythonic best practices, lesser known functionality, and built-in tools. The topics range in complexity, beginning with the simple concept of being aware of which Python version you’re ...
Carey and Wu (2023); Weinberg (2022) survey the existing critiques on the hegemonic theory of fairness that draw from non-computing disciplines, including philosophy, law, critical race and ethnic studies, and feminist studies. The hegemonic (i.e., dominant) theory of fairness in the ML commu...