Sökning: "Gradient descent method"
Visar resultat 1 - 5 av 16 avhandlingar innehållade orden Gradient descent method.
1. Fuzzy Control for an Unmanned Helicopter
Sammanfattning : The overall objective of the Wallenberg Laboratory for Information Technology and Autonomous Systems (WITAS) at Linköping University is the development of an intelligent command and control system, containing vision sensors, which supports the operation of a unmanned air vehicle (UAV) in both semi- and full-autonomy modes. One of the UAV platforms of choice is the APID-MK3 unmanned helicopter, by Scandicraft Systems AB. LÄS MER
2. Group-Sparse Regression : With Applications in Spectral Analysis and Audio Signal Processing
Sammanfattning : This doctorate thesis focuses on sparse regression, a statistical modeling tool for selecting valuable predictors in underdetermined linear models. By imposing different constraints on the structure of the variable vector in the regression problem, one obtains estimates which have sparse supports, i.e. LÄS MER
3. Scalable Optimization Methods for Machine Learning : Acceleration, Adaptivity and Structured Non-Convexity
Sammanfattning : This thesis aims at developing efficient optimization algorithms for solving large-scale machine learning problems. To cope with the increasing scale and complexity of such models, we focus on first-order and stochastic methods in which updates are carried out using only (noisy) information about function values and (sub)gradients. LÄS MER
4. Asynchronous Algorithms for Large-Scale Optimization : Analysis and Implementation
Sammanfattning : This thesis proposes and analyzes several first-order methods for convex optimization, designed for parallel implementation in shared and distributed memory architectures. The theoretical focus is on designing algorithms that can run asynchronously, allowing computing nodes to execute their tasks with stale information without jeopardizing convergence to the optimal solution. LÄS MER
5. Accelerating Convergence of Large-scale Optimization Algorithms
Sammanfattning : Several recent engineering applications in multi-agent systems, communication networks, and machine learning deal with decision problems that can be formulated as optimization problems. For many of these problems, new constraints limit the usefulness of traditional optimization algorithms. LÄS MER