Sökning: "sekventiella"
Visar resultat 1 - 5 av 63 uppsatser innehållade ordet sekventiella.
1. Scalable Hyperparameter Opimization: Combining Asynchronous Bayesian Optimization With Efficient Budget Allocation
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Automated hyperparameter tuning has become an integral part in the optimization of machine learning (ML) pipelines. Sequential model based optimization algorithms, such as bayesian optimization (BO), have been proven to be sample efficient with strong final performance. LÄS MER
2. Particle-Based Online Bayesian Learning of Static Parameters with Application to Mixture Models
Master-uppsats, KTH/Matematisk statistikSammanfattning : This thesis investigates the possibility of using Sequential Monte Carlo methods (SMC) to create an online algorithm to infer properties from a dataset, such as unknown model parameters. Statistical inference from data streams tends to be difficult, and this is particularly the case for parametric models, which will be the focus of this paper. LÄS MER
3. Ramverket Scrum vid mjukvaruutveckling i praktiken : En jämförelse av Scrum i praktik och teori
Uppsats för yrkesexamina på grundnivå, Högskolan i Gävle/Avdelningen för datavetenskap och samhällsbyggnadSammanfattning : Det finns många olika teorier om hur man skall bedriva framgångsrik mjukvaruut- veckling. Metoderna har gått alltifrån mer sekventiella metoder till mer agila arbets- metoder. Misslyckanden inom projekt och brister i programvarorna var anledningen till att den agila arbetsmetoden definierades. LÄS MER
4. Particle Simulation using Asynchronous Compute : A Study of The Hardware
Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : Background. With the introduction of the compute shader, followed by the application programming interface (API) DirectX 12, the modern GPU is now going through a transformation. Previously the GPU was used as a massive computational tool for running a single task at unparalleled speed. LÄS MER
5. Continual imitation learning: Enhancing safe data set aggregation with elastic weight consolidation
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The field of machine learning currently draws massive attention due to ad- vancements and successful applications announced in the last few years. One of these applications is self-driving vehicles. A machine learning model can learn to drive through behavior cloning. Behavior cloning uses an expert’s behavioral traces as training data. LÄS MER
