Sökning: "kernel methods"

Visar resultat 1 - 5 av 112 uppsatser innehållade orden kernel methods.

  1. 1. Kernel Methods for Regression

    Kandidat-uppsats, Linnéuniversitetet/Institutionen för matematik (MA)

    Författare :Tom Lennart Rossmann; [2023]
    Nyckelord :Kernel Methods; Regression; Ridge Regression;

    Sammanfattning : Kernel methods are a well-studied approach for addressing regression problems by implicitly mapping input variables into possibly infinite-dimensional feature spaces, particularly in cases where standard linear regression fails to capture non-linear relationships in data. Therefore, the choice between standard linear regression and kernel regression can be seen as a tradeoff between constraints on the number of features and the number of training samples. LÄS MER

  3. 2. An Algorithm for Sampling from Bandlimited Circular Probability Distributions

    Kandidat-uppsats, KTH/Skolan för teknikvetenskap (SCI)

    Författare :Mattias Olofsson; [2023]
    Nyckelord :Matematisk Statistik;

    Sammanfattning : In this Bachelor thesis, a novel algorithm for sampling from bandlimited circular probability distributions is presented. The algorithm leverages results from Fourier analysis concerning the Fejér kernel to simulate data with some desired probability distribution, realized as a sum of data sampled from a discrete distribution and a small continuous perturbation sampled from the Fejér kernel distribution. LÄS MER

  4. 3. A Multi-camera based Next Best View Approach for Semantic Scene Understanding

    Uppsats för yrkesexamina på avancerad nivå, Högskolan i Halmstad/Akademin för informationsteknologi

    Författare :Anton Persson; [2023]
    Nyckelord :Next Best View; NBV; Semantic Scene Understanding; Robotics;

    Sammanfattning : Robots are becoming more common; robotics has gone from bleeding-edge technology to an everyday topic that families discuss around thedinner table.The number of robots in the industry is growing, which means thatthe demand and need for robots to understand the environment it isworking in is also growing. LÄS MER

  5. 4. A Conjugate Residual Solver with Kernel Fusion for massive MIMO Detection

    Master-uppsats, Högskolan i Halmstad/Centrum för forskning om tillämpade intelligenta system (CAISR)

    Författare :Ioannis Broumas; [2023]
    Nyckelord :MIMO; massive MIMO; GPU; CUDA; Software Defined Radio; SDR; MMSE; ZF; zero-forcing; parallel detection; iterative methods; conjugate residual; parallel computing; kernel fusion;

    Sammanfattning : This thesis presents a comparison of a GPU implementation of the Conjugate Residual method as a sequence of generic library kernels against implementations ofthe method with custom kernels to expose the performance gains of a keyoptimization strategy, kernel fusion, for memory-bound operations which is to makeefficient reuse of the processed data. For massive MIMO the iterative solver is to be employed at the linear detection stageto overcome the computational bottleneck of the matrix inversion required in theequalization process, which is 𝒪(𝑛3) for direct solvers. LÄS MER

  7. 5. An empirical study of the impact of data dimensionality on the performance of change point detection algorithms

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Léo Noharet; [2023]
    Nyckelord :Time series segmentation; Change point detection; Multivariate time series; Data dimensionality; Tidsserie-segmentering; Förändringspunkts detektering; Mulitvariabla tidsserier; Data dimentionalitet;

    Sammanfattning : When a system is monitored over time, changes can be discovered in the time series of monitored variables. Change Point Detection (CPD) aims at finding the time point where a change occurs in the monitored system. LÄS MER