Prof. Dr. Emily King
Ehemalige Leiterin der AAG Computational Data Analysis (2014-2019)
E-Mail: emily.king@colostate.edu
Persönliche Homepage: https://www.math.colostate.edu/~king/index.html
Persönliche Homepage: https://www.math.colostate.edu/~king/index.html
Veranstaltungen (Auswahl)
- Algebraic, Geometric and Combinatorial Methods in Frame Theory (Sommersemester 2019)
- Inverse Methods and Data Analysis in Environmental Physics (Wintersemester 2018/2019)
- Harmonic Analysis: Theory and Applications (Wintersemester 2018/2019)
- Reading Course in Randomisation approaches in data analysis (Wintersemester 2017/2018)
- Reading Course in Sparse and redundant representation systems (Wintersemester 2017/2018)
Abschlussarbeiten (Auswahl)
- Randomized Image Decomposition and Reconstruction (Lennart Abels)
- Tangent and Curvature Estimation of 2D Point Clouds (Laura Breitkopf)
- Distributed Kalman Filtering for Large-Scale Dynamic Systems with Sparsely Coupled States (Lukas Zumvorde)
- Mathematical Analysis of Information Loss and Errors in Neural Networks (Sören Dittmer)
- Spectogram-based Musical Instrument Separation via Pitch-invariant Dictionaries (Sören Schulze)
Publikationen (Auswahl)
- S. Schulze, E. King.
Formulating Beurling LASSO for Source Separation via Proximal Gradient Iteration.
Zur Veröffentlichung eingereicht.online unter: https://doi.org/10.48550/arXiv.2202.08082
- S. Schulze, E. King.
Sparse Pursuit and Dictionary Learning for Blind Source Separation in Polyphonic Music Recordings.
EURASIP Journal on Audio, Speech, and Music Processing, 6:2-25, 2021.DOI: 10.1186/s13636-020-00190-4
online unter: https://rdcu.be/ceo1J - S. Schulze, J. Leuschner, E. King.
Blind Source Separation in Polyphonic Music Recordings Using Deep Neural Networks Trained via Policy Gradients.
MDPI Open Access Journals Signals, 2(4):637-661, 2021.DOI: 10.3390/signals2040039
online unter: https://www.mdpi.com/2624-6120/2/4/39 - E. King.
Constructing Subspace Packings from Other Packings.
Zur Veröffentlichung eingereicht.online unter: https://arxiv.org/abs/1902.07145
- S. Schulze, E. King.
A Frequency‐Uniform and Pitch‐Invariant Time‐Frequency Representation.
90th GAMM Annual Meeting of the international Association of Applied Mathematics and Mechanics (GAMM), 18.02.-22.02.2019, Wien, Österreich.
Proc. Appl. Math. Mech., 19(1):e201900374, 2019.