Kristiaan Pelckmans
Forskare vid Institutionen för fysik och astronomi; FREIA
- Telefon:
- 070-875 05 95
- Mobiltelefon:
- 070-875 05 95
- E-post:
- kristiaan.pelckmans@physics.uu.se
- Besöksadress:
- Ångströmlaboratoriet, Lägerhyddsvägen 1
- Postadress:
- Box 516
751 20 Uppsala
Ladda ned kontaktuppgifter för Kristiaan Pelckmans vid Institutionen för fysik och astronomi; FREIA
Mer information visas för dig som medarbetare om du loggar in.
Kort presentation
Denna text finns inte på svenska, därför visas den engelska versionen.
Since 2018, I am appointed the 'docent' in Uppsala University, equivalent to 'associate professor'. My research touches on machine learning, automatic control and different applications of either.
Nyckelord
- automatic control
- machine learning
- system identification
Forskning
Denna text finns inte på svenska, därför visas den engelska versionen.
My (see also http://user.it.uu.se/~kripe367/) research studies different forms of Machine Learning (ML), and various applications of those. My interests are found in the theoretical, algorithmical and application-oriented aspects of the question: what makes a good ML algorithm work in given case? It is fair to say that data-based techniques are evolving parallel to the ever-increasing availability of computational power. But while the availability of fast hardware is mostly regulating the latter, the limits of the former are often dictated by the availability of proper algorithms. Properly designed algorithms are (1) theoretically sound, (2) in-tune with its intended application aim, and (3) computational attractive. These topics are invariantly present underlying trends as neural networks, kernel machines, compressed sensing, deep learning and Big Data.
Publikationer
Senaste publikationer
- Evolution of schooling drives changes in neuroanatomy and motion characteristics across predation contexts in guppies (2023)
- Launching the VASCO Citizen Science Project (2022)
- A HPC Co-scheduler with Reinforcement Learning (2021)
- Identifying reionization-epoch galaxies with extreme levels of Lyman continuum leakage in James Webb Space Telescope surveys (2020)
- Rapid evolution of coordinated and collective movement in response to artificial selection (2020)
Alla publikationer
Artiklar
- Evolution of schooling drives changes in neuroanatomy and motion characteristics across predation contexts in guppies (2023)
- Launching the VASCO Citizen Science Project (2022)
- Identifying reionization-epoch galaxies with extreme levels of Lyman continuum leakage in James Webb Space Telescope surveys (2020)
- Rapid evolution of coordinated and collective movement in response to artificial selection (2020)
- Monitoring High-Frequency Data Streams in FinTech (2020)
- The Vanishing and Appearing Sources during a Century of Observations Project. I. USNO Objects Missing in Modern Sky Surveys and Follow-up Observations of a "Missing Star" (2020)
- Frequency conditions for stable networked controllers with time-delay (2019)
- Lyman continuum leakage versus quenching with the James Webb Space Telescope (2018)
- Brain size does not impact shoaling dynamics in unfamiliar groups of guppies (Poecilia reticulata) (2018)
- A stability criterion for switching Lur'e systems with switching-path restrictions (2018)
- Assortative interactions revealed by sorting of animal groups (2018)
- Worst-case prediction performance analysis of the Kalman filter (2018)
- Evolution of brain region volumes during artificial selection for relative brain size (2017)
- Unmixing hyperspectral data by using signal subspace sampling (2017)
- Tensor decompositions for the analysis of atomic resolution electron energy loss spectra (2017)
- Analysis of electron energy loss spectroscopy data using geometric extraction methods (2017)
- An efficient method for sorting and quantifying individual social traits based on group-level behaviour (2017)
- A machine-learning approach to measuring the escape of ionizing radiation from galaxies in the reionization epoch (2016)
- A direct proof of the discrete-time multivariate circle and Tsypkin criteria (2016)
- On the nuclear norm heuristic for a Hankel matrix completion problem (2015)
- Identifiability and convergence analysis of the MINLIP estimator (2015)
- System components of a general theory of software engineering (2015)
- Sparse estimation from noisy observations of an overdetermined linear system (2014)
- On the randomized Kaczmarz algorithm (2014)
- Asymmetric nu-tube support vector regression (2014)
- On the stability and optimality of an output feedback control law (2014)
- Approximate adjoint-based iterative learning control (2014)
- Least-Squares Support Vector Machines for the identification of Wiener-Hammerstein systems (2012)
- Sparse conjugate directions pursuit with application to fixed-size kernel models (2011)
- MINLIP for the identification of monotone Wiener systems (2011)
- Learning transformation models for ranking and survival analysis (2011)
- Support vector methods for survival analysis (2011)
- Improved performance on high-dimensional survival data by application of Survival-SVM (2011)
- Linear Systems, Sparse Solutions, and Sudoku (2010)
- Primal and dual model representations in kernel-based learning (2010)
- Additive survival least-squares support vector machines (2010)
- Least conservative support and tolerance tubes (2009)
Kapitel
Konferenser
- A HPC Co-scheduler with Reinforcement Learning (2021)
- ASA (2020)
- APTER (2019)
- Constraining Lyman continuum escape using Machine Learning (2018)
- High-dimensional online adaptive filtering (2017)
- Stability analysis of an adaptively sampled controller for SISO systems with nonlinear feedback (2015)
- A closed loop stability condition of switched systems applied to NCSs with packet loss (2015)
- Conditions for input-output stability of discrete-time Luré systems with time-varying delays (2015)
- Nuclear Norms for System Identification (2015)
- Randomized gossip algorithms for achieving consensus on the majority vote (2013)
- An adaptive compression algorithm in a deterministic world (2013)
- An online algorithm for controlling a monotone Wiener system (2012)
- An ellipsoid based, two-stage screening test for BPDN (2012)
- A cooperative decentralized PI control strategy (2012)
- On the Convergence Analysis of the MINLIP Estimator (2012)
- A simple recursive algorithm for learning a monotone Wiener system (2011)
- On Robustness in Kernel Based Regression (2010)
- Iterative Learning Control and Recursive Identification (2010)
- On the identification of monotone Wiener systems (2010)
- Efficient adaptive filtering for smooth linear FIR models (2010)
- Improved non-parametric sparse recovery with data matched penalties (2010)
- On the use of a clinical kernel in survival analysis (2010)