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Found 7 papers, 0 papers with code
Detecting Suspicious Events in Fast Information Flows
We describe a computational feather-light and intuitive, yet provably efficient algorithm, named HALFADO.
Longitudinal Support Vector Machines for High Dimensional Time Series
We consider the problem of learning a classifier from observed functional data.
APTER: Aggregated Prognosis Through Exponential Reweighting
This paper considers the task of learning how to make a prognosis of a patient based on his/her micro-array expression levels.
FADO: A Deterministic Detection/Learning Algorithm
This paper proposes and studies a detection technique for adversarial scenarios (dubbed deterministic detection).
A machine-learning approach to measuring the escape of ionizing radiation from galaxies in the reionization epoch
Recent observations of galaxies at $z \gtrsim 7$, along with the low value of the electron scattering optical depth measured by the Planck mission, make galaxies plausible as dominant sources of ionizing photons during the epoch of reionization.
Astrophysics of Galaxies
Sparse Estimation From Noisy Observations of an Overdetermined Linear System
This note studies a method for the efficient estimation of a finite number of unknown parameters from linear equations, which are perturbed by Gaussian noise.
A Risk Minimization Principle for a Class of Parzen Estimators
This paper explores the use of a Maximal Average Margin (MAM) optimality principle for the design of learning algorithms.
