منابع مشابه
Robust Subspace Discovery via Relaxed Rank Minimization
This letter examines the problem of robust subspace discovery from input data samples (instances) in the presence of overwhelming outliers and corruptions. A typical example is the case where we are given a set of images; each image contains, for example, a face at an unknown location of an unknown size; our goal is to identify or detect the face in the image and simultaneously learn its model....
متن کاملDyadic Classification Trees via Structural Risk Minimization
Classification trees are one of the most popular types of classifiers, with ease of implementation and interpretation being among their attractive features. Despite the widespread use of classification trees, theoretical analysis of their performance is scarce. In this paper, we show that a new family of classification trees, called dyadic classification trees (DCTs), are near optimal (in a min...
متن کاملRanking via Robust Binary Classification
We propose RoBiRank, a ranking algorithm that is motivated by observing a close connection between evaluation metrics for learning to rank and loss functions for robust classification. It shows competitive performance on standard benchmark datasets against a number of other representative algorithms in the literature. We also discuss extensions of RoBiRank to large scale problems where explicit...
متن کاملRobust Control via Genetic Algorithms and Integral Criteria Minimization
PID controllers have found extensive industrial applications for several decades. Recently, mixed H2/H∞ optimal control problems have received a great deal of attention from the viewpoint of theoretical design. Mixed H2/H∞ control design approaches are useful for robust performance for systems under parameter perturbation and uncertain disturbance. In this paper, a design procedure is proposed ...
متن کاملIntegrated Robust Optimal Design (IROD) via sensitivity minimization
A novel Integrated Robust Optimal Design (IROD) methodology is presented in this work which combines a traditional sensitivity theory with relatively new advancements in Bilinear Matrix Inequality (BMI) constrained optimization problems. IROD provides the least conservative approach for robust control synthesis. The proposed methodology is demonstrated using numerical examples of integrated con...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Machine Learning
سال: 2020
ISSN: 0885-6125,1573-0565
DOI: 10.1007/s10994-019-05863-6