The Min-Max Algorithm and Isotonic Regression
نویسندگان
چکیده
منابع مشابه
Min-max Bias Robust Regression
This the problem maximum asymptotic bias of regression estimates over a-contamination for the joint of the response carriers. Two classes of estimates are treated: (1) Msestimates with bounded function p applied to the scaled residuals, using a very general class of scale estimates, and (2) Bounded influence function type generalized M-estimates. Estimates in the first class are oblta1rled as p...
متن کاملImproved Max-Min Scheduling Algorithm
In this research paper, additional constrains have been considered to progress a holistic analysis based algorithm based on Max-Min algorithm, which work on principle of sorting jobs(cloudlets) based on completion time of cloudlets. The improved algorithms here also reviews the job characteristics in method of size, pattern, payload ratio and available storage blocks in particular cluster of co...
متن کاملA Hybrid Min-min Max-min Algorithm with Improved Performance
The high cost of supercomputers and the need for large-scale computational resources has led to the development of network of computational resources known as Grid. To better use tremendous capabilities of this large scale distributed system, effective and efficient scheduling algorithms are needed. Many such algorithms have been designed and implemented. We introduce a new scheduling algorithm...
متن کاملThe Isotron Algorithm: High-Dimensional Isotonic Regression
The Perceptron algorithm elegantly solves binary classification problems that have a margin between positive and negative examples. Isotonic regression (fitting an arbitrary increasing function in one dimension) is also a natural problem with a simple solution. By combining the two, we get a new but very simple algorithm with strong guarantees. Our ISOTRON algorithm provably learns Single Index...
متن کاملA smoothing algorithm for finite min-max-min problems
We generalize a smoothing algorithm for finite min–max to finite min– max–min problems. We apply a smoothing technique twice, once to eliminate the inner min operator and once to eliminate the max operator. In mini–max problems, where only the max operator is eliminated, the approximation function is decreasing with respect to the smoothing parameter. Such a property is convenient to establish ...
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: The Annals of Statistics
سال: 1983
ISSN: 0090-5364
DOI: 10.1214/aos/1176346153