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Loss function

Known as: Zero-one loss, Loss, Risk function 
In mathematical optimization, statistics, decision theory and machine learning, a loss function or cost function is a function that maps an event or… 
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Related topics

Related topics

50 relations
Adaptive filterBackpropagationBootstrapping (statistics)Constrained optimization

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2010
Highly Cited
2010
Coordinated linear beamforming in downlink multi-cell wireless networks
We consider the problem of co-channel interference mitigation in a downlink multi-cell wireless network. Assuming that each… 
Highly Cited
2008
Highly Cited
2008
Joint Power and Channel Allocation for Cognitive Radios
Spectrum scarcity is the major challenge facing all parties working in the telecommunications industry. As recently shown, the… 
Highly Cited
2007
Highly Cited
2007
Sliding-Mode Neuro-Controller for Uncertain Systems
In this paper, a method that allows for the merger of the good features of sliding-mode control and neural network (NN) design is… 
Highly Cited
2005
Highly Cited
2005
Context-Independent Scatter and Tabu Search for Permutation Problems
In this paper, we develop a general-purpose heuristic for permutations problems. The procedure is based on the scatter-search and… 
Highly Cited
1999
Highly Cited
1999
Introduction to Model Based Predictive Control
Model (Based) Predictive Control (MBPC or MPC) originated in the late seventies and has developed considerably since then. The… 
Highly Cited
1995
Highly Cited
1995
Evolutionary identification of cloth animation models
This paper presents an application of evolutionary genetic techniques to the identification of internal parameters of a mass… 
Highly Cited
1994
Highly Cited
1994
Polygonal approximation using a competitive Hopfield neural network
Highly Cited
1989
Highly Cited
1989
A directed search method for test generation using a concurrent simulator
A description is given of the application of a concurrent fault simulator to automatic test vector generation. As faults are… 
Highly Cited
1986
Highly Cited
1986
On the Accurate Determination of Search Directions for Simple Differentiable Penalty Functions
On presente des methodes fiables de calcul d'une direction de recherche utilisee dans les methodes sequentielles de resolution… 
Highly Cited
1984
Highly Cited
1984
Adaptive filtering with binary reinforcement
Recently there has been increased interest in high speed adaptive filtering where the usual stochastic gradient or least mean… 
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