Skip to search formSkip to main contentSkip to account menu

Stochastic optimization

Known as: Stochastic optimisation, Stochastic search 
Stochastic optimization (SO) methods are optimization methods that generate and use random variables. For stochastic problems, the random variables… 
Wikipedia (opens in a new tab)

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2014
2014
We propose RoBiRank, a ranking algorithm that is motivated by observing a close connection between evaluation metrics for… 
Review
2012
Review
2012
Shock wave-dominated systems are very sensitive to uncertainties in initial or boundary conditions as they often give rise to… 
2009
2009
Problem statement: Solving the state assignment problem means finding the optimum assignment for each state within a sequential… 
2009
2009
Color is the major source of information widely used in image analysis and content-based retrieval. Extracting dominant colors… 
2004
2004
  • C. B. Atkins
  • 2004
  • Corpus ID: 3205809
This paper presents a new photo collection page layout that attempts to maximize page coverage without having photos overlap… 
2002
2002
A new dynamical model is developed here to study the stochastic stability of Fault Tolerant Control Systems (FTCS) with multiple… 
2002
2002
One of the most significant problems in the training centers is presenting an exam timetabling due to enrolled subjects for each… 
1997
1997
| Population Based Incremental Learning (PBIL) is a stochastic search technique which combines characteristics of both the… 
Review
1996
Review
1996
This paper o ers a comprehensive review and classi cation of techniques to manipulate part routing sequences for manufacturing… 
1995
1995
We discuss the issue of missing and noisy data in nonlinear time-series prediction. We derive fundamental equations both for…