ouuni

Metric Learning A Survey

Themetriclearningproblemisconcernedwithlearningadistance functiontunedtoaparticulartask,andhasbeenshowntobeuseful whenusedinconjunctionwithnearest-nei

Theory of Active Learning

Activelearningisaprotocolforsupervisedmachinelearning,inwhichalearningalgorithmsequentiallyrequeststhelabelsofselecteddatapointsfromalargepoolofunlabe

Kernels for Vector_Valued Functions A Review

Kernelmethodsareamongthemostpopulartechniquesinmachinelearning.Fromaregularizationperspec-tivetheyplayacentralroleinregularizationtheoryastheyprovidea

MRFlib马尔科夫图像处理开发包

MRFlib Markov Image Processing Development Kit

统计工具箱computationalstatisticstoolbox

包含很多的统计计算函数，例如马尔科夫和参数估计等等，可以直接使用，具有一定的价值。可以参考。

DictionaryLearninginVisualComputing

e last few years have witnessed fast development on dictionary learning approaches for a set of visual computing tasks, largely due to their utilizat

Graph_BasedSemi_SupervisedLearning

While labeled data is expensive to prepare, ever increasing amounts of unlabeled data is becoming widely available. In order to adapt to this phenomen

ParticleFiltersforRobotNavigation

Autonomous navigation is an essential capability for mobile robots. In order to operate robustly, a robot needs to know what the environment looks lik

DomainAdaptationforVisualRecognition

Domain adaptation is an active, emerging research area that attempts to address the changes in data distribution across training and testing datasets.

InformationTheoryandStatisticsATutorial

This tutorial is concerned with applications of information theory concepts in statistics, in the finite alphabet setting. The information measure kno