Multiple Hypothesis Semantic Mapping for Robust Data Association
نویسندگان
چکیده
منابع مشابه
Hypothesis Testing over Factorizations for Data Association
The issue of data association arises frequently in sensor networks; whenever multiple sensors and sources are present, it may be necessary to determine which observations from different sensors correspond to the same target. In highly uncertain environments, one may need to determine this correspondence without the benefit of an a priori known joint signal/sensor model. This paper examines the ...
متن کاملMultiple Hypothesis Testing for Data Mining
INTRODUCTION A number of important problems in data mining can be usefully addressed within the framework of statistical hypothesis testing. However, while the conventional treatment of statistical significance deals with error probabilities at the level of a single variable, practical data mining tasks tend to involve thousands, if not millions , of variables. This Chapter looks at some of the...
متن کاملSupplementary Appendix to: Hypothesis testing at the extremes: fast and robust association for high-throughput data
We assume exchangeability, but in many applications we expect that the elements of (say) y are in fact independent. However, the weaker exchangeability requirement is useful to clarify that various forms of pre-treating the data, such as normalization techniques, do not invalidate permutation testing. The same comment applies to normalization of X, provided that X and y are normalized separatel...
متن کاملHypothesis testing at the extremes: fast and robust association for high-throughput data.
A number of biomedical problems require performing many hypothesis tests, with an attendant need to apply stringent thresholds. Often the data take the form of a series of predictor vectors, each of which must be compared with a single response vector, perhaps with nuisance covariates. Parametric tests of association are often used, but can result in inaccurate type I error at the extreme thres...
متن کاملIndex Mapping for Robust Multiple Description Lattice Vector Quantizer INDEX MAPPING FOR ROBUST MULTIPLE DESCRIPTION LATTICE VECTOR QUANTIZER
Multiple Description Coding (MDC) is a source coding technique which generates several descriptions of a signal such that the reconstruction gradually refines with the number of decoded descriptions. Conventionally, the design of MDC has largely focused on combating the description loss. This thesis considers the construction of robust multiple description lattice vector quantizers (MDLVQ) by a...
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: IEEE Robotics and Automation Letters
سال: 2019
ISSN: 2377-3766,2377-3774
DOI: 10.1109/lra.2019.2925756