Evaluate error sources and uncertainty in large scale measurement systems
نویسندگان
چکیده
منابع مشابه
Exalt: Empowering Researchers to Evaluate Large-Scale Storage Systems
This paper presents Exalt, a library that gives back to researchers the ability to test the scalability of today’s large storage systems. To that end, we introduce Tardis, a data representation scheme that allows data to be identified and efficiently compressed even at low-level storage layers that are not aware of the semantics and formatting used by higher levels of the system. This compressi...
متن کاملSources of Variability in Large-scale Machine Learning Systems
We investigate sources of variability of a state-of-the-art distributed machine learning system for learning click and conversion prediction models for display advertising. We focus on three main sources of variability: asynchronous updates in the learning algorithm, downsampling of the data, and the non-deterministic order of examples received by each learning instance. We observe that some so...
متن کاملError - Correcting Codes and Applications to Large Scale Classification Systems
In this thesis, we study the performance of distributed output coding (DOC) and error-Correcting output coding (ECOC) as potential methods for expanding the class of tractable machine-learning problems. Using distributed output coding, we were able to scale a neural-network-based algorithm to handle nearly 10,000 output classes. In particular, we built a prototype OCR engine for Devanagari and ...
متن کاملPredictability and Uncertainty in Large-Scale Simulations
In many simulations in fluid and solid mechanics but also in molecular simulations there are many sources of uncertainty, e.g. associated with boundary conditions, material properties or equations of state and constitutive laws. These uncertainties may contribute to large errors in the simulation, typically much larger than the spatio-temporal discretization errors, leading to erroneous dynamic...
متن کاملA partition-based algorithm for clustering large-scale software systems
Clustering techniques are used to extract the structure of software for understanding, maintaining, and refactoring. In the literature, most of the proposed approaches for software clustering are divided into hierarchical algorithms and search-based techniques. In the former, clustering is a process of merging (splitting) similar (non-similar) clusters. These techniques suffered from the drawba...
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: Robotics and Computer-Integrated Manufacturing
سال: 2013
ISSN: 0736-5845
DOI: 10.1016/j.rcim.2012.06.003