Advanced battery management strategies for a sustainable energy future: Multilayer design concepts and research trends
Lithium-ion batteries are promising energy storage devices for electric vehicles and
renewable energy systems. However, due to complex electrochemical processes, potential …
renewable energy systems. However, due to complex electrochemical processes, potential …
Data cleaning: Overview and emerging challenges
Detecting and repairing dirty data is one of the perennial challenges in data analytics, and
failure to do so can result in inaccurate analytics and unreliable decisions. Over the past few …
failure to do so can result in inaccurate analytics and unreliable decisions. Over the past few …
Holoclean: Holistic data repairs with probabilistic inference
T Rekatsinas, X Chu, IF Ilyas, C Ré - ar** machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …
relationships has been a longstanding goal of AI. Over the last decade, large-scale …
Automated machine learning: State-of-the-art and open challenges
With the continuous and vast increase in the amount of data in our digital world, it has been
acknowledged that the number of knowledgeable data scientists can not scale to address …
acknowledged that the number of knowledgeable data scientists can not scale to address …
Data fusion
J Bleiholder, F Naumann - ACM computing surveys (CSUR), 2009 - dl.acm.org
The development of the Internet in recent years has made it possible and useful to access
many different information systems anywhere in the world to obtain information. While there …
many different information systems anywhere in the world to obtain information. While there …
Katara: A data cleaning system powered by knowledge bases and crowdsourcing
Classical approaches to clean data have relied on using integrity constraints, statistics, or
machine learning. These approaches are known to be limited in the cleaning accuracy …
machine learning. These approaches are known to be limited in the cleaning accuracy …
Data lifecycle challenges in production machine learning: a survey
Machine learning has become an essential tool for gleaning knowledge from data and
tackling a diverse set of computationally hard tasks. However, the accuracy of a machine …
tackling a diverse set of computationally hard tasks. However, the accuracy of a machine …
Holistic data cleaning: Putting violations into context
Data cleaning is an important problem and data quality rules are the most promising way to
face it with a declarative approach. Previous work has focused on specific formalisms, such …
face it with a declarative approach. Previous work has focused on specific formalisms, such …