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2410.08576
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A Theoretical Framework for AI-driven data quality monitoring in high-volume data environments
11 October 2024
Nikhil Bangad
Vivekananda Jayaram
Manjunatha Sughaturu Krishnappa
Amey Ram Banarse
Darshan Mohan Bidkar
Akshay Nagpal
Vidyasagar Parlapalli
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Papers citing
"A Theoretical Framework for AI-driven data quality monitoring in high-volume data environments"
12 / 12 papers shown
Title
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Deep Visual Domain Adaptation: A Survey
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Doyen Sahoo
Jing Lu
P. Zhao
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NIMA: Neural Image Assessment
Hossein Talebi
P. Milanfar
3DH
92
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15 Sep 2017
An Overview of Multi-Task Learning in Deep Neural Networks
Sebastian Ruder
CVBM
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A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
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Federated Learning: Strategies for Improving Communication Efficiency
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H. B. McMahan
Felix X. Yu
Peter Richtárik
A. Suresh
Dave Bacon
FedML
314
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18 Oct 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data
H. B. McMahan
Eider Moore
Daniel Ramage
S. Hampson
Blaise Agüera y Arcas
FedML
412
17,615
0
17 Feb 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAtt
FaML
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16 Feb 2016
Distributed Representations of Words and Phrases and their Compositionality
Tomas Mikolov
Ilya Sutskever
Kai Chen
G. Corrado
J. Dean
NAI
OCL
406
33,573
0
16 Oct 2013
Practical Bayesian Optimization of Machine Learning Algorithms
Jasper Snoek
Hugo Larochelle
Ryan P. Adams
382
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