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Learning from untrusted data:

, In: Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing,

Charikar, Moses ; Steinhardt, Jacob ; Valiant, Gregory - p. 47-60 , 2017

Link: https://dl.acm.org/doi/10.1145/3055399.3055491

RT 
T1 <cTitle>Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing</cTitle>: T1 <Title>Learning from untrusted data</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3055491&Exemplar=1&LAN=DE
				
A1 Charikar, Moses
A1 Steinhardt, Jacob
A1 Valiant, Gregory
PB ACM
YR 2017
K1 high-dimensional statistics
K1 outlier removal
K1 robust learning
K1 Theory of computation
K1 Theory and algorithms for application domains
K1 Machine learning theory
K1 Models of learning
K1 Security and privacy
K1 Formal methods and theory of security
K1 Formal security models
K1 Intrusion/anomaly detection and malware mitigation
K1 Intrusion detection systems
K1 Artificial immune systems
K1 Sample complexity and generalization bounds
K1 Randomness, geometry and discrete structures
K1 Random projections and metric embeddings
K1 Random network models
SP 47
OP 60
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3055399.3055491
DO https://dl.acm.org/doi/10.1145/3055399.3055491
SF ELIB - SuUB Bremen

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