
An Efficient OneClass SVM for Anomaly Detection in the Internet of Things
Insecure Internet of things (IoT) devices pose significant threats to cr...
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SelfTuning Bandits over Unknown CovariateShifts
Bandits with covariates, a.k.a. contextual bandits, address situations w...
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A Comparative Study of Network Traffic Representations for Novelty Detection
Data representation plays a critical role in the performance of novelty ...
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A NoFreeLunch Theorem for MultiTask Learning
Multitask learning and related areas such as multisource domain adaptat...
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On the Value of Target Data in Transfer Learning
We aim to understand the value of additional labeled or unlabeled target...
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Kernel Sketching yields Kernel JL
The main contribution of the paper is to show that Gaussian sketching of...
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Quickshift++: Provably Good Initializations for SampleBased Mean Shift
We provide initial seedings to the Quick Shift clustering algorithm, whi...
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Marginal Singularity, and the Benefits of Labels in CovariateShift
We present new minimax results that concisely capture the relative benef...
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Achieving the time of 1NN, but the accuracy of kNN
We propose a simple approach which, given distributed computing resource...
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An Adaptive Strategy for Active Learning with Smooth Decision Boundary
We present the first adaptive strategy for active learning in the settin...
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Adaptivity to Noise Parameters in Nonparametric Active Learning
This work addresses various open questions in the theory of active learn...
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Modalset estimation with an application to clustering
We present a first procedure that can estimate  with statistical consi...
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Consistency of Causal Inference under the Additive Noise Model
We analyze a family of methods for statistical causal inference from sam...
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Which Spatial Partition Trees are Adaptive to Intrinsic Dimension?
Recent theory work has found that a special type of spatial partition tr...
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kNN Regression Adapts to Local Intrinsic Dimension
Many nonparametric regressors were recently shown to converge at rates t...
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Pruning nearest neighbor cluster trees
Nearest neighbor (kNN) graphs are widely used in machine learning and d...
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Samory Kpotufe
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