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Minimax Estimation of Functionals of Discrete Distributions
TLDR
We propose a general methodology for the construction and analysis of essentially minimax estimators for a wide class of functionals of finite dimensional parameters, and elaborate on the case of discrete distributions, where the support size S is comparable with or even much larger than the number of observations n. Expand
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Local moment matching: A unified methodology for symmetric functional estimation and distribution estimation under Wasserstein distance
TLDR
We present \emph{Local Moment Matching (LMM)}, a unified methodology for symmetric functional estimation and distribution estimation under Wasserstein distance. Expand
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Performance Limits and Geometric Properties of Array Localization
TLDR
This paper determines the localization accuracy of an agent, which is equipped with an antenna array and localizes itself using wireless measurements with anchor nodes, in a far-field environment. Expand
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Minimax estimation of the L1 distance
TLDR
We consider the problem of estimating the L1 distance between two discrete probability measures P and Q from empirical data in a nonasymptotic and large alphabet setting. Expand
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Face Sketch Synthesis via Sparse Representation
TLDR
A new face sketch synthesis method is presented, which is inspired by recent advances in sparse signal representation and neuroscience that human brain probably perceives images using high-level features which are sparse. Expand
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Geometric Lower Bounds for Distributed Parameter Estimation under Communication Constraints
TLDR
We consider parameter estimation in distributed networks, where each sensor in the network observes an independent sample from an underlying distribution and has $k$ bits to communicate its sample to a centralized processor which computes an estimate of a desired parameter. Expand
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Maximum Likelihood Estimation of Functionals of Discrete Distributions
TLDR
We consider the problem of estimating functionals of discrete distributions, and focus on a tight (up to universal multiplicative constants for each specific functional) nonasymptotic analysis of the worst case squared error risk of widely used estimators. Expand
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Optimal rates of entropy estimation over Lipschitz balls
TLDR
We consider the problem of minimax estimation of the entropy of a density over Lipschitz balls. Expand
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Minimax Estimation of the $L_1$ Distance
TLDR
We consider the problem of estimating the $L_{1}$ distance between two discrete probability measures $P$ and $Q$ from empirical data in a nonasymptotic and large alphabet setting. Expand
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Avoiding False Positive in Multi-Instance Learning
  • Y. Han, Qing Tao, Jue Wang
  • Mathematics, Computer Science
  • NIPS
  • 6 December 2010
TLDR
In multi-instance learning, there are two kinds of prediction failure, i.e., false negative and false positive. Expand
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