Jul 17, 2024 · We study the problem of estimating a large, low-rank matrix corrupted by additive noise of unknown covariance, assuming one has access to additional side ...
5 days ago · Yet, to the best of our knowledge, there are no established goodness-of-fit tests for elliptical models that are theoretically supported in high dimensions.
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8 days ago · In general, the cross projection test approach for high-dimensional mean vectors via multiple random splits is more powerful for the two-sample case.
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Aug 4, 2024 · This paper introduces a novel framework called Mode-wise Principal Subspace Pursuit. (MOP-UP) to extract hidden variations in both the row and column ...
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High-performance deep spiking neural networks with 0.3 spikes per ...
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6 days ago · Our approach accomplishes high-performance classification with less than 0.3 spikes per neuron, lending itself for an energy-efficient implementation. We also ...
Aug 5, 2024 · Longer observation of spike firing sequences allows for higher accuracy in parameter estimation but increases latency and reduces energy efficiency. In this ...
5 days ago · Abstract. Standard high-dimensional regression methods assume that the underlying coefficient vector is sparse. This might not be true in some cases, ...
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Jul 19, 2024 · The CP decomposition for high dimensional non-orthogonal spiked tensors is an important problem with broad applications across many disciplines.
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4 days ago · Following Ganguli and Simoncelli (2014), we perform the maximization under two constraints: 1- that there is a finite number of spikes available for coding, and ...
Jul 19, 2024 · The former mapping pattern typically involves reconstructing high-dimensional outputs with spatial structures from sparse inputs, exhibiting high dimension ...