- Read more about DETECTION OF SHIP WAKES IN SAR IMAGERY USING CAUCHY REGULARISATION
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- Read more about On design of optimal smart meter privacy control strategy against adversarial MAP detection
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We study the optimal control problem of the maximum a posteriori (MAP) state sequence detection of an adversary using smart meter data. The privacy leakage is measured using the Bayesian risk and the privacy-enhancing control is achieved in real-time using an energy storage system. The control strategy is designed to minimize the expected performance of a non-causal adversary at each time instant. With a discrete-state Markov model, we study two detection problems: when the adversary is unaware or aware of the control.

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- Read more about ICASSP 2020
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We address the problem of detection, in the frequency domain, of a M-dimensional time series modeled as the output of a M × K MIMO filter driven by a K-dimensional Gaussian white noise, and disturbed by an additive M-dimensional Gaussian col- ored noise. We consider the study of test statistics based of the Spectral Coherence Matrix (SCM) obtained as renormalization of the smoothed periodogram matrix of the observed time series over N samples, and with smoothing span B.

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- Read more about Entropy Coders Based on the Splitting of Lexicographic Intervals
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## poster.pdf

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- Read more about Estimating Structural Missing Values via Low-tubal-rank Tensor Completion
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The recently proposed Tensor Nuclear Norm (TNN) minimization has been widely used for tensor completion. However, previous works didn’t consider the structural difference between the observed data and missing data, which widely exists in many applications. In this paper, we propose to incorporate a constraint item on the missing values into low-tubal-rank tensor completion to promote the structural hypothesis

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- Read more about Particle Filtering on the Complex Stiefel Manifold with Application to Subspace Tracking
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In this paper, we extend previous particle filtering methods whose states were constrained to the (real) Stiefel manifold to the complex case. The method is then applied to a Bayesian formulation of the subspace tracking problem. To implement the proposed particle filter, we modify a previous MCMC algorithm so as to simulate from densities defined on the complex manifold. Also, to compute subspace estimates from particle approximations, we extend existing averaging methods to complex Grassmannians.

## slides.pdf

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- Read more about On the Robustness of Causal Discovery with Additive Noise Models on Discrete Data
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- Read more about A whiteness test based on the spectral measure of large non-Hermitian random matrices
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In the context of multivariate time series, a whiteness test against an MA(1)

correlation model is proposed. This test is built on the eigenvalue

distribution (spectral measure) of the non-Hermitian one-lag sample

autocovariance matrix, instead of its singular value distribution. The large

dimensional limit spectral measure of this matrix is derived. To obtain this

result, a control over the smallest singular value of a related random matrix

is provided. Numerical simulations show the excellent performance of this

test.

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- Read more about ROBUST M-ESTIMATION BASED MATRIX COMPLETION
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Conventional approaches to matrix completion are sensitive to outliers and impulsive noise. This paper develops robust and computationally efficient M-estimation based matrix completion algorithms. By appropriately arranging the observed entries, and then applying alternating minimization, the robust matrix completion problem is converted into a set of regression M-estimation problems. Making use of differ- entiable loss functions, the proposed algorithm overcomes a weakness of the lp-loss (p ≤ 1), which easily gets stuck in an inferior point.

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