Boosting the Accuracy of Differentially-Private Histograms Through Consistency

We show that it is possible to significantly improve the accuracy of a general class of histogram queries while satisfying differential privacy. Our approach carefully chooses a set of queries to evaluate, and then exploits consistency constraints that should hold over the noisy output. In a post-processing phase, we compute the consistent input most likely to have produced the noisy output. The final output is differentially-private and consistent, but in addition, it is often much more accurate. We show, both theoretically and experimentally, that these techniques can be used for estimating the degree sequence of a graph very precisely, and for computing a histogram that can support arbitrary range queries accurately.Comment: 15 pages, 7 figures, minor revisions to previous versio

Trajectory Synthesis for Fisher Information Maximization

Estimation of model parameters in a dynamic system can be significantly improved with the choice of experimental trajectory. For general, nonlinear dynamic systems, finding globally "best" trajectories is typically not feasible; however, given an initial estimate of the model parameters and an initial trajectory, we present a continuous-time optimization method that produces a locally optimal trajectory for parameter estimation in the presence of measurement noise. The optimization algorithm is formulated to find system trajectories that improve a norm on the Fisher information matrix. A double-pendulum cart apparatus is used to numerically and experimentally validate this technique. In simulation, the optimized trajectory increases the minimum eigenvalue of the Fisher information matrix by three orders of magnitude compared to the initial trajectory. Experimental results show that this optimized trajectory translates to an order of magnitude improvement in the parameter estimate error in practice.Comment: 12 page

DNN-Based Multi-Frame MVDR Filtering for Single-Microphone Speech Enhancement

Multi-frame approaches for single-microphone speech enhancement, e.g., the multi-frame minimum-variance-distortionless-response (MVDR) filter, are able to exploit speech correlations across neighboring time frames. In contrast to single-frame approaches such as the Wiener gain, it has been shown that multi-frame approaches achieve a substantial noise reduction with hardly any speech distortion, provided that an accurate estimate of the correlation matrices and especially the speech interframe correlation vector is available. Typical estimation procedures of the correlation matrices and the speech interframe correlation (IFC) vector require an estimate of the speech presence probability (SPP) in each time-frequency bin. In this paper, we propose to use a bi-directional long short-term memory deep neural network (DNN) to estimate a speech mask and a noise mask for each time-frequency bin, using which two different SPP estimates are derived. Aiming at achieving a robust performance, the DNN is trained for various noise types and signal-to-noise ratios. Experimental results show that the multi-frame MVDR in combination with the proposed data-driven SPP estimator yields an increased speech quality compared to a state-of-the-art model-based estimator

Maximum likelihood, parametric component separation and CMB B-mode detection in suborbital experiments

We investigate the performance of the parametric Maximum Likelihood component separation method in the context of the CMB B-mode signal detection and its characterization by small-scale CMB suborbital experiments. We consider high-resolution (FWHM=8') balloon-borne and ground-based observatories mapping low dust-contrast sky areas of 400 and 1000 square degrees, in three frequency channels, 150, 250, 410 GHz, and 90, 150, 220 GHz, with sensitivity of order 1 to 10 micro-K per beam-size pixel. These are chosen to be representative of some of the proposed, next-generation, bolometric experiments. We study the residual foreground contributions left in the recovered CMB maps in the pixel and harmonic domain and discuss their impact on a determination of the tensor-to-scalar ratio, r. In particular, we find that the residuals derived from the simulated data of the considered balloon-borne observatories are sufficiently low not to be relevant for the B-mode science. However, the ground-based observatories are in need of some external information to permit satisfactory cleaning. We find that if such information is indeed available in the latter case, both the ground-based and balloon-borne experiments can detect the values of r as low as ~0.04 at 95% confidence level. The contribution of the foreground residuals to these limits is found to be then subdominant and these are driven by the statistical uncertainty due to CMB, including E-to-B leakage, and noise. We emphasize that reaching such levels will require a sufficient control of the level of systematic effects present in the data.Comment: 18 pages, 12 figures, 6 table

Sobol' indices for problems defined in non-rectangular domains

A novel theoretical and numerical framework for the estimation of Sobol sensitivity indices for models in which inputs are confined to a non-rectangular domain (e.g., in presence of inequality constraints) is developed. Two numerical methods, namely the quadrature integration method which may be very efficient for problems of low and medium dimensionality and the MC/QMC estimators based on the acceptance-rejection sampling method are proposed for the numerical estimation of Sobol sensitivity indices. Several model test functions with constraints are considered for which analytical solutions for Sobol sensitivity indices were found. These solutions were used as benchmarks for verifying numerical estimates. The method is shown to be general and efficient

An investigation of the observability of ocean-surface parameters using GEOS-3 backscatter data

The degree to which ocean surface roughness can be synoptically observed through use of the information extracted from the GEOS-3 backscattered waveform data was evaluated. Algorithms are given for use in estimating the radar sensed waveheight distribution or ocean-surface impulse response. Other factors discussed include comparisons between theoretical and experimental radar cross section values, sea state bias effects, spatial variability of significant waveheight data, and sensor-related considerations