Doctor2Vec: Dynamic Doctor Representation Learning for Clinical Trial Recruitment. (arXiv:1911.10395v1 [cs.LG])

Massive electronic health records (EHRs) enable the success of learning accurate patient representations to support various predictive health applications. In contrast, doctor representation was not well studied despite that doctors play pivotal roles in healthcare. How to construct the right doctor representations? How to use doctor representation to solve important health analytic problems? In this…

Intermittent Demand Forecasting with Deep Renewal Processes. (arXiv:1911.10416v1 [cs.LG])

Intermittent demand, where demand occurrences appear sporadically in time, is a common and challenging problem in forecasting. In this paper, we first make the connections between renewal processes, and a collection of current models used for intermittent demand forecasting. We then develop a set of models that benefit from recurrent neural networks to parameterize conditional…

DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles. (arXiv:1911.10418v1 [cs.LG])

Selecting and combining the outlier scores of different base detectors used within outlier ensembles can be quite challenging in the absence of ground truth. In this paper, an unsupervised outlier detector combination framework called DCSO is proposed, demonstrated and assessed for the dynamic selection of most competent base detectors, with an emphasis on data locality.…

Low Rank Approximation for Smoothing Spline via Eigensystem Truncation. (arXiv:1911.10434v1 [stat.ML])

Smoothing splines provide a powerful and flexible means for nonparametric estimation and inference. With a cubic time complexity, fitting smoothing spline models to large data is computationally prohibitive. In this paper, we use the theoretical optimal eigenspace to derive a low rank approximation of the smoothing spline estimates. We develop a method to approximate the…

A More Refined Mobile Edge Cache Replacement Scheme for Adaptive Video Streaming with Mutual Cooperation in Multi-MEC Servers. (arXiv:1911.10723v1 [eess.IV])

In this paper, we propose a more refined video segment based Mobile Edge Computing (MEC) enhanced cache update strategy, which takes into account the client’s playback status and transmission state, MEC cache capacity and the popularity of each segment, to improve the quality of experience (QoE) of clients and the use ratio of MEC cache.…

Boundary feedback stabilization of a reaction-diffusion equation with Robin boundary conditions and state-delay. (arXiv:1911.10761v1 [math.OC])

This paper discusses the boundary feedback stabilization of a reaction-diffusion equation with Robin boundary conditions and in the presence of a time-varying state-delay. The proposed control design strategy is based on a finite-dimensional truncated model obtained via a spectral decomposition. By an adequate selection of the number of modes of the original infinite-dimensional system, we…

Invertible DNN-based nonlinear time-frequency transform for speech enhancement. (arXiv:1911.10764v1 [eess.AS])

We propose an end-to-end speech enhancement method with trainable time-frequency~(T-F) transform based on invertible deep neural network~(DNN). The resent development of speech enhancement is brought by using DNN. The ordinary DNN-based speech enhancement employs T-F transform, typically the short-time Fourier transform~(STFT), and estimates a T-F mask using DNN. On the other hand, some methods have…

Axisymmetric diffeomorphisms and ideal fluids on Riemannian 3-manifolds. (arXiv:1911.10302v1 [math.DG])

We study the Riemannian geometry of 3D axisymmetric ideal fluids. We prove that the $L^2$ exponential map on the group of volume-preserving diffeomorphisms of a $3$-manifold is Fredholm along axisymmetric flows with sufficiently small swirl. Along the way, we define the notions of axisymmetric and swirl-free diffeomorphisms of any manifold with suitable symmetries and show…