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  1. Robust pervasive context-aware augmented reality (AR) has the potential to enable a range of applications that support users in reaching their personal and professional goals. In such applications, AR can be used to deliver richer, more immersive, and more timely just in time adaptive interventions (JITAI) than conventional mobile solutions, leading to more effective support of the user. This position paper defines a research agenda centered on improving AR applications' environmental, user, and social context awareness. Specifically, we argue for two key architectural approaches that will allow pushing AR context awareness to the next level: use of wearable and Internetmore »of Things (IoT) devices as additional data streams that complement the data captured by the AR devices, and the development of edge computing-based mechanisms for enriching existing scene understanding and simultaneous localization and mapping (SLAM) algorithms. The paper outlines a collection of specific research directions in the development of such architectures and in the design of next-generation environmental, user, and social context awareness algorithms.« less
    Free, publicly-accessible full text available March 13, 2023
  2. Abstract There have been 77 TNOs discovered to be librating in the distant trans-Neptunian resonances (beyond the 2:1 resonance, at semimajor axes greater than 47.7 au) in four well-characterized surveys: the Outer Solar System Origins Survey (OSSOS) and three similar prior surveys. Here, we use the OSSOS Survey Simulator to measure their intrinsic orbital distributions using an empirical parameterized model. Because many of the resonances had only one or very few detections, j : k resonant objects were grouped by k in order to have a better basis for comparison between models and reality. We also use the Survey Simulatormore »to constrain their absolute populations, finding that they are much larger than predicted by any published Neptune migration model to date; we also find population ratios that are inconsistent with published models, presenting a challenge for future Kuiper Belt emplacement models. The estimated population ratios between these resonances are largely consistent with scattering–sticking predictions, though further discoveries of resonant TNOs with high-precision orbits will be needed to determine whether scattering–sticking can explain the entire distant resonant population or not.« less
    Free, publicly-accessible full text available May 1, 2023
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  9. Recent research shows that the dynamics of an infinitely wide neural network (NN) trained by gradient descent can be characterized by Neural Tangent Kernel (NTK) [27]. Under the squared loss, the infinite-width NN trained by gradient descent with an infinitely small learning rate is equivalent to kernel regression with NTK [4]. However, the equivalence is only known for ridge regression currently [6], while the equivalence between NN and other kernel machines (KMs), e.g. support vector machine (SVM), remains unknown. Therefore, in this work, we propose to establish the equivalence between NN and SVM, and specifically, the infinitely wide NN trainedmore »by soft margin loss and the standard soft margin SVM with NTK trained by subgradient descent. Our main theoretical results include establishing the equivalence between NN and a broad family of L2 regularized KMs with finite width bounds, which cannot be handled by prior work, and showing that every finite-width NN trained by such regularized loss functions is approximately a KM. Furthermore, we demonstrate our theory can enable three practical applications, including (i) non-vacuous generalization bound of NN via the corresponding KM; (ii) nontrivial robustness certificate for the infinite-width NN (while existing robustness verification methods would provide vacuous bounds); (iii) intrinsically more robust infinite-width NNs than those from previous kernel regression.« less
    Free, publicly-accessible full text available December 1, 2022
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