Despite extensive efforts in computational modeling of the emotion of surprise, the literature seems far from reaching a consensus. Our contribution is to provide in silico evidence for the theory of Bayesian surprise...
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In this paper, an N-coalitions game of multi-agents system is investigated, which is a combination problem of distributed optimization and game. The objective functions of the coalition depend on not only its members...
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We compute flavor non-singlet meson screening masses in the chiral limit of QCD with Nf = 3 quarks. The calculation is carried out at 12 temperatures from T ≈ 1 GeV up to the electroweak scale. For each temperature w...
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As one of effective methods, topology optimization design has been extensively applied to improve structural performance and efficiency of material usage for lightweight automobile. The chassis structure is an importa...
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This paper investigates the expressiveness of a fragment of frstorder sentences in Gaifman normal form, namely the positive Boolean combinations of basic local sentences. We show that they match exactly the frst-order...
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We compute hybrid static potentials in SU(3) lattice Yang-Mills theory at short quark-antiquark separations using four different small lattice spacings as small as 0.04 fm. The resulting static potentials are importan...
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As the number of edge devices grows to tens of billions, the importance of intelligent computing has been shifted from cloud datacenters to edge devices. On-device training, which enables the personalization of a mach...
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We develop greedy algorithms to approximate the optimal solution to the multi-fidelity sensor selection problem, which is a cost constrained optimization problem prescribing the placement and number of cheap (low sign...
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We develop greedy algorithms to approximate the optimal solution to the multi-fidelity sensor selection problem, which is a cost constrained optimization problem prescribing the placement and number of cheap (low signal-to-noise) and expensive (high signal-to-noise) sensors in an environment or state space. Specifically, we evaluate the composition of cheap and expensive sensors, along with their placement, required to achieve accurate reconstruction of a high-dimensional state. We use the column-pivoted QR decomposition to obtain preliminary sensor positions. How many of each type of sensor to use is highly dependent upon the sensor noise levels, sensor costs, overall cost budget, and the singular value spectrum of the data measured. Such nuances allow us to provide sensor selection recommendations based on computational results for asymptotic regions of parameter space. We also present a systematic exploration of the effects of the number of modes and sensors on reconstruction error when using one type of sensor. Our extensive exploration of multi-fidelity sensor composition as a function of data characteristics is the first of its kind to provide guidelines towards optimal multi-fidelity sensor selection.
Some technologies exhibit positive feedback loops; the effect of their own progress is to accelerate their own further progress, constant acceleration in other words. Using ever more powerful computational models to d...
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Some technologies exhibit positive feedback loops; the effect of their own progress is to accelerate their own further progress, constant acceleration in other words. Using ever more powerful computational models to design ever more powerful computational models is obviously such a case. Obtaining (and holding) a technologic lead in the presence of a positive feedback loop is inherently different than doing so in a field where persistence—just doggedly slogging it out—is the driving mechanism for progress. Put differently, under constant acceleration the distance between two entities can only increase.
Human social intelligence relies on our ability to infer other people's mental states such as their beliefs, desires, and intentions. While people are proficient at mental state inference from physical action, it ...
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Human social intelligence relies on our ability to infer other people's mental states such as their beliefs, desires, and intentions. While people are proficient at mental state inference from physical action, it is unknown whether people can make inferences of comparable granularity from simple linguistic events. Here, we show that people can make quantitative mental state attributions from simple referential expressions, replicating the fine-grained inferential structure characteristic of nonlinguistic theory of mind. Moreover, people quantitatively adjust these inferences after brief exposures to speaker-specific speech patterns. These judgments matched the predictions made by our computational model of theory of mind in language, but could not be explained by a simpler qualitative model that attributes mental states deductively. Our findings show how the connection between language and theory of mind runs deep, with their interaction showing in one of the most fundamental forms of human communication: reference.
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