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Found 6 papers, 0 papers with code
Unified Uncertainty Estimation for Cognitive Diagnosis Models
Specifically, based on the idea of estimating the posterior distributions of cognitive diagnosis model parameters, we first provide a unified objective function for mini-batch based optimization that can be more efficiently applied to a wide range of models and large datasets.
Distributed Finite-Time Cooperative Localization for Three-Dimensional Sensor Networks
This paper addresses the distributed localization problem for a network of sensors placed in a three-dimensional space, in which sensors are able to perform range measurements, i. e., measure the relative distance between them, and exchange information on a network structure.
A Novel Approach for Auto-Formulation of Optimization Problems
In the Natural Language for Optimization (NL4Opt) NeurIPS 2022 competition, competitors focus on improving the accessibility and usability of optimization solvers, with the aim of subtask 1: recognizing the semantic entities that correspond to the components of the optimization problem; subtask 2: generating formulations for the optimization problem.
Cooperative Guidance Strategy for Active Defense Spacecraft with Imperfect Information via Deep Reinforcement Learning
In this paper, an adaptive cooperative guidance strategy for the active protection of a target spacecraft trying to evade an interceptor was developed.
Imaging the transverse spin density of light via electromagnetically induced transparency
When a light beam is strongly laterally confined, its field vector spins in a plane not perpendicular to the propagation direction, leading to the presence of transverse spin angular momentum, which plays a crucial role in the field of chiral quantum optics.
Optics
FedSiam: Towards Adaptive Federated Semi-Supervised Learning
In this paper, we focus on designing a general framework FedSiam to tackle different scenarios of federated semi-supervised learning, including four settings in the labels-at-client scenario and two setting in the labels-at-server scenario.
