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Found 14 papers, 0 papers with code
A unified uncertainty-aware exploration: Combining epistemic and aleatory uncertainty
In this paper, we propose an algorithm that clarifies the theoretical connection between aleatory and epistemic uncertainty, unifies aleatory and epistemic uncertainty estimation, and quantifies the combined effect of both uncertainties for a risk-sensitive exploration.
Uncertainty-aware transfer across tasks using hybrid model-based successor feature reinforcement learning
Putting together two ideas of hybrid model-based successor feature (MB-SF) and uncertainty leads to an approach to the problem of sample efficient uncertainty-aware knowledge transfer across tasks with different transition dynamics or/and reward functions.
ViT-CAT: Parallel Vision Transformers with Cross Attention Fusion for Popularity Prediction in MEC Networks
Followed by a Cross Attention (CA) module as the Fusion Center (FC), the proposed ViT-CAT is capable of learning the mutual information between temporal and spatial correlations, as well, resulting in improving the classification accuracy, and decreasing the model's complexity about 8 times.
Multi-Content Time-Series Popularity Prediction with Multiple-Model Transformers in MEC Networks
Most existing datadriven popularity prediction models, however, are not suitable for the coded/uncoded content placement frameworks.
JUNO: Jump-Start Reinforcement Learning-based Node Selection for UWB Indoor Localization
Performance of UWB-based localization systems, however, can significantly degrade because of Non Line of Sight (NLoS) connections between a mobile user and UWB beacons.
AKF-SR: Adaptive Kalman Filtering-based Successor Representation
Recent studies in neuroscience suggest that Successor Representation (SR)-based models provide adaptation to changes in the goal locations or reward function faster than model-free algorithms, together with lower computational cost compared to that of model-based algorithms.
DQLEL: Deep Q-Learning for Energy-Optimized LoS/NLoS UWB Node Selection
Although UWB technology can enhance the accuracy of indoor positioning due to the use of a wide-frequency spectrum, there are key challenges ahead for its efficient implementation.
On the Philosophical, Cognitive and Mathematical Foundations of Symbiotic Autonomous Systems (SAS)
Symbiotic Autonomous Systems (SAS) are advanced intelligent and cognitive systems exhibiting autonomous collective intelligence enabled by coherent symbiosis of human-machine interactions in hybrid societies.
Assessing Risks of Biases in Cognitive Decision Support Systems
An example of such a system is a cognitive biometric-enabled security checkpoint.
Deep Multimodal Multilinear Fusion with High-order Polynomial Pooling
Tensor-based multimodal fusion techniques have exhibited great predictive performance.
TENSOR RING NETS ADAPTED DEEP MULTI-TASK LEARNING
Recent deep multi-task learning (MTL) has been witnessed its success in alleviating data scarcity of some task by utilizing domain-specific knowledge from related tasks.
Low-Rank Embedding of Kernels in Convolutional Neural Networks under Random Shuffling
We demonstrate this by compressing the convolutional layers via randomly-shuffled tensor decomposition (RsTD) for a standard classification task using CIFAR-10.
Blind Predicting Similar Quality Map for Image Quality Assessment
A key problem in blind image quality assessment (BIQA) is how to effectively model the properties of human visual system in a data-driven manner.
Generative Adversarial Positive-Unlabelled Learning
However, given limited P data, the conventional PU models tend to suffer from overfitting when adapted to very flexible deep neural networks.
