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Convolutional Neural Networks Quantization with Double-Stage Squeeze-and-Threshold.

International journal of neural systems
It has been proven that, compared to using 32-bit floating-point numbers in the training phase, Deep Convolutional Neural Networks (DCNNs) can operate with low-precision during inference, thereby saving memory footprint and power consumption. However...

General object-based features account for letter perception.

PLoS computational biology
After years of experience, humans become experts at perceiving letters. Is this visual capacity attained by learning specialized letter features, or by reusing general visual features previously learned in service of object categorization? To explore...

A path planning approach for mobile robots using short and safe Q-learning.

PloS one
Path planning is a major challenging problem for mobile robots, as the robot is required to reach the target position from the starting position while simultaneously avoiding conflicts with obstacles. This paper refers to a novel method as short and ...

Time series (re)sampling using Generative Adversarial Networks.

Neural networks : the official journal of the International Neural Network Society
We propose a novel bootstrap procedure for time series data based on Generative Adversarial networks (GANs). We show that the dynamics of common stationary time series processes can be learned by GANs and demonstrate that GANs trained on a single sam...

Not all edges are peers: Accurate structure-aware graph pooling networks.

Neural networks : the official journal of the International Neural Network Society
Graph Neural Networks (GNNs) have achieved state-of-the-art performance in graph-related tasks. For graph classification task, an elaborated pooling operator is vital for learning graph-level representations. Most pooling operators derived from exist...

Self-supervised graph neural network with pre-training generative learning for recommendation systems.

Scientific reports
The case assignment system is an essential system of case management and assignment within the procuratorate and is an important aspect of judicial fairness and efficiency. However, existing methods mostly use manual or random case assignment, which ...

Interaction with a reactive partner improves learning in contrast to passive guidance.

Scientific reports
Many tasks such as physical rehabilitation, vehicle co-piloting or surgical training, rely on physical assistance from a partner. While this assistance may be provided by a robotic interface, how to implement the necessary haptic support to help impr...

Digital Media Teaching and Effectiveness Evaluation Integrating Big Data and Artificial Intelligence.

Computational intelligence and neuroscience
With the development of digital media technology, its application in teaching and learning is becoming more widespread. Digital media technology helps present information in transmitting knowledge or skills, reduces cognitive load, and promotes under...

TaskDrop: A competitive baseline for continual learning of sentiment classification.

Neural networks : the official journal of the International Neural Network Society
In this paper, we study the multi-task sentiment classification problem in the continual learning setting, i.e., a model is sequentially trained to classify the sentiment of reviews of products in a particular category. The use of common sentiment wo...

A Graph-Neural-Network-Based Social Network Recommendation Algorithm Using High-Order Neighbor Information.

Sensors (Basel, Switzerland)
Social-network-based recommendation algorithms leverage rich social network information to alleviate the problem of data sparsity and boost the recommendation performance. However, traditional social-network-based recommendation algorithms ignore hig...