Titlebook: Knowledge Science, Engineering and Management; 16th International C Zhi Jin,Yuncheng Jiang,Wenjun Ma Conference proceedings 2023 The Editor

Abutment

Blood-Clot

Advancing Domain Adaptation of?BERT by?Learning Domain Term SemanticsNatural Language Processing (NLP) tasks. However, these models yield an unsatisfactory results in domain scenarios, particularly in specialized fields like biomedical contexts, where they cannot amass sufficient semantics of domain terms. To tackle this problem, we present a semantic learning method

Macronutrients

Deep Reinforcement Learning for?Group-Aware Robot Navigation in?Crowdspredictable. Previous research has addressed the problem of navigating in dense crowds by modelling the crowd and using a self-attention mechanism to assign different weights to each individual. However, in reality, crowds do not only consist of individuals, but more often appear as groups, so avoid

Congeal

An Enhanced Distributed Algorithm for?Area Skyline Computation Based on?Apache Sparkta grows larger, these computations become slower and more challenging. To address this issue, we propose an efficient algorithm that uses Apache Spark, a platform for distributed processing, to perform area skyline computations faster and more salable. Our algorithm consists of three main phases: c

Assignment

過剩

設(shè)施

PRACM: Predictive Rewards for?Actor-Critic with?Mixing Function in?Multi-Agent Reinforcement Learninnificant progress in tackling cooperative problems with discrete action spaces. Nevertheless, many existing algorithms suffer from significant performance degradation when faced with large numbers of agents or more challenging tasks. Furthermore, some specific scenarios, such as cooperative environm

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CONE

Research on?Remote Sensing Image Classification Based on?Transfer Learning and?Data Augmentation sensing image classification algorithm based on convolutional neural net-work architecture needs a significant amount of annotated datasets, and the creation of these training data is labor-intensive and time-consuming. Therefore, using a small sample dataset and a mix of transfer learning and data

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