PRICAI 2022: Trends in Artificial Intelligence: 19th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2022, Shanghai, China, November 10–13, 2022, Proceedings, Part III

ISBN-13: 9783031208676 / Angielski / Miękka / 2022 / 650 str.

Sankalp Khanna; Jian Cao; Quan Bai

Opis

This three-volume set, LNAI 13629, LNAI 13630, and LNAI 13631 constitutes  the thoroughly refereed proceedings of the 19th Pacific Rim Conference on Artificial Intelligence, PRICAI 2022, held in Shangai, China, in November 10–13, 2022.

The 91 full papers and 39 short papers presented in these volumes were carefully reviewed and selected from 432 submissions. PRICAI covers a wide range of topics in the areas of social and economic importance for countries in the Pacific Rim: artificial intelligence, machine learning, natural language processing, knowledge representation and reasoning, planning and scheduling, computer vision, distributed artificial intelligence, search methodologies, etc.

Spis treści

Recommender System.- Mixture of Graph Enhanced Expert Networks for Multi-task Recommendation.- MF-TagRec: Multi-feature fused tag recommendation for GitHub.- Co-contrastive Learning for Multi-behavior Recommendation.- Pattern Matching and Information-aware between Reviews and Ratings for Recommendation.- Cross-view Contrastive Learning for Knowledge-aware Session-based Recommendation.- Reinforcement Learning.- HiSA: Facilitating Efficient Multi-Agent Coordination and Cooperation by Hierarchical Policy with Shared Attention.- DDMA: Discrepancy-Driven Multi-Agent Reinforcement Learning.- PRAG: Periodic Regularized Action Gradient for Efficient Continuous Control.- Identifying Multiple Influential Nodes for Complex Networks based on Multi-Agent Deep Reinforcement Learning.- Online Learning in Iterated Prisoner’s Dilemma to Mimic Human Behavior.- Optimizing Exploration-Exploitation Trade-off in Continuous Action Spaces via Q-ensemble.- Hidden Information General Game Playing With Deep Learning and Search.- Sequential Decision Making with “Sequential Information” in Deep Reinforcement Learning.- Two-Stream Communication-Efficient Federated Pruning Network.- Strong General AI.- Multi-scale Lightweight Neural Network for Real-time Object Detection.- Hyperspectral Image Classification Based On Transformer and Generative Adversarial Network.- Deliberation Selector for Knowledge-grounded Conversation Generation.- Training a Lightweight ViT Network for Image Retrieval.- Vision and Perception.- Segmented–original Image Pairs to Facilitate Feature Extraction in Deep Learning Models.- FusionSeg: Motion Segmentation by Jointly Exploiting Frames and Events.- Weakly-supervised Temporal Action Localization with Multi-head Cross-modal Attention.- CrGAN: Continuous Rendering of Image Style.- DPCN: Dual Path Convolutional Network for Single Image Deraining.- All Up to You: Controllable Video Captioning With a Masked Scene Graph.- A Multi-Head Convolutional Neural Network With Multi-path Attention improves Image Denoising.- Learning Spatial Fusion and Matching for Visual Object Tracking.- Lightweight Wavelet-based Transformer for Image Super-resolution.- Efficient high-resolution human pose estimation.- The Geometry Enhanced Deep Implicit Function based 3D Reconstruction for objects in a real-scene image.- Multi-View Stereo Network with Attention Thin Volume.- 3D Point Cloud Segmentation Leveraging Global 2D-view Features.- Self-Supervised Indoor 360-Degree Depth Estimation via Structural Regularization.- Global Boundary Refinement for Semantic Segmentation via Optimal Transport.- Optimization-based Predictive Approach for On-Demand  Transportation.- Joint Contrast: Skeleton-based Mutual Action Recognition with Contrastive Learning.- Nested Multi-Axis Learning Network for Single Image Super Resolution.- Efficient Scale Divide and Conquer Network for Object Detection.- Video-Based Emotion Recognition in the Wild for Online Education Systems.- Real-world Underwater Image Enhancement via Degradation-aware Dynamic Network.- Self-Supervised Vision Transformer based Nearest Neighbor Classification for Multi-Source Open-Set Domain Adaptation.- Lightweight image dehazing neural network model based on estimating medium transmission map by intensity.- CMNet: Cross-aggregation Multi-branch Network for Salient Object Detection.- More than Accuracy: an Empirical Study of Consistency between Performance and Interpretability.- Object-scale Adaptive Optical Flow Estimation Network.- A Task-aware Dual Similarity Network for Fine-grained Few-shot Learning.- Rotating Target Detection Based On Lightweight Network.- Corner Detection Based on a Dynamic Measure of Cornerity.