A5100653058- Reinforcement Learning in Robotics
- Bayesian Modeling and Causal Inference
- AI-based Problem Solving and Planning
- Multi-Agent Systems and Negotiation
- Artificial Intelligence in Games
- Logic, Reasoning, and Knowledge
- Evolutionary Algorithms and Applications
- Complex Systems and Decision Making
- Data Visualization and Analytics
- Simulation Techniques and Applications
- Robotic Path Planning Algorithms
- Data Mining Algorithms and Applications
- Complex Network Analysis Techniques
- Data Management and Algorithms
- Tensor decomposition and applications
- Opinion Dynamics and Social Influence
- Data Stream Mining Techniques
- Evolutionary Game Theory and Cooperation
- Recommender Systems and Techniques
- Artificial Immune Systems Applications
- Time Series Analysis and Forecasting
- Network Security and Intrusion Detection
- Data Quality and Management
- Human Mobility and Location-Based Analysis
- Face and Expression Recognition
University of California, Los Angeles
2025
Northumbria University
2020-2024
Huazhong University of Science and Technology
2023-2024
Shandong University of Science and Technology
2023
Washington University in St. Louis
2022
Hohai University
2022
Xiamen University
2002-2021
University Ucinf
2021
Dalian University of Technology
2021
Teesside University
2012-2020
Influence maximization is a fundamental research problem in social networks. Viral marketing, one of its applications, to get small number users adopt product, which subsequently triggers large cascade further adoptions by utilizing "Word-of-Mouth" effect has been extensively studied recently. However, none the previous work considers time constraint influence problem. In this paper, we propose constrained We show that NP-hard, and prove monotonicity submodularity spread function. Based on...
Influence maximization is a fundamental research problem in social networks. Viral marketing, one of its applications, to get small number users adopt product, which subsequently triggers large cascade further adoptions by utilizing “Word-of-Mouth” effect Time plays an important role the influence spread from user another and time needed for varies. In this paper, we propose constrained problem. We show that NP-hard, prove monotonicity submodularity function. Based on this, develop greedy...
Point-of-interest(POI) recommendation becomes a valuable service in location-based social networks. Based on the norm that similar users are likely to have preference of POIs, current techniques mainly focus users' provide accurate results. This tends generate list homogeneous POIs clustered into narrow band location categories(like food, museum, etc.) city. However, more interested taste wide range flavors exposed global set categories city.In this paper, we formulate new POI problem,...
Due to the "curse of dimensionality" issue, how discard redundant features and select informative in high-dimensional data has become a critical problem, hence there are many research studies dedicated solving this problem. Unsupervised feature selection technique, which does not require any prior category information conduct with, gained prominent place preprocessing among all techniques, it been applied neural networks learning systems related applications, e.g., pattern classification. In...
The mechanical properties of human lung tissue were measured in a state biaxial tension. experimental data fitted with pseudo-elastic constitutive equation proposed earlier and the physical constants identified.
We focus on the problem of sequential decision making in partially observable environments shared with other agents uncertain types having similar or conflicting objectives. This has been previously formalized by multiple frameworks one which is interactive dynamic influence diagram (I-DID), generalizes well-known to multiagent setting. I-DIDs are graphical models and may be used compute policy an agent given its belief over physical state others' models, changes as acts observes As we...
Influence maximization problem is to find a set of seed nodes in social network such that their influence spread maximized under certain propagation models. A few algorithms have been proposed for solving this problem. However, they not considered the impact novelty decay on propagation, i.e., repeated exposures will diminishing users. In paper, we consider with (IMND). We investigate effect real-life datasets and formulate IMND further analyze properties propose an estimation technique....
Abstract Practice is an essential means by which humans and animals engage in cognitive activities. Intelligent tutoring systems, with a crucial component of modelling learners’ processes during learning optimizing their strategies, offer excellent platform to investigate students’ practice-based processes. In related studies, methods for have demonstrated commendable performance. Furthermore, researchers extended investigations using decision-theoretic approaches, such as partially...
Abstract The gastrointestinal tract remodels its morphology and circumferential stress–strain properties in diabetes mellitus. This study adds one more piece of mechanical knowledge, namely the oesophageal shear modulus dependence on longitudinal stresses strains oesophagus diabetic rats control rats. Diabetes was induced by a single intraperitoneal injection streptozotocin (50 mg kg −1 body weight). lived up to 28 days after induction diabetes. studied vitro using triaxial machine. Stepwise...
Meme automaton is an adaptive entity that autonomously acquires increasing level of capability and intelligence through embedded memes evolving independently or via social interactions. This paper begins a study on memetic multiagent system (MeMAS) toward human-like agents with automaton. We introduce potentially rich meme-inspired design operational model, Darwin's theory natural selection Dawkins' notion meme as the principal driving forces behind interactions among agents, whereby form...
Using Generative Adversarial Networks (GANs) to generate synthetic Electronic Health Records (EHR) has attracted increasing attention. However, in existing approaches, the events EHRs are treated as separate variables which indiscriminately entered into model, without taking account meaning and grouping of them. Besides, efficacy treatment is often neglected. In this paper, we first embed information disease diagnosis, then propose Grouped Correlational GAN (GcGAN) explicitly learn inherent...
Discovering common intentions of multiple agents is one the important ways to detect tendency their collaborative behaviours. Existing work mainly focuses on intention recognition in a single-agent setting and uses descriptive model, e.g. Bayesian networks, process. In this article, we develop new approach identifying for through analysing behaviours over time. We first define prescriptive, behavioural model single agent that represents agent's where are hidden plan execution. introduce...