Query Optimization Properties of Modified VBS
Valuation-Based~System can represent knowledge in different domains including probability theory, Dempster-Shafer theory and possibility theory. More recent studies show that the framework of VBS is also appropriate for representing and solving Bayesian decision problems and optimization problems. In this paper after introducing the valuation based system (VBS) framework, we present Markov-like properties of VBS and a method for resolving queries to VBS.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Multi-Grained Attention Network With Mutual Exclusion for Composed Query-Based Image Retrieval
The Composed Query-Based Image Retrieval (CQBIR) task aims to precisely obtain the preserved and modified parts, based on the multi-grained semantics learned from the composed query. Since the composed query includes a r…
Image RetrievalRetrievalUtilizing Large Language Models in an iterative paradigm with domain feedback for zero-shot molecule optimization
Molecule optimization is a critical task in drug discovery to optimize desired properties of a given molecule. Despite Large Language Models (LLMs) holding the potential to efficiently simulate this task by using natural…
Drug DiscoveryHallucinationMaskSearch: Querying Image Masks at Scale
Machine learning tasks over image databases often generate masks that annotate image content (e.g., saliency maps, segmentation maps, depth maps) and enable a variety of applications (e.g., determine if a model is learni…
Modified Query Expansion Through Generative Adversarial Networks for Information Extraction in E-Commerce
This work addresses an alternative approach for query expansion (QE) using a generative adversarial network (GAN) to enhance the effectiveness of information search in e-commerce. We propose a modified QE conditional GAN…
Generative Adversarial NetworkSemantic SimilaritySemantic Textual SimilarityFrom exponential to finite/fixed-time stability: Applications to optimization
The development of finite/fixed-time stable optimization algorithms typically involves study of specific problem instances. The lack of a unified framework hinders understanding of more sophisticated algorithms, e.g., pr…