尽忠
发表于 2025-3-30 08:12:38
http://reply.papertrans.cn/63/6206/620546/620546_51.png
Resign
发表于 2025-3-30 13:54:52
Real-Part Quantum Support Vector Machinesmental discipline. Within quantum computing, quantum machine learning is becoming more and more popular. However, subtle differences between classical and quantum machine learning methods sometimes lead to incompatible formalizations of otherwise well aligned methods. Inspired by this observation, w
确定
发表于 2025-3-30 19:15:21
http://reply.papertrans.cn/63/6206/620546/620546_53.png
gratify
发表于 2025-3-30 22:16:00
Enhancing Shortest-Path Graph Kernels via Graph Augmentationt compare graphs with variable scales of the graph structure well and cannot compare attributed graphs whose vertices have continuous attributes. To overcome these two challenges, we propose to enhance SP via graph augmentation: Variable scales of the graph structure around vertices are extracted to
思想上升
发表于 2025-3-31 03:16:59
Hyperbolic Contrastive Learning with Model-Augmentation for Knowledge-Aware Recommendationnowledge-aware recommendation. However, most existing contrastive learning-based methods have difficulties in effectively capturing the underlying hierarchical structure within user-item bipartite graphs and knowledge graphs. Moreover, they commonly generate positive samples for contrastive learning
octogenarian
发表于 2025-3-31 08:09:40
http://reply.papertrans.cn/63/6206/620546/620546_56.png
Palate
发表于 2025-3-31 11:14:26
Adaptive Knowledge Distillation for Classification of Hand Images Using Explainable Vision Transformnct characteristics, such as the pattern of veins, fingerprints, and the geometry of the hand itself. This paper investigates the use of vision transformers (ViTs) for classification of hand images. We use explainability tools to explore the internal representations of ViTs and assess their impact o
食物
发表于 2025-3-31 13:34:45
http://reply.papertrans.cn/63/6206/620546/620546_58.png
全能
发表于 2025-3-31 20:57:38
Lifelong Hierarchical Topic Modeling via Nonparametric Word Embedding Clusteringwever, the existing methods often assume a fixed topic hierarchy, leading to poor performance when applied to document streams. Meanwhile, the prior knowledge of topic structure is helpful for hierarchical topic modeling but it is quite costly to obtain such information manually. To address these is
Outshine
发表于 2025-4-1 00:59:00
High-Dimensional Bayesian Optimization via Random Projection of Manifold Subspacesay decrease exponentially as the dimensionality increases. A common framework to tackle this problem is to assume that the objective function depends on a limited set of features that lie on a low-dimensional manifold embedded in the high-dimensional ambient space. The latent space can be linear or