Search Results for author:
Found 12 papers, 4 papers with code
Does Knowledge Graph Really Matter for Recommender Systems?
We consider the scenarios where knowledge in a KG gets completely removed, randomly distorted and decreased, and also where recommendations are for cold-start users.
Context-based Transfer and Efficient Iterative Learning for Unbiased Scene Graph Generation
Thus, we introduce a plug-and-play method named CITrans, which iteratively trains SGG models with progressively enhanced data.
IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate Importance
Among existing Neural Architecture Search methods, DARTS is known for its efficiency and simplicity.
RAH! RecSys-Assistant-Human: A Human-Centered Recommendation Framework with LLM Agents
The rapid evolution of the web has led to an exponential growth in content.
Self-supervised arbitrary scale super-resolution framework for anisotropic MRI
The anisotropic volume's high-resolution (HR) plane is used to build the HR-LR image pairs for model training.
Leveraging policy instruments and financial incentives to reduce embodied carbon in energy retrofits
This research aims to develop policy strategies to reduce embodied carbon emissions in retrofits.
Life cycle costing analysis of deep energy retrofits of a mid-rise building to understand the impact of energy conservation measures
This study employed EnergyPlus to examine the energy performance of 11 energy retrofit measures for a typical multi-unit residential building (MURB) in Metro Vancouver, British Columbia, Canada.
A Differentiable Semantic Metric Approximation in Probabilistic Embedding for Cross-Modal Retrieval
To verify the effectiveness of our approach, extensive experiments are conducted on MS-COCO, CUB Captions, and Flickr30K, which are commonly used in cross-modal retrieval.
Visual Commonsense-aware Representation Network for Video Captioning
Generating consecutive descriptions for videos, i. e., Video Captioning, requires taking full advantage of visual representation along with the generation process.
Disentangled Graph Contrastive Learning for Review-based Recommendation
In review-based recommendation methods, review data is considered as auxiliary information that can improve the quality of learned user/item or interaction representations for the user rating prediction task.
GLAVNet: Global-Local Audio-Visual Cues for Fine-Grained Material Recognition
We demonstrate that local geometry has a greater impact on the sound than the global geometry and offers more cues in material recognition.
Predicting Kidney Transplant Survival using Multiple Feature Representations for HLAs
Kidney transplantation can significantly enhance living standards for people suffering from end-stage renal disease.
