3 papers
cs.LG2023
The Energy Prediction Smart-Meter Dataset: Analysis of Previous Competitions and Beyond
Direnc Pekaslan, Jose Maria Alonso-Moral, Kasun Bandara +17
This paper presents the real-world smart-meter dataset and offers an analysis of solutions derived from the Energy Prediction Technical Challenges, focusing primarily on two key co…
cs.LG2019
L2AE-D: Learning to Aggregate Embeddings for Few-shot Learning with Meta-level Dropout
Heda Song, Mercedes Torres Torres, Ender Özcan +1
Few-shot learning focuses on learning a new visual concept with very limited labelled examples. A successful approach to tackle this problem is to compare the similarity between ex…
cs.LG2018
Graph Node-Feature Convolution for Representation Learning
Li Zhang, Heda Song, Nikolaos Aletras +1
Graph convolutional network (GCN) is an emerging neural network approach. It learns new representation of a node by aggregating feature vectors of all neighbors in the aggregation…