59 citations · 180 across the 28 of their papers we have counts for
6 papers · 1 filter
Disentangled Representation Learning
Xin Wang, Hong Chen, Si'ao Tang +2
Disentangled Representation Learning (DRL) aims to learn a model capable of identifying and disentangling the underlying factors hidden in the observable data in representation for…
NeurIPS'22 Cross-Domain MetaDL competition: Design and baseline results
Dustin Carrión-Ojeda, Hong Chen, Adrian El Baz +6
We present the design and baseline results for a new challenge in the ChaLearn meta-learning series, accepted at NeurIPS'22, focusing on "cross-domain" meta-learning. Meta-learning…
Learning to Solve Travelling Salesman Problem with Hardness-adaptive Curriculum
Zeyang Zhang, Ziwei Zhang, Xin Wang +1
Various neural network models have been proposed to tackle combinatorial optimization problems such as the travelling salesman problem (TSP). Existing learning-based TSP methods ad…
A Closer Look at Debiased Temporal Sentence Grounding in Videos: Dataset, Metric, and Approach
Xiaohan Lan, Yitian Yuan, Xin Wang +4
Temporal Sentence Grounding in Videos (TSGV), which aims to ground a natural language sentence in an untrimmed video, has drawn widespread attention over the past few years. Howeve…
Self-directed Machine Learning
Wenwu Zhu, Xin Wang, Pengtao Xie
Conventional machine learning (ML) relies heavily on manual design from machine learning experts to decide learning tasks, data, models, optimization algorithms, and evaluation met…
Automated Graph Machine Learning: Approaches, Libraries, Benchmarks and Directions
Xin Wang, Ziwei Zhang, Haoyang Li +1
Graph machine learning has been extensively studied in both academic and industry. However, as the literature on graph learning booms with a vast number of emerging methods and tec…