277 citations · 1.7k across the 70 of their papers we have counts for
8 papers · 1 filter
Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach
Yu Zheng, Bowei Chen, Timothy M. Hospedales +1
Partial (replication) index tracking is a popular passive investment strategy. It aims to replicate the performance of a given index by constructing a tracking portfolio which cont…
Deep clustering with concrete k-means
Boyan Gao, Yongxin Yang, Henry Gouk +1
We address the problem of simultaneously learning a k-means clustering and deep feature representation from unlabelled data, which is of interest due to the potential of deep k-mea…
Learning Generalisable Omni-Scale Representations for Person Re-Identification
Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro +1
An effective person re-identification (re-ID) model should learn feature representations that are both discriminative, for distinguishing similar-looking people, and generalisable,…
Goal-Driven Sequential Data Abstraction
Umar Riaz Muhammad, Yongxin Yang, Timothy M. Hospedales +2
Automatic data abstraction is an important capability for both benchmarking machine intelligence and supporting summarization applications. In the former one asks whether a machine…
Omni-Scale Feature Learning for Person Re-Identification
Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro +1
As an instance-level recognition problem, person re-identification (ReID) relies on discriminative features, which not only capture different spatial scales but also encapsulate an…
Incorporating prior financial domain knowledge into neural networks for implied volatility surface prediction
Yu Zheng, Yongxin Yang, Bowei Chen
In this paper we develop a novel neural network model for predicting implied volatility surface. Prior financial domain knowledge is taken into account. A new activation function t…
Episodic Training for Domain Generalization
Da Li, Jianshu Zhang, Yongxin Yang +3
Domain generalization (DG) is the challenging and topical problem of learning models that generalize to novel testing domains with different statistics than a set of known training…
Feature-Critic Networks for Heterogeneous Domain Generalization
Yiying Li, Yongxin Yang, Wei Zhou +1
The well known domain shift issue causes model performance to degrade when deployed to a new target domain with different statistics to training. Domain adaptation techniques allev…