With the advancement of modern technology, especially the increase in network speed, videos are taking more and more important places among media types. With vast potential applications, video recognition has received great attention. However, video recognition is a non-trivial task: a lot of training data are needed for complicated neural networks, but annotated data are […]

Machine learning has been applied in various fields and shown promising results in recent years. Researchers have found that tuning machine learning models in a proper way can vastly boost the model performance with respect to the specific AI task. However, tuning machine learning models at scale, especially finding the right hyperparameter values, can be […]

The goal of the project is to improve upon the methodology behind goal conditioned learning. In this framework, similar to the setup in traditional reinforcement learning, an agent interacts with an environment. However, instead of training the agent to maximize return, the agent is trained to reach a given goal at the end of the […]

In a few words, this is a fintech data analysis project. The idea is, given temporal data of financial nature, to build algorithms that predict its evolution over time. For instance, the data could be certain assets prices, or customer buying history. The objective would be to respectively predict this asset price in a close […]

Layer 6 builds state-of-the-art recommender systems for TD’s online businesses. Collaborative Filtering (CF) is a common recommendation approach that widely adopted by many e-commerce platforms. Modern CF algorithms attempt to exploit latent features to represent users and items, which can lead to the lack of transparency of the recommender systems. In order to build a […]

The pre-trained Bi-directional Encoder Representation from Transformers (BERT) model had proven to be a milestone in the field of Neural Machine Translation, achieving new state-of-the-art performances on many tasks in the field of Natural Language Processing. Despite its success, it has been noticed that there are still a lot of room for improvement, both in […]

Health disparities arise as a result of long-standing societal disadvantage and discrimination. As machine learning models become more popular in the healthcare sector, understanding of current health disparities becomes even more critical. Without careful management of existing biases, the models can inherit and amplify health disparities, leading to highly undesirable clinical outcomes. This project focuses […]

Despite a significant improvement in healthcare systems over the past decades, the rapid growth in the number of patients with multiple chronic diseases – called multimorbidity – stands as a complex challenge to healthcare services that are primarily designed to treat individuals with single conditions. Advances in machine learning as well as in computing power […]