activity
20202023
most citedA Data Science Pipeline for Algorithmic Trading: A Comparative Study of Applications for Finance and Cryptoeconomics

29 citations · 50 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2023★ 1 cited

SynGen: A Syntactic Plug-and-play Module for Generative Aspect-based Sentiment Analysis

Chengze Yu, Taiqiang Wu, Jiayi Li +2

Aspect-based Sentiment Analysis (ABSA) is a sentiment analysis task at fine-grained level. Recently, generative frameworks have attracted increasing attention in ABSA due to their…

cs.HC2022★ 29 cited

A Data Science Pipeline for Algorithmic Trading: A Comparative Study of Applications for Finance and Cryptoeconomics

Luyao Zhang, Tianyu Wu, Saad Lahrichi +2

Recent advances in Artificial Intelligence (AI) have made algorithmic trading play a central role in finance. However, current research and applications are disconnected informatio…

cs.IR2022★ 19 cited

What are People Talking about in #BlackLivesMatter and #StopAsianHate? Exploring and Categorizing Twitter Topics Emerging in Online Social Movements through the Latent Dirichlet Allocation Model

Xin Tong, Yixuan Li, Jiayi Li +2

Minority groups have been using social media to organize social movements that create profound social impacts. Black Lives Matter (BLM) and Stop Asian Hate (SAH) are two successful…

cs.LG2021

Trajectory Prediction using Generative Adversarial Network in Multi-Class Scenarios

Shilun Li, Tracy Cai, Jiayi Li

Predicting traffic agents' trajectories is an important task for auto-piloting. Most previous work on trajectory prediction only considers a single class of road agents. We use a s…

eess.SY2021★ 1 cited

Decentralized Safe Reinforcement Learning for Voltage Control

Wenqi Cui, Jiayi Li, Baosen Zhang

Inverter-based distributed energy resources provide the possibility for fast time-scale voltage control by quickly adjusting their reactive power. The power-electronic interfaces a…

cs.NE2020

Geometric algorithms for predicting resilience and recovering damage in neural networks

Guruprasad Raghavan, Jiayi Li, Matt Thomson

Biological neural networks have evolved to maintain performance despite significant circuit damage. To survive damage, biological network architectures have both intrinsic resilien…