15 citations · 35 across the 6 of their papers we have counts for
7 papers
What Do Sparse Autoencoder Feature Discovery Scores Identify? From Activations to Interventions
Yifeng Guo, Yanran Li, Xiang Chen
Sparse autoencoder (SAE) features are typically discovered from how their activations co-vary with behaviour, yet they are often used through interventions such as steering or abla…
Beyond Importance: Interchange-Sobol Sensitivity Reveals Task-Specific Content Channels in Transformer Components
Yifeng Guo, Jin-Hong Du, Xiang Chen
Mechanistic interpretability methods summarize a transformer component by a single importance score, conflating two distinct roles: a component may matter because it transports tas…
HAR-Ito models and high-dimensional HAR modeling for high-frequency data
Huiling Yuan, Kexin Lu, Yifeng Guo +1
It is an important task to model realized volatilities for high-frequency data in finance and economics and, as arguably the most popular model, the heterogeneous autoregressive (H…
High Dimensional Portfolio Selection with Cardinality Constraints
Jin-Hong Du, Yifeng Guo, Xueqin Wang
The expanding number of assets offers more opportunities for investors but poses new challenges for modern portfolio management (PM). As a central plank of PM, portfolio selection…
Explainable Recommendation Systems by Generalized Additive Models with Manifest and Latent Interactions
Yifeng Guo, Yu Su, Zebin Yang +1
In recent years, the field of recommendation systems has attracted increasing attention to developing predictive models that provide explanations of why an item is recommended to a…
A Machine Learning Framework for Stock Selection
XingYu Fu, JinHong Du, YiFeng Guo +3
This paper demonstrates how to apply machine learning algorithms to distinguish good stocks from the bad stocks. To this end, we construct 244 technical and fundamental features to…
Robust Log-Optimal Strategy with Reinforcement Learning
Yifeng Guo, Xingyu Fu, Yuyan Shi +1
We proposed a new Portfolio Management method termed as Robust Log-Optimal Strategy (RLOS), which ameliorates the General Log-Optimal Strategy (GLOS) by approximating the tradition…