4 papers
Environment-Conditioned Tail Reweighting for Invariant Learning under Mixed Shifts
Yuanchao Wang, Zhao-Rong Lai, Tianqi Zhong +1
Out-of-distribution generalization becomes challenging when spurious correlations vary across environments while difficult or underrepresented samples remain insufficiently emphasi…
Linear Trading Position with Sparse Spectrum
Zhao-Rong Lai, Haisheng Yang
The principal portfolio approach is an emerging method in signal-based trading. However, these principal portfolios may not be diversified to explore the key features of the predic…
Out-of-distribution Generalization for Total Variation based Invariant Risk Minimization
Yuanchao Wang, Zhao-Rong Lai, Tianqi Zhong
Invariant risk minimization is an important general machine learning framework that has recently been interpreted as a total variation model (IRM-TV). However, how to improve out-o…
Invariant Risk Minimization Is A Total Variation Model
Zhao-Rong Lai, Weiwen Wang
Invariant risk minimization (IRM) is an arising approach to generalize invariant features to different environments in machine learning. While most related works focus on new IRM s…