6 citations · 18 across the 12 of their papers we have counts for
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cs.LG2023
Dynamic Ensemble of Low-fidelity Experts: Mitigating NAS "Cold-Start"
Junbo Zhao, Xuefei Ning, Enshu Liu +7
Predictor-based Neural Architecture Search (NAS) employs an architecture performance predictor to improve the sample efficiency. However, predictor-based NAS suffers from the sever…
cs.LG2023
Filtering Context Mitigates Scarcity and Selection Bias in Political Ideology Prediction
Chen Chen, Dylan Walker, Venkatesh Saligrama
We propose a novel supervised learning approach for political ideology prediction (PIP) that is capable of predicting out-of-distribution inputs. This problem is motivated by the f…
cs.LG2023★ 4 cited
Plan To Predict: Learning an Uncertainty-Foreseeing Model for Model-Based Reinforcement Learning
Zifan Wu, Chao Yu, Chen Chen +2
In Model-based Reinforcement Learning (MBRL), model learning is critical since an inaccurate model can bias policy learning via generating misleading samples. However, learning an…