9 citations · 21 across the 10 of their papers we have counts for
9 papers · 1 filter
Predictive Inference With Fast Feature Conformal Prediction
Zihao Tang, Boyuan Wang, Chuan Wen +1
Conformal prediction is widely adopted in uncertainty quantification, due to its post-hoc, distribution-free, and model-agnostic properties. In the realm of modern deep learning, r…
Lower Generalization Bounds for GD and SGD in Smooth Stochastic Convex Optimization
Peiyuan Zhang, Jiaye Teng, Jingzhao Zhang
This work studies the generalization error of gradient methods. More specifically, we focus on how training steps and step-size might affect generalization in smooth stocha…
Predictive Inference with Feature Conformal Prediction
Jiaye Teng, Chuan Wen, Dinghuai Zhang +3
Conformal prediction is a distribution-free technique for establishing valid prediction intervals. Although conventionally people conduct conformal prediction in the output space,…
Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming
Chuan Wen, Jianing Qian, Jierui Lin +3
Across applications spanning supervised classification and sequential control, deep learning has been reported to find "shortcut" solutions that fail catastrophically under minor c…
Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models
Kaiyue Wen, Jiaye Teng, Jingzhao Zhang
Studies on benign overfitting provide insights for the success of overparameterized deep learning models. In this work, we examine whether overfitting is truly benign in real-world…
Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression
Jing Xu, Jiaye Teng, Yang Yuan +1
One of the major open problems in machine learning is to characterize generalization in the overparameterized regime, where most traditional generalization bounds become inconsiste…