Jiaye Teng

According to our database, Jiaye Teng authored at least 16 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2023

High-resolution probabilistic load forecasting: A learning ensemble approach.

Chenbei Lu, Jinhao Liang, Wenqian Jiang, Jiaye Teng, Chenye Wu

J. Frankl. Inst., 2023

Lower Generalization Bounds for GD and SGD in Smooth Stochastic Convex Optimization.

Peiyuan Zhang, Jiaye Teng, Jingzhao Zhang

CoRR, 2023

Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression.

Jing Xu, Jiaye Teng, Yang Yuan, Andrew C. Yao

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Finding Generalization Measures by Contrasting Signal and Noise.

Jiaye Teng, Bohang Zhang, Ruichen Li, Haowei He, Yequan Wang, Yan Tian, Yang Yuan

Proceedings of the International Conference on Machine Learning, 2023

On Uni-Modal Feature Learning in Supervised Multi-Modal Learning.

Chenzhuang Du, Jiaye Teng, Tingle Li, Yichen Liu, Tianyuan Yuan, Yue Wang, Yang Yuan, Hang Zhao

Proceedings of the International Conference on Machine Learning, 2023

Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models.

Kaiyue Wen, Jiaye Teng, Jingzhao Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Predictive Inference with Feature Conformal Prediction.

Jiaye Teng, Chuan Wen, Dinghuai Zhang, Yoshua Bengio, Yang Gao, Yang Yuan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Anomaly Detection with Test Time Augmentation and Consistency Evaluation.

Haowei He, Jiaye Teng, Yang Yuan

CoRR, 2022

Realistic Deep Learning May Not Fit Benignly.

Kaiyue Wen, Jiaye Teng, Jingzhao Zhang

CoRR, 2022

Relaxing the Feature Covariance Assumption: Time-Variant Bounds for Benign Overfitting in Linear Regression.

Jing Xu, Jiaye Teng, Andrew Chi-Chih Yao

CoRR, 2022

Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming.

Chuan Wen, Jianing Qian, Jierui Lin, Jiaye Teng, Dinesh Jayaraman, Yang Gao

Proceedings of the International Conference on Machine Learning, 2022

Towards Understanding Generalization via Decomposing Excess Risk Dynamics.

Jiaye Teng, Jianhao Ma, Yang Yuan

Proceedings of the Tenth International Conference on Learning Representations, 2022

Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis.

Jiaye Teng, Weiran Huang, Haowei He

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis.

Jiaye Teng, Weiran Huang

CoRR, 2021

T-SCI: A Two-Stage Conformal Inference Algorithm with Guaranteed Coverage for Cox-MLP.

Jiaye Teng, Zeren Tan, Yang Yuan

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Inject Machine Learning into Significance Test for Misspecified Linear Models.

Jiaye Teng, Yang Yuan

CoRR, 2020