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bias-variance tradeoff

32 papers

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Co-occurring keywords

bias-variance trade-off (21) generalization error (285) neural network (6616) model averaging (62) ensemble learning (1274) stochastic optimization (1060) bias variance tradeoff (25) k-nearest neighbor (152) least squares regression (49) knowledge distillation (3725)

Papers

Scaling Up Temporal Domain Generalization via Temporal Experts Averaging EMNLP 2025
Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests JMLR 2025
Towards Costless Model Selection in Contextual Bandits: A Bias-Variance Perspective AISTATS 2024
Least Squares Regression Can Exhibit Under-Parameterized Double Descent NIPS 2024
Why Do We Need Weight Decay in Modern Deep Learning? NIPS 2024
IWBVT: Instance Weighting-based Bias-Variance Trade-off for Crowdsourcing NIPS 2024
Fine-Grained Dynamic Framework for Bias-Variance Joint Optimization on Data Missing Not at Random NIPS 2024
Instance-Specific Asymmetric Sensitivity in Differential Privacy NIPS 2024
On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation ICML 2023
Cold Analysis of Rao-Blackwellized Straight-Through Gumbel-Softmax Gradient Estimator ICML 2023
Soft Target-Enhanced Matching Framework for Deep Entity Matching AAAI 2023
Causal Classification: Treatment Effect Estimation vs. Outcome Prediction JMLR 2022
Adaptive Importance Sampling meets Mirror Descent : a Bias-variance Tradeoff AISTATS 2022
Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalization NIPS 2022
Expected Validation Performance and Estimation of a Random Variable’s Maximum EMNLP 2021
Nested Mixture of Experts: Cooperative and Competitive Learning of Hybrid Dynamical System L4DC 2021
Bias and variance of the Bayesian-mean decoder NIPS 2021
What Causes the Test Error? Going Beyond Bias-Variance via ANOVA JMLR 2021
On the Bias-Variance-Cost Tradeoff of Stochastic Optimization NIPS 2021
A statistical perspective on distillation ICML 2021
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks ICML 2020
Transferable Calibration with Lower Bias and Variance in Domain Adaptation NIPS 2020
Extrapolation Towards Imaginary 0-Nearest Neighbour and Its Improved Convergence Rate NIPS 2020
Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions AAAI 2019
Generalization-Aware Structured Regression towards Balancing Bias and Variance IJCAI 2018