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bias-variance trade-off

21 papers

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Co-occurring keywords

bias-variance tradeoff (32) neural network (6616) contextual bandit (381) generalization bound (652) generalization error (285) discount factor (28) markov decision process (790) empirical risk minimization (352) offline reinforcement learning (492) reinforcement learning (4352)

Papers

Balancing Signal and Variance: Adaptive Offline RL Post-Training for VLA Flow Models AAAI 2026
On Shallow Planning Under Partial Observability AAAI 2025
IWBVT: Instance Weighting-based Bias-Variance Trade-off for Crowdsourcing NIPS 2024
Exploring Channel-Aware Typical Features for Out-of-Distribution Detection AAAI 2024
Towards Costless Model Selection in Contextual Bandits: A Bias-Variance Perspective AISTATS 2024
On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation ICML 2023
Multiclass learning with margin: exponential rates with no bias-variance trade-off ICML 2022
Bayesian Active Learning with Fully Bayesian Gaussian Processes NIPS 2022
Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare NIPS 2022
Spectral Bias Outside the Training Set for Deep Networks in the Kernel Regime NIPS 2022
Tractable contextual bandits beyond realizability AISTATS 2021
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks ICML 2020
Extrapolation Towards Imaginary 0-Nearest Neighbour and Its Improved Convergence Rate NIPS 2020
Per-Decision Option Discounting ICML 2019
Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions AAAI 2019
Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping JMLR 2019
Bounding User Contributions: A Bias-Variance Trade-off in Differential Privacy ICML 2019
Control Regularization for Reduced Variance Reinforcement Learning ICML 2019
On the Dimensionality of Word Embedding NIPS 2018
Fast generalization error bound of deep learning from a kernel perspective AISTATS 2018
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging ICML 2017