prediction error

A Switching Framework for Online Interval Scheduling with Predictions AAAI 2026 Goal-Oriented Time-Series Forecasting: Foundation Framework Design AAAI 2026 Minimum-Cost Network Flow with Dual Predictions AAAI 2026 On efficient robust regression with subquadratic samples COLT 2026 Ordinal Secretaries with Advice AAAI 2026 When Models Hesitate: Answer Instability as a Label-Free Uncertainty Signal for LLMs ACL 2026 Worst-case Error Bounds for Online Learning of Smooth Functions COLT 2026 Approximation algorithms for combinatorial optimization with predictions ICLR 2025 Competitive Fair Scheduling with Predictions ICLR 2025 Improved Bounds for Online Facility Location with Predictions AAAI 2025 Minimal Variance Model Aggregation: A principled, non-intrusive, and versatile integration of black box models ICLR 2025 PEAKS: Selecting Key Training Examples Incrementally via Prediction Error Anchored by Kernel Similarity ICML 2025 Predicting quantum channels over general product distributions COLT 2025 RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models ICML 2025 Algorithms for Caching and MTS with reduced number of predictions ICLR 2024 High-dimensional (Group) Adversarial Training in Linear Regression NeurIPS 2024 Learning-Augmented Algorithms for the Bahncard Problem NeurIPS 2024 Learning-Based Algorithms for Graph Searching Problems AISTATS 2024 Online Classification with Predictions NeurIPS 2024 Parsimonious Learning-Augmented Approximations for Dense Instances of NP-hard Problems ICML 2024 Prediction Error-based Classification for Class-Incremental Learning ICLR 2024 Scale-invariant Optimal Sampling for Rare-events Data and Sparse Models NeurIPS 2024 Statistical Optimality of Divide and Conquer Kernel-based Functional Linear Regression JMLR 2024 Discrete-Smoothness in Online Algorithms with Predictions NeurIPS 2023 Learning-Augmented Algorithms for Online TSP on the Line AAAI 2023