In-Context Learning as Nonparametric Conditional Probability Estimation: Risk Bounds and Optimality
Fuente:
arXiv
Saved in:
| Main Authors: | Liu, Chenrui, Tan, Falong, Xie, Chuanlong, Zeng, Yicheng, Zhu, Lixing |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Enhancing Out-of-Distribution Detection with Multitesting-based Layer-wise Feature Fusion
by: Li, Jiawei, et al.
Published: (2024)
by: Li, Jiawei, et al.
Published: (2024)
DSDE: Using Proportion Estimation to Improve Model Selection for Out-of-Distribution Detection
by: Geng, Jingyao, et al.
Published: (2024)
by: Geng, Jingyao, et al.
Published: (2024)
Empirical Likelihood-Based Fairness Auditing: Distribution-Free Certification and Flagging
by: Tang, Jie, et al.
Published: (2026)
by: Tang, Jie, et al.
Published: (2026)
Transformers are Minimax Optimal Nonparametric In-Context Learners
by: Kim, Juno, et al.
Published: (2024)
by: Kim, Juno, et al.
Published: (2024)
Enhancing Hierarchical Reinforcement Learning through Change Point Detection in Time Series
by: Arumugam, Hemanath, et al.
Published: (2025)
by: Arumugam, Hemanath, et al.
Published: (2025)
High Probability Bound for Cross-Learning Contextual Bandits with Unknown Context Distributions
by: Huang, Ruiyuan, et al.
Published: (2024)
by: Huang, Ruiyuan, et al.
Published: (2024)
Local Learning for Covariate Selection in Nonparametric Causal Effect Estimation with Latent Variables
by: Li, Zheng, et al.
Published: (2024)
by: Li, Zheng, et al.
Published: (2024)
Density Ratio Estimation with Conditional Probability Paths
by: Yu, Hanlin, et al.
Published: (2025)
by: Yu, Hanlin, et al.
Published: (2025)
Transforming Conditional Density Estimation Into a Single Nonparametric Regression Task
by: Reisach, Alexander G., et al.
Published: (2025)
by: Reisach, Alexander G., et al.
Published: (2025)
Weighted residual empirical processes, martingale transformations, and model specification tests for regressions with diverging number of parameters
by: Tan, Falong, et al.
Published: (2022)
by: Tan, Falong, et al.
Published: (2022)
Asymptotic Distribution-Free Tests for Ultra-high Dimensional Parametric Regressions via Projected Empirical Processes and $p$-value Combination
by: Tan, Falong, et al.
Published: (2026)
by: Tan, Falong, et al.
Published: (2026)
Sample Complexity Bounds for Estimating Probability Divergences under Invariances
by: Tahmasebi, Behrooz, et al.
Published: (2023)
by: Tahmasebi, Behrooz, et al.
Published: (2023)
Sparse Learning and Class Probability Estimation with Weighted Support Vector Machines
by: Zeng, Liyun, et al.
Published: (2023)
by: Zeng, Liyun, et al.
Published: (2023)
Generative and Nonparametric Approaches for Conditional Distribution Estimation: Methods, Perspectives, and Comparative Evaluations
by: Chin, Yen-Shiu, et al.
Published: (2026)
by: Chin, Yen-Shiu, et al.
Published: (2026)
General Lower Bounds for Differentially Private Federated Learning with Arbitrary Public-Transcript Interactions
by: Li, Yicheng
Published: (2026)
by: Li, Yicheng
Published: (2026)
Finding Probably Approximate Optimal Solutions by Training to Estimate the Optimal Values of Subproblems
by: Megiddo, Nimrod, et al.
Published: (2025)
by: Megiddo, Nimrod, et al.
Published: (2025)
Nonparametric Instrumental Regression via Kernel Methods is Minimax Optimal
by: Meunier, Dimitri, et al.
Published: (2024)
by: Meunier, Dimitri, et al.
Published: (2024)
Optimal Rates of Kernel Ridge Regression under Source Condition in Large Dimensions
by: Zhang, Haobo, et al.
Published: (2024)
by: Zhang, Haobo, et al.
Published: (2024)
A Generalizable Physics-informed Learning Framework for Risk Probability Estimation
by: Wang, Zhuoyuan, et al.
Published: (2023)
by: Wang, Zhuoyuan, et al.
Published: (2023)
PeerGuard: Defending Multi-Agent Systems Against Backdoor Attacks Through Mutual Reasoning
by: Fan, Falong, et al.
Published: (2025)
by: Fan, Falong, et al.
Published: (2025)
Accelerated Gradient Methods with Biased Gradient Estimates: Risk Sensitivity, High-Probability Guarantees, and Large Deviation Bounds
by: Gürbüzbalaban, Mert, et al.
Published: (2025)
by: Gürbüzbalaban, Mert, et al.
Published: (2025)
From Weighting to Modeling: A Nonparametric Estimator for Off-Policy Evaluation
by: Zhu, Rong J. B.
Published: (2026)
by: Zhu, Rong J. B.
Published: (2026)
Provable Contrastive Continual Learning
by: Wen, Yichen, et al.
Published: (2024)
by: Wen, Yichen, et al.
Published: (2024)
Kernelized Advantage Estimation: From Nonparametric Statistics to LLM Reasoning
by: Gong, Shijin, et al.
Published: (2026)
by: Gong, Shijin, et al.
Published: (2026)
Learning Optimal Individualized Decision Rules with Conditional Demographic Parity
by: Cui, Wenhai, et al.
Published: (2026)
by: Cui, Wenhai, et al.
Published: (2026)
Towards Sharper Risk Bounds for Minimax Problems
by: Zhu, Bowei, et al.
Published: (2024)
by: Zhu, Bowei, et al.
Published: (2024)
TeamTR: Trust-Region Fine-Tuning for Multi-Agent LLM Coordination
by: Xie, Yi, et al.
Published: (2026)
by: Xie, Yi, et al.
Published: (2026)
CALYREX: Cross-Attention LaYeR EXtended Transformers for System Prompt Anchoring
by: Lixing, Li
Published: (2026)
by: Lixing, Li
Published: (2026)
A Two-Step Projection-Based Goodness-of-Fit Test for Ultra-High Dimensional Sparse Regressions
by: Tan, Falong, et al.
Published: (2024)
by: Tan, Falong, et al.
Published: (2024)
Optimal Demixing of Nonparametric Densities
by: Fan, Jianqing, et al.
Published: (2026)
by: Fan, Jianqing, et al.
Published: (2026)
Always Tell Me The Odds: Fine-grained Conditional Probability Estimation
by: Wang, Liaoyaqi, et al.
Published: (2025)
by: Wang, Liaoyaqi, et al.
Published: (2025)
Active Learning with Neural Networks: Insights from Nonparametric Statistics
by: Zhu, Yinglun, et al.
Published: (2022)
by: Zhu, Yinglun, et al.
Published: (2022)
Concentration Bounds for Optimized Certainty Equivalent Risk Estimation
by: Ghosh, Ayon, et al.
Published: (2024)
by: Ghosh, Ayon, et al.
Published: (2024)
Reweighting Improves Conditional Risk Bounds
by: Zhang, Yikai, et al.
Published: (2025)
by: Zhang, Yikai, et al.
Published: (2025)
Model-Robust and Adaptive-Optimal Transfer Learning for Tackling Concept Shifts in Nonparametric Regression
by: Lin, Haotian, et al.
Published: (2025)
by: Lin, Haotian, et al.
Published: (2025)
Online Prediction of Stochastic Sequences with High Probability Regret Bounds
by: Frey, Matthias, et al.
Published: (2026)
by: Frey, Matthias, et al.
Published: (2026)
Online Bandits with (Biased) Offline Data: Adaptive Learning under Distribution Mismatch
by: Cheung, Wang Chi, et al.
Published: (2024)
by: Cheung, Wang Chi, et al.
Published: (2024)
High-Probability Bounds for SGD under the Polyak-Lojasiewicz Condition with Markovian Noise
by: Kar, Avik, et al.
Published: (2026)
by: Kar, Avik, et al.
Published: (2026)
Learning Monotonic Probabilities with a Generative Cost Model
by: Tang, Yongxiang, et al.
Published: (2025)
by: Tang, Yongxiang, et al.
Published: (2025)
Causal Representation Learning from General Environments under Nonparametric Mixing
by: Ng, Ignavier, et al.
Published: (2026)
by: Ng, Ignavier, et al.
Published: (2026)
Similar Items
-
Enhancing Out-of-Distribution Detection with Multitesting-based Layer-wise Feature Fusion
by: Li, Jiawei, et al.
Published: (2024) -
DSDE: Using Proportion Estimation to Improve Model Selection for Out-of-Distribution Detection
by: Geng, Jingyao, et al.
Published: (2024) -
Empirical Likelihood-Based Fairness Auditing: Distribution-Free Certification and Flagging
by: Tang, Jie, et al.
Published: (2026) -
Transformers are Minimax Optimal Nonparametric In-Context Learners
by: Kim, Juno, et al.
Published: (2024) -
Enhancing Hierarchical Reinforcement Learning through Change Point Detection in Time Series
by: Arumugam, Hemanath, et al.
Published: (2025)