Data Mixture Optimization: A Multi-fidelity Multi-scale Bayesian Framework
Fuente:
arXiv
Saved in:
| Main Authors: | Yen, Thomson, Siah, Andrew Wei Tung, Chen, Haozhe, Peng, Tianyi, Guetta, Daniel, Namkoong, Hongseok |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Benchmarking In-context Experiential Learning Through Repeated Product Recommendations
by: Yang, Gilbert, et al.
Published: (2025)
by: Yang, Gilbert, et al.
Published: (2025)
Architectural and Inferential Inductive Biases For Exchangeable Sequence Modeling
by: Mittal, Daksh, et al.
Published: (2025)
by: Mittal, Daksh, et al.
Published: (2025)
Empirical Likelihood for Nonsmooth Functionals
by: Namkoong, Hongseok
Published: (2026)
by: Namkoong, Hongseok
Published: (2026)
PersonalLLM: Tailoring LLMs to Individual Preferences
by: Zollo, Thomas P., et al.
Published: (2024)
by: Zollo, Thomas P., et al.
Published: (2024)
QGym: Scalable Simulation and Benchmarking of Queuing Network Controllers
by: Chen, Haozhe, et al.
Published: (2024)
by: Chen, Haozhe, et al.
Published: (2024)
Exchangeable Sequence Models Quantify Uncertainty Over Latent Concepts
by: Ye, Naimeng, et al.
Published: (2024)
by: Ye, Naimeng, et al.
Published: (2024)
SynthTools: A Framework for Scaling Synthetic Tools for Agent Development
by: Castellani, Tommaso, et al.
Published: (2025)
by: Castellani, Tommaso, et al.
Published: (2025)
Optimization-Driven Adaptive Experimentation
by: Che, Ethan, et al.
Published: (2024)
by: Che, Ethan, et al.
Published: (2024)
A Planning Framework for Adaptive Labeling
by: Mittal, Daksh, et al.
Published: (2025)
by: Mittal, Daksh, et al.
Published: (2025)
Rethinking Distribution Shifts: Empirical Analysis and Inductive Modeling for Tabular Data
by: Wang, Tianyu, et al.
Published: (2023)
by: Wang, Tianyu, et al.
Published: (2023)
A Broader View of Thompson Sampling
by: Qu, Yanlin, et al.
Published: (2025)
by: Qu, Yanlin, et al.
Published: (2025)
A Sensitivity Approach to Causal Inference Under Limited Overlap
by: Ma, Yuanzhe, et al.
Published: (2025)
by: Ma, Yuanzhe, et al.
Published: (2025)
Active Exploration via Autoregressive Generation of Missing Data
by: Cai, Tiffany Tianhui, et al.
Published: (2024)
by: Cai, Tiffany Tianhui, et al.
Published: (2024)
Data-Driven Stochastic Modeling Using Autoregressive Sequence Models: Translating Event Tables to Queueing Dynamics
by: Mittal, Daksh, et al.
Published: (2025)
by: Mittal, Daksh, et al.
Published: (2025)
Design and Scheduling of an AI-based Queueing System
by: Lee, Jiung, et al.
Published: (2024)
by: Lee, Jiung, et al.
Published: (2024)
Distilled Thompson Sampling: Practical and Efficient Thompson Sampling via Imitation Learning
by: Namkoong, Hongseok, et al.
Published: (2020)
by: Namkoong, Hongseok, et al.
Published: (2020)
LLM Generated Persona is a Promise with a Catch
by: Li, Ang, et al.
Published: (2025)
by: Li, Ang, et al.
Published: (2025)
Contextual Thompson Sampling via Generation of Missing Data
by: Zhang, Kelly W., et al.
Published: (2025)
by: Zhang, Kelly W., et al.
Published: (2025)
On Some Tunable Multi-fidelity Bayesian Optimization Frameworks
by: Manoj, Arjun, et al.
Published: (2025)
by: Manoj, Arjun, et al.
Published: (2025)
Minimax Optimal Estimation of Stability Under Distribution Shift
by: Namkoong, Hongseok, et al.
Published: (2022)
by: Namkoong, Hongseok, et al.
Published: (2022)
AExGym: Benchmarks and Environments for Adaptive Experimentation
by: Wang, Jimmy, et al.
Published: (2024)
by: Wang, Jimmy, et al.
Published: (2024)
Differentiable Discrete Event Simulation for Queuing Network Control
by: Che, Ethan, et al.
Published: (2024)
by: Che, Ethan, et al.
Published: (2024)
DRO: A Python Library for Distributionally Robust Optimization in Machine Learning
by: Liu, Jiashuo, et al.
Published: (2025)
by: Liu, Jiashuo, et al.
Published: (2025)
Multi-fidelity Bayesian Optimization: A Review
by: Do, Bach, et al.
Published: (2023)
by: Do, Bach, et al.
Published: (2023)
C-Learner: Constrained Learning for Causal Inference
by: Cai, Tiffany Tianhui, et al.
Published: (2024)
by: Cai, Tiffany Tianhui, et al.
Published: (2024)
Evaluating Model Performance Under Worst-case Subpopulations
by: Li, Mike, et al.
Published: (2024)
by: Li, Mike, et al.
Published: (2024)
LLM Embeddings Improve Test-time Adaptation to Tabular $Y|X$-Shifts
by: Zeng, Yibo, et al.
Published: (2024)
by: Zeng, Yibo, et al.
Published: (2024)
Adaptive Elicitation of Latent Information Using Natural Language
by: Wang, Jimmy, et al.
Published: (2025)
by: Wang, Jimmy, et al.
Published: (2025)
Multi-fidelity Bayesian Data-Driven Design of Energy Absorbing Spinodoid Cellular Structures
by: Guo, Leo, et al.
Published: (2025)
by: Guo, Leo, et al.
Published: (2025)
LLM Swiss Round: Aggregating Multi-Benchmark Performance via Competitive Swiss-System Dynamics
by: Liu, Jiashuo, et al.
Published: (2025)
by: Liu, Jiashuo, et al.
Published: (2025)
Multi-agent Markov Entanglement
by: Chen, Shuze, et al.
Published: (2025)
by: Chen, Shuze, et al.
Published: (2025)
Graph Laplacian-based Bayesian Multi-fidelity Modeling
by: Pinti, Orazio, et al.
Published: (2024)
by: Pinti, Orazio, et al.
Published: (2024)
Multi-fidelity Machine Learning for Uncertainty Quantification and Optimization
by: Zhang, Ruda, et al.
Published: (2024)
by: Zhang, Ruda, et al.
Published: (2024)
GRAPE: Optimize Data Mixture for Group Robust Multi-target Adaptive Pretraining
by: Fan, Simin, et al.
Published: (2025)
by: Fan, Simin, et al.
Published: (2025)
Balancing Multi-modal Sensor Learning via Multi-objective Optimization
by: Fernando, Heshan, et al.
Published: (2025)
by: Fernando, Heshan, et al.
Published: (2025)
FERERO: A Flexible Framework for Preference-Guided Multi-Objective Learning
by: Chen, Lisha, et al.
Published: (2024)
by: Chen, Lisha, et al.
Published: (2024)
Multi-Objective Causal Bayesian Optimization
by: Bhatija, Shriya, et al.
Published: (2025)
by: Bhatija, Shriya, et al.
Published: (2025)
ARCO-BO: Adaptive Resource-aware COllaborative Bayesian Optimization for Heterogeneous Multi-Agent Design
by: Wang, Zihan, et al.
Published: (2025)
by: Wang, Zihan, et al.
Published: (2025)
Self-supervised Equality Embedded Deep Lagrange Dual for Approximate Constrained Optimization
by: Kim, Minsoo, et al.
Published: (2023)
by: Kim, Minsoo, et al.
Published: (2023)
Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance
by: Chen, Lisha, et al.
Published: (2023)
by: Chen, Lisha, et al.
Published: (2023)
Similar Items
-
Benchmarking In-context Experiential Learning Through Repeated Product Recommendations
by: Yang, Gilbert, et al.
Published: (2025) -
Architectural and Inferential Inductive Biases For Exchangeable Sequence Modeling
by: Mittal, Daksh, et al.
Published: (2025) -
Empirical Likelihood for Nonsmooth Functionals
by: Namkoong, Hongseok
Published: (2026) -
PersonalLLM: Tailoring LLMs to Individual Preferences
by: Zollo, Thomas P., et al.
Published: (2024) -
QGym: Scalable Simulation and Benchmarking of Queuing Network Controllers
by: Chen, Haozhe, et al.
Published: (2024)