Cover Image

Measuring Stochastic Data Complexity with Boltzmann Influence Functions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ng, Nathan, Grosse, Roger, Ghassemi, Marzyeh
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Improving Mutual Information Estimation with Annealed and Energy-Based Bounds
by: Brekelmans, Rob, et al.
Published: (2023)

MaskMedPaint: Masked Medical Image Inpainting with Diffusion Models for Mitigation of Spurious Correlations
by: Jin, Qixuan, et al.
Published: (2024)

Improving Black-box Robustness with In-Context Rewriting
by: O'Brien, Kyle, et al.
Published: (2024)

Data Debiasing with Datamodels (D3M): Improving Subgroup Robustness via Data Selection
by: Jain, Saachi, et al.
Published: (2024)

An Investigation of Memorization Risk in Healthcare Foundation Models
by: Tonekaboni, Sana, et al.
Published: (2025)

Aggregation Hides Out-of-Distribution Generalization Failures from Spurious Correlations
by: Salaudeen, Olawale, et al.
Published: (2025)

Robustness Beyond Known Groups with Low-rank Adaptation
by: Gourabathina, Abinitha, et al.
Published: (2026)

Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation
by: Hamidieh, Kimia, et al.
Published: (2024)

What's in a Query: Polarity-Aware Distribution-Based Fair Ranking
by: Balagopalan, Aparna, et al.
Published: (2025)

Speak Easy: Eliciting Harmful Jailbreaks from LLMs with Simple Interactions
by: Chan, Yik Siu, et al.
Published: (2025)

In the Name of Fairness: Assessing the Bias in Clinical Record De-identification
by: Xiao, Yuxin, et al.
Published: (2023)

SFTMix: Elevating Language Model Instruction Tuning with Mixup Recipe
by: Xiao, Yuxin, et al.
Published: (2024)

Distributional Training Data Attribution: What do Influence Functions Sample?
by: Mlodozeniec, Bruno, et al.
Published: (2025)

When Style Breaks Safety: Defending LLMs Against Superficial Style Alignment
by: Xiao, Yuxin, et al.
Published: (2025)

Event-Based Contrastive Learning for Medical Time Series
by: Jeong, Hyewon, et al.
Published: (2023)

Reaching Beyond the Mode: RL for Distributional Reasoning in Language Models
by: Puri, Isha, et al.
Published: (2026)

KScope: A Framework for Characterizing the Knowledge Status of Language Models
by: Xiao, Yuxin, et al.
Published: (2025)

LEMoN: Label Error Detection using Multimodal Neighbors
by: Zhang, Haoran, et al.
Published: (2024)

BendVLM: Test-Time Debiasing of Vision-Language Embeddings
by: Gerych, Walter, et al.
Published: (2024)

Training Data Attribution via Approximate Unrolled Differentiation
by: Bae, Juhan, et al.
Published: (2024)

What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions
by: Choe, Sang Keun, et al.
Published: (2024)

Train Long, Think Short: Curriculum Learning for Efficient Reasoning
by: Hammoud, Hasan Abed Al Kader, et al.
Published: (2025)

Evaluation without Generation: Non-Generative Assessment of Harmful Model Specialization with Applications to CSAM
by: Suriyakumar, Vinith M., et al.
Published: (2026)

Asymmetry in Low-Rank Adapters of Foundation Models
by: Zhu, Jiacheng, et al.
Published: (2024)

Generative AI in Medicine
by: Shanmugam, Divya, et al.
Published: (2024)

On the Sample Complexity of Quantum Boltzmann Machine Learning
by: Coopmans, Luuk, et al.
Published: (2023)

Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions
by: Cinà, Antonio Emanuele, et al.
Published: (2021)

Bayesian Influence Functions for Hessian-Free Data Attribution
by: Kreer, Philipp Alexander, et al.
Published: (2025)

A Comprehensive Forecasting-Based Framework for Time Series Anomaly Detection: Benchmarking on the Numenta Anomaly Benchmark (NAB)
by: Karami, Mohammad, et al.
Published: (2025)

On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries
by: Joshi, Nirmit, et al.
Published: (2024)

Revisiting Data Attribution for Influence Functions
by: Zhu, Hongbo, et al.
Published: (2025)

Better Training Data Attribution via Better Inverse Hessian-Vector Products
by: Wang, Andrew, et al.
Published: (2025)

Rescaled Influence Functions: Accurate Data Attribution in High Dimension
by: Rubinstein, Ittai, et al.
Published: (2025)

Distribution-Free Uncertainty Quantification in Mechanical Ventilation Treatment: A Conformal Deep Q-Learning Framework
by: Eghbali, Niloufar, et al.
Published: (2024)

Influence Functions for Efficient Data Selection in Reasoning
by: Humane, Prateek, et al.
Published: (2025)

Application-Driven Innovation in Machine Learning
by: Rolnick, David, et al.
Published: (2024)

BoltzNCE: Learning Likelihoods for Boltzmann Generation with Stochastic Interpolants and Noise Contrastive Estimation
by: Aggarwal, Rishal, et al.
Published: (2025)

Theoretical Analysis of Submodular Information Measures for Targeted Data Subset Selection
by: Beck, Nathan, et al.
Published: (2024)

A Versatile Influence Function for Data Attribution with Non-Decomposable Loss
by: Deng, Junwei, et al.
Published: (2024)

TimeInf: Time Series Data Contribution via Influence Functions
by: Zhang, Yizi, et al.
Published: (2024)