Cover Image

Theoretical Analysis of Submodular Information Measures for Targeted Data Subset Selection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Beck, Nathan, Pham, Truong, Iyer, Rishabh
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Information Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Complement Submodular Information Measures for Balanced and Robust Data Selection
by: Iyer, Rishabh
Published: (2026)

SMA: Submodular Modality Aligner For Data Efficient Multimodal Learning
by: Pham, Truong, et al.
Published: (2026)

STENCIL: Submodular Mutual Information Based Weak Supervision for Cold-Start Active Learning
by: Beck, Nathan, et al.
Published: (2024)

Advancing Deep Active Learning & Data Subset Selection: Unifying Principles with Information-Theory Intuitions
by: Kirsch, Andreas
Published: (2024)

Submodular Information Selection for Hypothesis Testing with Misclassification Penalties
by: Bhargav, Jayanth, et al.
Published: (2024)

Information-Theoretic Measures on Lattices for High-Order Interactions
by: Liu, Zhaolu, et al.
Published: (2024)

An Information-Theoretic Analysis of Temporal GNNs
by: Farzaneh, Amirmohammad
Published: (2024)

An Information-Theoretic Analysis of In-Context Learning
by: Jeon, Hong Jun, et al.
Published: (2024)

On the Generalization for Transfer Learning: An Information-Theoretic Analysis
by: Wu, Xuetong, et al.
Published: (2022)

Information-Theoretic Progress Measures reveal Grokking is an Emergent Phase Transition
by: Clauw, Kenzo, et al.
Published: (2024)

Learning Short Codes for Fading Channels with No or Receiver-Only Channel State Information
by: Pomaje, Rishabh Sharad, et al.
Published: (2024)

Tighter Information-Theoretic Generalization Bounds via a Novel Class of Change of Measure Inequalities
by: Liu, Yanxiao, et al.
Published: (2026)

InfoDPCCA: Information-Theoretic Dynamic Probabilistic Canonical Correlation Analysis
by: Tang, Shiqin, et al.
Published: (2025)

Information-Theoretic State Variable Selection for Reinforcement Learning
by: Westphal, Charles, et al.
Published: (2024)

Information-Theoretic Discrete Diffusion
by: Jeon, Moongyu, et al.
Published: (2025)

On Causality in Domain Adaptation and Semi-Supervised Learning: an Information-Theoretic Analysis for Parametric Models
by: Wu, Xuetong, et al.
Published: (2022)

An Information-Theoretic Criterion for Efficient Data Synthesis
by: Li, Hanyu, et al.
Published: (2026)

An Information Theoretic Perspective on Conformal Prediction
by: Correia, Alvaro H. C., et al.
Published: (2024)

Information-Theoretic Proofs for Diffusion Sampling
by: Reeves, Galen, et al.
Published: (2025)

Information Theoretic Perspective on Representation Learning
by: Pereg, Deborah, et al.
Published: (2026)

Probing the Information Theoretical Roots of Spatial Dependence Measures
by: Wang, Zhangyu, et al.
Published: (2024)

Information-Theoretic Guarantees for Recovering Low-Rank Tensors from Symmetric Rank-One Measurements
by: Kızıldağ, Eren C.
Published: (2025)

Information-Theoretic Multi-Model Fusion for Target-Oriented Adaptive Sampling in Materials Design
by: Zhang, Yixuan, et al.
Published: (2026)

Statistical-Computational Trade-offs in Tensor PCA and Related Problems via Communication Complexity
by: Dudeja, Rishabh, et al.
Published: (2022)

On the Generalization of Knowledge Distillation: An Information-Theoretic View
by: Li, Bingying, et al.
Published: (2026)

Theoretical Guarantees of Data Augmented Last Layer Retraining Methods
by: Welfert, Monica, et al.
Published: (2024)

Directed Information $γ$-covering: An Information-Theoretic Framework for Context Engineering
by: Huang, Hai
Published: (2025)

Uncertainty Quantification and Data Efficiency in AI: An Information-Theoretic Perspective
by: Simeone, Osvaldo, et al.
Published: (2025)

Information-Theoretic Generalization Bounds for Deep Neural Networks
by: He, Haiyun, et al.
Published: (2024)

Optimal Best-Arm Identification under Fixed Confidence with Multiple Optima
by: Truong, Lan V.
Published: (2025)

Information-Theoretic Framework for Understanding Modern Machine-Learning
by: Feder, Meir, et al.
Published: (2025)

Information Theoretic Learning for Diffusion Models with Warm Start
by: Shen, Yirong, et al.
Published: (2025)

Unifying Information-Theoretic and Pair-Counting Clustering Similarity
by: Gates, Alexander J.
Published: (2025)

Information Theoretic Guarantees For Policy Alignment In Large Language Models
by: Mroueh, Youssef
Published: (2024)

Information-Theoretic Thresholds for the Alignments of Partially Correlated Graphs
by: Huang, Dong, et al.
Published: (2024)

Improved Information Theoretic Generalization Bounds for Distributed and Federated Learning
by: Barnes, L. P., et al.
Published: (2022)

Forecastability as an Information-Theoretic Limit on Prediction
by: Catt, Peter Maurice
Published: (2026)

Subset-Based Instance Optimality in Private Estimation
by: Dick, Travis, et al.
Published: (2023)

High-Dimensional Asymptotics of Differentially Private PCA
by: Yun, Youngjoo, et al.
Published: (2025)

Separable Computation of Information Measures
by: Xu, Xiangxiang, et al.
Published: (2025)