A Connection Between Learning to Reject and Bhattacharyya Divergences
Fuente:
arXiv
Saved in:
| Main Author: | Soen, Alexander |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
pyBregMan: A Python library for Bregman Manifolds
by: Nielsen, Frank, et al.
Published: (2024)
by: Nielsen, Frank, et al.
Published: (2024)
Connecting Jensen-Shannon and Kullback-Leibler Divergences: A New Bound for Representation Learning
by: Dorent, Reuben, et al.
Published: (2025)
by: Dorent, Reuben, et al.
Published: (2025)
Robust Semi-supervised Learning via $f$-Divergence and $α$-Rényi Divergence
by: Aminian, Gholamali, et al.
Published: (2024)
by: Aminian, Gholamali, et al.
Published: (2024)
Relaxed Triangle Inequality for Kullback-Leibler Divergence Between Multivariate Gaussian Distributions
by: Xiao, Shiji, et al.
Published: (2026)
by: Xiao, Shiji, et al.
Published: (2026)
Rejection via Learning Density Ratios
by: Soen, Alexander, et al.
Published: (2024)
by: Soen, Alexander, et al.
Published: (2024)
Channel Simulation and Distributed Compression with Ensemble Rejection Sampling
by: Phan, Buu, et al.
Published: (2025)
by: Phan, Buu, et al.
Published: (2025)
Relationship between Hölder Divergence and Functional Density Power Divergence: Intersection and Generalization
by: Kobayashi, Masahiro
Published: (2025)
by: Kobayashi, Masahiro
Published: (2025)
The Representation Jensen-Shannon Divergence
by: Hoyos-Osorio, Jhoan K., et al.
Published: (2023)
by: Hoyos-Osorio, Jhoan K., et al.
Published: (2023)
Cauchy-Schwarz Divergence Information Bottleneck for Regression
by: Yu, Shujian, et al.
Published: (2024)
by: Yu, Shujian, et al.
Published: (2024)
Generalization Bounds for Quantum Learning via Rényi Divergences
by: Warsi, Naqueeb Ahmad, et al.
Published: (2025)
by: Warsi, Naqueeb Ahmad, et al.
Published: (2025)
Implicit Hypothesis Testing and Divergence Preservation in Neural Network Representations
by: Aksoy, Kadircan, et al.
Published: (2026)
by: Aksoy, Kadircan, et al.
Published: (2026)
Equivalence of the Empirical Risk Minimization to Regularization on the Family of f-Divergences
by: Daunas, Francisco, et al.
Published: (2024)
by: Daunas, Francisco, et al.
Published: (2024)
Indexed Minimum Empirical Divergence-Based Algorithms for Linear Bandits
by: Bian, Jie, et al.
Published: (2024)
by: Bian, Jie, et al.
Published: (2024)
Unbiased Estimating Equation on Inverse Divergence and Its Conditions
by: Kobayashi, Masahiro, et al.
Published: (2024)
by: Kobayashi, Masahiro, et al.
Published: (2024)
A Unified Representation of Density-Power-Based Divergences Reducible to M-Estimation
by: Kobayashi, Masahiro
Published: (2025)
by: Kobayashi, Masahiro
Published: (2025)
Bounds on the Excess Minimum Risk via Generalized Information Divergence Measures
by: Omanwar, Ananya, et al.
Published: (2025)
by: Omanwar, Ananya, et al.
Published: (2025)
Transformers Provably Learn Sparse Token Selection While Fully-Connected Nets Cannot
by: Wang, Zixuan, et al.
Published: (2024)
by: Wang, Zixuan, et al.
Published: (2024)
Divergences induced by dual subtractive and divisive normalizations of exponential families and their convex deformations
by: Nielsen, Frank
Published: (2023)
by: Nielsen, Frank
Published: (2023)
Black-Box Detection of LLM-Generated Text Using Generalized Jensen-Shannon Divergence
by: Chen, Shuangyi, et al.
Published: (2025)
by: Chen, Shuangyi, et al.
Published: (2025)
The Conditional Cauchy-Schwarz Divergence with Applications to Time-Series Data and Sequential Decision Making
by: Yu, Shujian, et al.
Published: (2023)
by: Yu, Shujian, et al.
Published: (2023)
Fast Convergence of $Φ$-Divergence Along the Unadjusted Langevin Algorithm and Proximal Sampler
by: Mitra, Siddharth, et al.
Published: (2024)
by: Mitra, Siddharth, et al.
Published: (2024)
Matrix Completion via Nonsmooth Regularization of Fully Connected Neural Networks
by: Faramarzi, Sajad, et al.
Published: (2024)
by: Faramarzi, Sajad, et al.
Published: (2024)
A Neural Network Algorithm for KL Divergence Estimation with Quantitative Error Bounds
by: Foss, Mikil, et al.
Published: (2025)
by: Foss, Mikil, et al.
Published: (2025)
Mutual Information Estimation via $f$-Divergence and Data Derangements
by: Letizia, Nunzio A., et al.
Published: (2023)
by: Letizia, Nunzio A., et al.
Published: (2023)
The Gap Between Principle and Practice of Lossy Image Coding
by: Zhang, Haotian, et al.
Published: (2025)
by: Zhang, Haotian, et al.
Published: (2025)
$f$-Divergence Regularized RLHF: Two Tales of Sampling and Unified Analyses
by: Wu, Di, et al.
Published: (2026)
by: Wu, Di, et al.
Published: (2026)
Unifying Information-Theoretic and Pair-Counting Clustering Similarity
by: Gates, Alexander J.
Published: (2025)
by: Gates, Alexander J.
Published: (2025)
Exponential convergence rate for Iterative Markovian Fitting
by: Sokolov, Kirill, et al.
Published: (2025)
by: Sokolov, Kirill, et al.
Published: (2025)
Bridging Algorithmic Information Theory and Machine Learning: A New Approach to Kernel Learning
by: Hamzi, Boumediene, et al.
Published: (2023)
by: Hamzi, Boumediene, et al.
Published: (2023)
A Generalized Information Bottleneck Theory of Deep Learning
by: Westphal, Charles, et al.
Published: (2025)
by: Westphal, Charles, et al.
Published: (2025)
A Hierarchical Federated Learning Approach for the Internet of Things
by: Azimi-Abarghouyi, Seyed Mohammad, et al.
Published: (2024)
by: Azimi-Abarghouyi, Seyed Mohammad, et al.
Published: (2024)
Decision Making in Changing Environments: Robustness, Query-Based Learning, and Differential Privacy
by: Chen, Fan, et al.
Published: (2025)
by: Chen, Fan, et al.
Published: (2025)
A Unified Probabilistic Framework for Dictionary Learning with Parsimonious Activation
by: Zhao, Zihui, et al.
Published: (2025)
by: Zhao, Zihui, et al.
Published: (2025)
Generalization in Federated Learning: A Conditional Mutual Information Framework
by: Wang, Ziqiao, et al.
Published: (2025)
by: Wang, Ziqiao, et al.
Published: (2025)
On the Minimax Regret of Sequential Probability Assignment via Square-Root Entropy
by: Jia, Zeyu, et al.
Published: (2025)
by: Jia, Zeyu, et al.
Published: (2025)
Learning Capacity: A Measure of the Effective Dimensionality of a Model
by: Chen, Daiwei, et al.
Published: (2023)
by: Chen, Daiwei, et al.
Published: (2023)
A Memory-Based Reinforcement Learning Approach to Integrated Sensing and Communication
by: Nikbakht, Homa, et al.
Published: (2024)
by: Nikbakht, Homa, et al.
Published: (2024)
Learning Regularities from Data using Spiking Functions: A Theory
by: Zhang, Canlin, et al.
Published: (2024)
by: Zhang, Canlin, et al.
Published: (2024)
A Hierarchical Sampling Framework for bounding the Generalization Error of Federated Learning
by: Filatrella, Dario, et al.
Published: (2026)
by: Filatrella, Dario, et al.
Published: (2026)
Personalized Federated Learning for Cellular VR: Online Learning and Dynamic Caching
by: Tharakan, Krishnendu S., et al.
Published: (2025)
by: Tharakan, Krishnendu S., et al.
Published: (2025)
Similar Items
-
pyBregMan: A Python library for Bregman Manifolds
by: Nielsen, Frank, et al.
Published: (2024) -
Connecting Jensen-Shannon and Kullback-Leibler Divergences: A New Bound for Representation Learning
by: Dorent, Reuben, et al.
Published: (2025) -
Robust Semi-supervised Learning via $f$-Divergence and $α$-Rényi Divergence
by: Aminian, Gholamali, et al.
Published: (2024) -
Relaxed Triangle Inequality for Kullback-Leibler Divergence Between Multivariate Gaussian Distributions
by: Xiao, Shiji, et al.
Published: (2026) -
Rejection via Learning Density Ratios
by: Soen, Alexander, et al.
Published: (2024)