:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Li, Weizhi, Klein, Natalie, Gifford, Brendan, Sklute, Elizabeth, Legett, Carey, Clegg, Samuel
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2502.03755
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Effect of Particle Size on Raman Signal Strength of Silicate Minerals
by: Laura B. Breitenfeld, et al.
Published: (2024)

Regularized $f$-Divergence Kernel Tests
by: Ribero, Mónica, et al.
Published: (2026)

Empirical Risk Minimization with $f$-Divergence Regularization
by: Daunas, Francisco, 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)

A Dual Optimization View to Empirical Risk Minimization with f-Divergence Regularization
by: Daunas, Francisco, et al.
Published: (2025)

Optimal Transport Regularized Divergences: Application to Adversarial Robustness
by: Birrell, Jeremiah, et al.
Published: (2023)

Robust Offline Reinforcement Learning with Linearly Structured f-Divergence Regularization
by: Tang, Cheng, et al.
Published: (2024)

Towards a Sharp Analysis of Offline Policy Learning for $f$-Divergence-Regularized Contextual Bandits
by: Zhao, Qingyue, et al.
Published: (2025)

Meta-learning to Address Data Shift in Time Series Classification
by: Myren, Samuel, et al.
Published: (2026)

$f$-Divergence Regularized RLHF: Two Tales of Sampling and Unified Analyses
by: Wu, Di, et al.
Published: (2026)

Robust Semi-supervised Learning via $f$-Divergence and $α$-Rényi Divergence
by: Aminian, Gholamali, et al.
Published: (2024)

Generalization Error of $f$-Divergence Stabilized Algorithms via Duality
by: Daunas, Francisco, et al.
Published: (2025)

On Weak-to-Strong Generalization and f-Divergence
by: Yao, Wei, et al.
Published: (2025)

Synthesis and Analysis of Data as Probability Measures with Entropy-Regularized Optimal Transport
by: Mallery, Brendan, et al.
Published: (2025)

The Sensitivity of Variational Bayesian Neural Network Performance to Hyperparameters
by: Koermer, Scott, et al.
Published: (2025)

Intransitive Player Dominance and Market Inefficiency in Tennis Forecasting: A Graph Neural Network Approach
by: Clegg, Lawrence, et al.
Published: (2025)

Loss Functions and Operators Generated by f-Divergences
by: Roulet, Vincent, et al.
Published: (2025)

Minimizing $f$-Divergences by Interpolating Velocity Fields
by: Liu, Song, et al.
Published: (2023)

Partition Function Estimation under Bounded f-Divergence
by: Block, Adam, et al.
Published: (2026)

Displacement-Resistant Extensions of DPO with Nonconvex $f$-Divergences
by: Pipano, Idan, et al.
Published: (2026)

Mutual Information Estimation via $f$-Divergence and Data Derangements
by: Letizia, Nunzio A., et al.
Published: (2023)

Bounding Neyman-Pearson Region with $f$-Divergences
by: Mullhaupt, Andrew, et al.
Published: (2025)

Thermodynamic Transferability in Coarse-Grained Force Fields using Graph Neural Networks
by: Shinkle, Emily, et al.
Published: (2024)

DBR: Divergence-Based Regularization for Debiasing Natural Language Understanding Models
by: Li, Zihao, et al.
Published: (2025)

Linearized Wasserstein Barycenters: Synthesis, Analysis, Representational Capacity, and Applications
by: Werenski, Matthew, et al.
Published: (2024)

Geometric Convergence Analysis of Variational Inference via Bregman Divergences
by: Bohara, Sushil, et al.
Published: (2025)

$f$-Divergence Based Classification: Beyond the Use of Cross-Entropy
by: Novello, Nicola, et al.
Published: (2024)

Ablation Based Counterfactuals
by: Dai, Zheng, et al.
Published: (2024)

Uncertainty-Aware Trajectory Prediction via Rule-Regularized Heteroscedastic Deep Classification
by: Manas, Kumar, et al.
Published: (2025)

wayne0908/NNFDivergence: NNFDivergence
by: Weizhi Li, et al.
Published: (2026)

Statistical Guarantees for Distributionally Robust Optimization with Optimal Transport and OT-Regularized Divergences
by: Birrell, Jeremiah, et al.
Published: (2026)

On $f$-Divergence Principled Domain Adaptation: An Improved Framework
by: Wang, Ziqiao, et al.
Published: (2024)

Matched-Pair Experimental Design with Active Learning
by: Li, Weizhi, et al.
Published: (2025)

Binary and Ternary Quantization Can Enhance Feature Discrimination
by: Lu, Weizhi, et al.
Published: (2025)

Causal-Transformer with Adaptive Mutation-Locking for Early Prediction of Acute Kidney Injury
by: Nie, Weizhi, et al.
Published: (2026)

f-GRPO and Beyond: Divergence-Based Reinforcement Learning Algorithms for General LLM Alignment
by: Haldar, Rajdeep, et al.
Published: (2026)

Adaptive Divergence Regularized Policy Optimization for Fine-tuning Generative Models
by: Fan, Jiajun, et al.
Published: (2025)

Persistent Nonnegative Matrix Factorization via Multi-Scale Graph Regularization
by: Zhang, Jichao, et al.
Published: (2026)

Developing the Temporal Graph Convolutional Neural Network Model to Predict Hip Replacement using Electronic Health Records
by: Hancox, Zoe, et al.
Published: (2024)

A Unified Framework for Diffusion Model Unlearning with f-Divergence
by: Novello, Nicola, et al.
Published: (2025)