:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Dorrego, Gustavo A.
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2603.08377
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Fractional Fox H-Function Kernel for Support Vector Machines: Robust Classification via Weighted Transmutation Operators
by: Dorrego, Gustavo
Published: (2026)

Spectral Analysis of Weighted Weyl Fractional Operators: Aging, Infinite Memory, and the Amnesia Effect
by: Dorrego, Gustavo
Published: (2026)

A Unified Spectral Framework for Aging, Heterogeneous, and Distributed Order Systems via Weighted Weyl-Sonine Operators
by: Dorrego, Gustavo
Published: (2026)

A Semigroup Approach to Weighted Weyl-Sonine Operators: Bypassing Bernstein Functions for Well-Posedness
by: Dorrego, Gustavo
Published: (2026)

Robust Universum Twin Support Vector Machine for Imbalanced Data
by: Tanveer, M., et al.
Published: (2024)

Robust Support Vector Machines for Imbalanced and Noisy Data via Benders Decomposition
by: Mohasel, Seyed Mojtaba, et al.
Published: (2025)

Sampling Imbalanced Data with Multi-objective Bilevel Optimization
by: Medlin, Karen, et al.
Published: (2025)

Close to Reality: Interpretable and Feasible Data Augmentation for Imbalanced Learning
by: da Silva, Matheus Camilo, et al.
Published: (2026)

Byzantine-Robust and Differentially Private Federated Optimization under Weaker Assumptions
by: Islamov, Rustem, et al.
Published: (2026)

Stochastic-Constrained Stochastic Optimization with Markovian Data
by: Kim, Yeongjong, et al.
Published: (2023)

Beyond Imbalance Ratio: Data Characteristics as Critical Moderators of Oversampling Method Selection
by: Jiang, Yuwen, et al.
Published: (2026)

CAMO: A Class-Aware Minority-Optimized Ensemble for Robust Language Model Evaluation on Imbalanced Data
by: Ehab, Mohamed, et al.
Published: (2026)

Sparse Representation Classification Beyond L1 Minimization and the Subspace Assumption
by: Shen, Cencheng, et al.
Published: (2015)

A Bilevel Optimization Framework for Imbalanced Data Classification
by: Medlin, Karen, et al.
Published: (2024)

Optimized Deferral for Imbalanced Settings
by: Cortes, Corinna, et al.
Published: (2026)

Towards Weaker Variance Assumptions for Stochastic Optimization
by: Alacaoglu, Ahmet, et al.
Published: (2025)

Beyond Synthetic Augmentation: Group-Aware Threshold Calibration for Robust Balanced Accuracy in Imbalanced Learning
by: Gittlin, Hunter
Published: (2025)

Markovian Sliced Wasserstein Distances: Beyond Independent Projections
by: Nguyen, Khai, et al.
Published: (2023)

Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance
by: Kaushik, Chiraag, et al.
Published: (2024)

Weighted Sobolev Spaces and Distributional Spectral Theory for Generalized Aging Operators via Transmutation Methods
by: Dorrego, Gustavo
Published: (2026)

Gradient Imbalance in Direct Preference Optimization
by: Ma, Qinwei, et al.
Published: (2025)

First Provable Guarantees for Practical Private FL: Beyond Restrictive Assumptions
by: Shulgin, Egor, et al.
Published: (2025)

Beyond Lipschitz: Data-Driven Robustness via Discrete Modulus of Continuity
by: Dölz, Jürgen, et al.
Published: (2026)

On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions
by: Hong, Yusu, et al.
Published: (2024)

Graphical Modelling without Independence Assumptions for Uncentered Data
by: Andrew, Bailey, et al.
Published: (2024)

Assumption-Lean and Data-Adaptive Post-Prediction Inference
by: Miao, Jiacheng, et al.
Published: (2023)

Robust Generative Learning with Lipschitz-Regularized $α$-Divergences Allows Minimal Assumptions on Target Distributions
by: Chen, Ziyu, et al.
Published: (2024)

A Markovian Model for Learning-to-Optimize
by: Sucker, Michael, et al.
Published: (2024)

Streaming Federated Learning with Markovian Data
by: Huynh, Tan-Khiem, et al.
Published: (2025)

Beyond the Independence Assumption: Finite-Sample Guarantees for Deep Q-Learning under $τ$-Mixing
by: Halgryn, Leon, et al.
Published: (2026)

Probabilistic Neural Networks (PNNs) with t-Distributed Outputs: Adaptive Prediction Intervals Beyond Gaussian Assumptions
by: Pourkamali-Anaraki, Farhad
Published: (2025)

Feature Selection via Robust Weighted Score for High Dimensional Binary Class-Imbalanced Gene Expression Data
by: Khan, Zardad, et al.
Published: (2024)

Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions
by: Jiang, Wei, et al.
Published: (2024)

Beyond Markovian: Reflective Exploration via Bayes-Adaptive RL for LLM Reasoning
by: Zhang, Shenao, et al.
Published: (2025)

Convergence Of Consistency Model With Multistep Sampling Under General Data Assumptions
by: Chen, Yiding, et al.
Published: (2025)

BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL
by: Hung, Yu-Heng, et al.
Published: (2025)

Exact Reformulation and Optimization for Direct Metric Optimization in Binary Imbalanced Classification
by: Peng, Le, et al.
Published: (2025)

Robust Offline Reinforcement Learning for Non-Markovian Decision Processes
by: Huang, Ruiquan, et al.
Published: (2024)

Learning Confidence Bounds for Classification with Imbalanced Data
by: Clifford, Matt, et al.
Published: (2024)

A Comprehensive Survey on Imbalanced Data Learning
by: Gao, Xinyi, et al.
Published: (2025)