:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Gurbuz, Mustafa Burak, Zheng, Xingyu, Dovrolis, Constantine
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2504.05250
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Growing Winning Subnetworks, Not Pruning Them: A Paradigm for Density Discovery in Sparse Neural Networks
by: Yao, Qihang, et al.
Published: (2025)

Continual Knowledge Updating in LLM Systems: Learning Through Multi-Timescale Memory Dynamics
by: Pattichis, Andreas, et al.
Published: (2026)

Patch-Based Contrastive Learning and Memory Consolidation for Online Unsupervised Continual Learning
by: Taylor, Cameron, et al.
Published: (2024)

Anchored Diffusion Language Model
by: Rout, Litu, et al.
Published: (2025)

AnCoder: Anchored Code Generation via Discrete Diffusion Models
by: Xue, Anton, et al.
Published: (2026)

Accelerating String-Key Learned Index Structures via Memoization-based Incremental Training
by: Kim, Minsu, et al.
Published: (2024)

Selective Prediction via Training Dynamics
by: Rabanser, Stephan, et al.
Published: (2022)

Zero Shot Molecular Generation via Similarity Kernels
by: Elijošius, Rokas, et al.
Published: (2024)

Metrics for Inter-Dataset Similarity with Example Applications in Synthetic Data and Feature Selection Evaluation -- Extended Version
by: Rajabinasab, Muhammad, et al.
Published: (2025)

Prediction Error-based Classification for Class-Incremental Learning
by: Zając, Michał, et al.
Published: (2023)

IDK-S: Incremental Distributional Kernel for Streaming Anomaly Detection
by: Xu, Yang, et al.
Published: (2025)

Generalization Error Analysis for Selective State-Space Models Through the Lens of Attention
by: Honarpisheh, Arya, et al.
Published: (2025)

Kernel Representation and Similarity Measure for Incomplete Data
by: Cao, Yang, et al.
Published: (2025)

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty
by: Cho, Yeseul, et al.
Published: (2025)

Test-Time Anchoring for Discrete Diffusion Posterior Sampling
by: Rout, Litu, et al.
Published: (2025)

A Doeblin-Anchored Contrastive Chart for Learning Markov Transition Kernels
by: Xu, Ao
Published: (2026)

Online Selective Conformal Prediction: Errors and Solutions
by: Sale, Yusuf, et al.
Published: (2025)

Robust Local Polynomial Regression with Similarity Kernels
by: Shulman, Yaniv
Published: (2025)

When Molecular Similarity Works: Property Cliffs Reveal Hidden Errors
by: Hu, Di, et al.
Published: (2026)

Hierarchical Semantic Tree Anchoring for CLIP-Based Class-Incremental Learning
by: Hu, Tao, et al.
Published: (2025)

Enhancing Conformal Prediction via Class Similarity
by: Fargion, Ariel, et al.
Published: (2025)

Stable Unlearnable Example: Enhancing the Robustness of Unlearnable Examples via Stable Error-Minimizing Noise
by: Liu, Yixin, et al.
Published: (2023)

Class Incremental Learning for Algorithm Selection
by: Nemeth, Mate Botond, et al.
Published: (2025)

Reconstruction Error-based Anomaly Detection with Few Outlying Examples
by: Angiulli, Fabrizio, et al.
Published: (2023)

Center-Sensitive Kernel Optimization for Efficient On-Device Incremental Learning
by: Zhang, Dingwen, et al.
Published: (2024)

Predicting Performance of Symbolic and Prompt Programs with Examples
by: Zheng, Chengqi, et al.
Published: (2026)

Relative Error Embeddings for the Gaussian Kernel Distance
by: Chen, Di, et al.
Published: (2016)

MaxSketch: Robust Distinct Counting in Streams via Random Projections
by: Tsikouras, Nikos, et al.
Published: (2026)

GraSP: Simple yet Effective Graph Similarity Predictions
by: Zheng, Haoran, et al.
Published: (2024)

Towards a Foundation-Model Paradigm for Aerodynamic Prediction in Three-dimensional Design
by: Yang, Yunjia, et al.
Published: (2026)

Private, Efficient and Scalable Kernel Learning for Medical Image Analysis
by: Hannemann, Anika, et al.
Published: (2024)

Distribution Shift Is Key to Learning Invariant Prediction
by: Zheng, Hong, et al.
Published: (2026)

Training-Free Generative Modeling via Kernelized Stochastic Interpolants
by: Coeurdoux, Florentin, et al.
Published: (2026)

Dynamic Incremental Optimization for Best Subset Selection
by: Ren, Shaogang, et al.
Published: (2024)

Joint Training for Selective Prediction
by: Li, Zhaohui, et al.
Published: (2024)

Fast Second-Order Online Kernel Learning through Incremental Matrix Sketching and Decomposition
by: Wen, Dongxie, et al.
Published: (2024)

Predicting the Susceptibility of Examples to Catastrophic Forgetting
by: Hacohen, Guy, et al.
Published: (2024)

Dynamic Similarity Graph Construction with Kernel Density Estimation
by: Laenen, Steinar, et al.
Published: (2025)

Training-free LLM Verification via Recycling Few-shot Examples
by: Lee, Dongseok, et al.
Published: (2025)

Adaptive Kernel Selection for Kernelized Diffusion Maps
by: Aboussaad, Othmane, et al.
Published: (2026)