:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Su, Jinyan, Dean, Sarah
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2406.01481
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On Targeted Manipulation and Deception when Optimizing LLMs for User Feedback
by: Williams, Marcus, et al.
Published: (2024)

Initializing Services in Interactive ML Systems for Diverse Users
by: Bose, Avinandan, et al.
Published: (2023)

StreamFP: Learnable Fingerprint-guided Data Selection for Efficient Stream Learning
by: Shi, Tongjun, et al.
Published: (2024)

Un-mixing Test-time Adaptation under Heterogeneous Data Streams
by: Su, Zixian, et al.
Published: (2024)

Open-Medical-R1: How to Choose Data for RLVR Training at Medicine Domain
by: Qiu, Zhongxi, et al.
Published: (2025)

A review on Machine Learning based User-Centric Multimedia Streaming Techniques
by: Ghosh, Monalisa, et al.
Published: (2024)

The Illusion of Specialization: Unveiling the Domain-Invariant "Standing Committee" in Mixture-of-Experts Models
by: Wang, Yan, et al.
Published: (2026)

Squeezing More from the Stream : Learning Representation Online for Streaming Reinforcement Learning
by: Nilaksh, et al.
Published: (2026)

Feature Importance Depends on Properties of the Data: Towards Choosing the Correct Explanations for Your Data and Decision Trees based Models
by: Ayad, Célia Wafa, et al.
Published: (2025)

Understanding the Impact of Differentially Private Training on Memorization of Long-Tailed Data
by: Zhang, Jiaming, et al.
Published: (2026)

In-context Learning of Evolving Data Streams with Tabular Foundational Models
by: Lourenço, Afonso, et al.
Published: (2025)

Autonomous Drift Learning in Data Streams: A Unified Perspective
by: Yang, Xiaoyu, et al.
Published: (2026)

Multi-Label Transfer Learning in Non-Stationary Data Streams
by: Du, Honghui, et al.
Published: (2025)

StreamEnsemble: Predictive Queries over Spatiotemporal Streaming Data
by: Chaves, Anderson, et al.
Published: (2024)

Continuous Fair SMOTE -- Fairness-Aware Stream Learning from Imbalanced Data
by: Lammers, Kathrin, et al.
Published: (2025)

Choosing a Classical Planner with Graph Neural Networks
by: Vatter, Jana, et al.
Published: (2024)

Adaptive Hoeffding Tree with Transfer Learning for Streaming Synchrophasor Data Sets
by: Mrabet, Zakaria El, et al.
Published: (2025)

Pre-trained Large Language Models Learn Hidden Markov Models In-context
by: Dai, Yijia, et al.
Published: (2025)

Choosing How to Remember: Adaptive Memory Structures for LLM Agents
by: Lu, Mingfei, et al.
Published: (2026)

Resilient Class-Incremental Learning: on the Interplay of Drifting, Unlabelled and Imbalanced Data Streams
by: Li, Jin, et al.
Published: (2026)

Generalized Incremental Learning under Concept Drift across Evolving Data Streams
by: Yu, En, et al.
Published: (2025)

Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers
by: de Haan, Pim, et al.
Published: (2023)

Residual Stream Analysis of Overfitting And Structural Disruptions
by: Liu, Quan, et al.
Published: (2026)

Causify DataFlow: A Framework For High-performance Machine Learning Stream Computing
by: Saggese, Giacinto Paolo, et al.
Published: (2025)

Large Language Models can Strategically Deceive their Users when Put Under Pressure
by: Scheurer, Jérémy, et al.
Published: (2023)

Evaluation for Regression Analyses on Evolving Data Streams
by: Sun, Yibin, et al.
Published: (2025)

Learning From High-Dimensional Cyber-Physical Data Streams for Diagnosing Faults in Smart Grids
by: Hassani, Hossein, et al.
Published: (2023)

Revisiting Adam for Streaming Reinforcement Learning
by: Gogianu, Florin, et al.
Published: (2026)

Intentional Updates for Streaming Reinforcement Learning
by: Sharifnassab, Arsalan, et al.
Published: (2026)

Machine Learning Approaches for Diagnostics and Prognostics of Industrial Systems Using Open Source Data from PHM Data Challenges: A Review
by: Su, Hanqi, et al.
Published: (2023)

Choose Your Explanation: A Comparison of SHAP and GradCAM in Human Activity Recognition
by: Tempel, Felix, et al.
Published: (2024)

Which PPML Would a User Choose? A Structured Decision Support Framework for Developers to Rank PPML Techniques Based on User Acceptance Criteria
by: Löbner, Sascha, et al.
Published: (2024)

Streaming Deep Reinforcement Learning Finally Works
by: Elsayed, Mohamed, et al.
Published: (2024)

Learn How to Query from Unlabeled Data Streams in Federated Learning
by: Sun, Yuchang, et al.
Published: (2024)

Beyond Expected Return: Accounting for Policy Reproducibility when Evaluating Reinforcement Learning Algorithms
by: Flageat, Manon, et al.
Published: (2023)

Renaissance of RNNs in Streaming Clinical Time Series: Compact Recurrence Remains Competitive with Transformers
by: Tong, Ran, et al.
Published: (2025)

Online Sparse Feature Selection in Data Streams via Differential Evolution
by: Xu, Ruiyang
Published: (2025)

Towards Differentiating Between Failures and Domain Shifts in Industrial Data Streams
by: Wojak-Strzelecka, Natalia, et al.
Published: (2026)

Why Federated Optimization Fails to Achieve Perfect Fitting? A Theoretical Perspective on Client-Side Optima
by: Lei, Zhongxiang, et al.
Published: (2025)

packetLSTM: Dynamic LSTM Framework for Streaming Data with Varying Feature Space
by: Agarwal, Rohit, et al.
Published: (2024)