Cover Image

Automated Machine Learning: From Principles to Practices

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Shen, Zhenqian, Zhang, Yongqi, Wei, Lanning, Zhao, Huan, Yao, Quanming
Format:	Preprint
Published:	2018
Subjects:	Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Versatile Graph Learning Approach through LLM-based Agent
by: Wei, Lanning, et al.
Published: (2023)

Heuristic Learning with Graph Neural Networks: A Unified Framework for Link Prediction
by: Zhang, Juzheng, et al.
Published: (2024)

Understanding Expressivity of GNN in Rule Learning
by: Qiu, Haiquan, et al.
Published: (2023)

Benchmarking drug-drug interaction prediction methods: a perspective of distribution changes
by: Shen, Zhenqian, et al.
Published: (2024)

Case-Based Reasoning Enhances the Predictive Power of LLMs in Drug-Drug Interaction
by: Liu, Guangyi, et al.
Published: (2025)

Towards Versatile Graph Learning Approach: from the Perspective of Large Language Models
by: Wei, Lanning, et al.
Published: (2024)

Knowledge-Enhanced Recommendation with User-Centric Subgraph Network
by: Liu, Guangyi, et al.
Published: (2024)

Beyond Scaleup: Knowledge-aware Parsimony Learning from Deep Networks
by: Yao, Quanming, et al.
Published: (2024)

Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs
by: Zhou, Zhanke, et al.
Published: (2024)

Automated Decision-Making on Networks with LLMs through Knowledge-Guided Evolution
by: Zheng, Xiaohan, et al.
Published: (2025)

Why Low-Precision Transformer Training Fails: An Analysis on Flash Attention
by: Qiu, Haiquan, et al.
Published: (2025)

Attention Sinks Induce Gradient Sinks: Massive Activations as Gradient Regulators in Transformers
by: Chen, Yihong, et al.
Published: (2026)

Accurate and interpretable drug-drug interaction prediction enabled by knowledge subgraph learning
by: Wang, Yaqing, et al.
Published: (2023)

PACIA: Parameter-Efficient Adapter for Few-Shot Molecular Property Prediction
by: Wu, Shiguang, et al.
Published: (2023)

Graph Unitary Message Passing
by: Qiu, Haiquan, et al.
Published: (2024)

Efficient Reinforcement Learning for Zero-Shot Coordination in Evolving Games
by: Hui, Bingyu, et al.
Published: (2025)

Attending on Multilevel Structure of Proteins enables Accurate Prediction of Cold-Start Drug-Target Interactions
by: Zhang, Ziying, et al.
Published: (2025)

FinKario: Event-Enhanced Automated Construction of Financial Knowledge Graph
by: Li, Xiang, et al.
Published: (2025)

Customized Subgraph Selection and Encoding for Drug-drug Interaction Prediction
by: Du, Haotong, et al.
Published: (2024)

Superpose Task-specific Features for Model Merging
by: Qiu, Haiquan, et al.
Published: (2025)

Generalizing Hyperedge Expansion for Hyper-relational Knowledge Graph Modeling
by: Liu, Yu, et al.
Published: (2024)

Comparative Study on Supervised versus Semi-supervised Machine Learning for Anomaly Detection of In-vehicle CAN Network
by: Dong, Yongqi, et al.
Published: (2022)

Automated Graph Machine Learning: Approaches, Libraries, Benchmarks and Directions
by: Wang, Xin, et al.
Published: (2022)

Degree-Conscious Spiking Graph for Cross-Domain Adaptation
by: Wang, Yingxu, et al.
Published: (2024)

Reflective Paper-to-Code Reproduction Enabled by Fine-Grained Verification
by: Zhou, Mingyang, et al.
Published: (2025)

Welfare as a Guiding Principle for Machine Learning -- From Compass, to Lens, to Roadmap
by: Rosenfeld, Nir, et al.
Published: (2025)

The Data Minimization Principle in Machine Learning
by: Ganesh, Prakhar, et al.
Published: (2024)

Evaluating Supervised Machine Learning Models: Principles, Pitfalls, and Metric Selection
by: Liu, Xuanyan, et al.
Published: (2026)

Exploratory Machine Learning with Unknown Unknowns
by: Zhao, Peng, et al.
Published: (2020)

Causal Feature Selection for Responsible Machine Learning
by: Moraffah, Raha, et al.
Published: (2024)

Automated Machine Learning for Remaining Useful Life Predictions
by: Zöller, Marc-André, et al.
Published: (2023)

CHoE: Cross-Domain Heterogeneous Graph Prompt Learning via Structure-Conditioned Experts
by: Li, Peiyuan, et al.
Published: (2026)

DecepChain: Inducing Deceptive Reasoning in Large Language Models
by: Shen, Wei, et al.
Published: (2025)

AI for the Open-World: the Learning Principles
by: Zhang, Jianyu
Published: (2025)

A Practical Introduction to Deep Reinforcement Learning
by: Sun, Yinghan, et al.
Published: (2025)

StructSynth: Leveraging LLMs for Structure-Aware Tabular Data Synthesis in Low-Data Regimes
by: Liu, Siyi, et al.
Published: (2025)

A Sparsity Principle for Partially Observable Causal Representation Learning
by: Xu, Danru, et al.
Published: (2024)

From Data to Behavior: Predicting Unintended Model Behaviors Before Training
by: Wang, Mengru, et al.
Published: (2026)

Towards Evolutionary-based Automated Machine Learning for Small Molecule Pharmacokinetic Prediction
by: de Sá, Alex G. C., et al.
Published: (2024)

PERSCEN: Learning Personalized Interaction Pattern and Scenario Preference for Multi-Scenario Matching
by: Du, Haotong, et al.
Published: (2025)