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20232026
most citedBiological Pathway Guided Gene Selection Through Collaborative Reinforcement Learning

1 citations · 7 across the 31 of their papers we have counts for

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Showing 2025Show all

8 papers · 1 filter

cs.AI2025

Autonomous Data Agents: A New Opportunity for Smart Data

Yanjie Fu, Dongjie Wang, Wangyang Ying +4

As data continues to grow in scale and complexity, preparing, transforming, and analyzing it remains labor-intensive, repetitive, and difficult to scale. Since data contains knowle…

cs.LG2025

Permutation-Invariant Representation Learning for Robust and Privacy-Preserving Feature Selection

Rui Liu, Tao Zhe, Yanjie Fu +3

Feature selection eliminates redundancy among features to improve downstream task performance while reducing computational overhead. Existing methods often struggle to capture intr…

cs.LG2025

Causal Graph Profiling via Structural Divergence for Robust Anomaly Detection in Cyber-Physical Systems

Arun Vignesh Malarkkan, Haoyue Bai, Dongjie Wang +1

With the growing complexity of cyberattacks targeting critical infrastructures such as water treatment networks, there is a pressing need for robust anomaly detection strategies th…

cs.AI2025★ 1 cited

Towards Urban Planing AI Agent in the Age of Agentic AI

Rui Liu, Tao Zhe, Zhong-Ren Peng +4

Generative AI, large language models, and agentic AI have emerged separately of urban planning. However, the convergence between AI and urban planning presents an interesting oppor…

cs.LG2025★ 1 cited

Biological Pathway Guided Gene Selection Through Collaborative Reinforcement Learning

Ehtesamul Azim, Dongjie Wang, Tae Hyun Hwang +2

Gene selection in high-dimensional genomic data is essential for understanding disease mechanisms and improving therapeutic outcomes. Traditional feature selection methods effectiv…

cs.LG2025

Continuous Optimization for Feature Selection with Permutation-Invariant Embedding and Policy-Guided Search

Rui Liu, Rui Xie, Zijun Yao +2

Feature selection removes redundant features to enhanc performance and computational efficiency in downstream tasks. Existing works often struggle to capture complex feature intera…

cs.LG2025

LEKA:LLM-Enhanced Knowledge Augmentation

Xinhao Zhang, Jinghan Zhang, Fengran Mo +3

Humans excel in analogical learning and knowledge transfer and, more importantly, possess a unique understanding of identifying appropriate sources of knowledge. From a model's per…

cs.LG2025

Iterative Feature Space Optimization through Incremental Adaptive Evaluation

Yanping Wu, Yanyong Huang, Zhengzhang Chen +5

Iterative feature space optimization involves systematically evaluating and adjusting the feature space to improve downstream task performance. However, existing works suffer from…