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Related papers: Learning GraphQL Query Costs (Extended Version)

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Graph comparison is a fundamental operation in data mining and information retrieval. Due to the combinatorial nature of graphs, it is hard to balance the expressiveness of the similarity measure and its scalability. Spectral analysis…

Social and Information Networks · Computer Science 2020-03-04 Anton Tsitsulin , Marina Munkhoeva , Bryan Perozzi

In service-oriented architectures, accurately predicting the Quality of Service (QoS) is crucial for maintaining reliability and enhancing user satisfaction. However, significant challenges remain due to existing methods always overlooking…

Artificial Intelligence · Computer Science 2024-10-28 Shengxiang Hu , Guobing Zou , Song Yang , Yanglan Gan , Bofeng Zhang , Yixin Chen

An expeditious development of graph learning in recent years has found innumerable applications in several diversified fields. Of the main associated challenges are the volume and complexity of graph data. The graph learning models suffer…

Machine Learning · Computer Science 2022-10-21 Ciyuan Peng , Feng Xia , Vidya Saikrishna , Huan Liu

Large language models have demonstrated outstanding performance on a wide range of tasks such as question answering and code generation. On a high level, given an input, a language model can be used to automatically complete the sequence in…

Computation and Language · Computer Science 2023-05-31 Luca Beurer-Kellner , Marc Fischer , Martin Vechev

Many dynamic applications are built upon large network infrastructures, such as social networks, communication networks, biological networks and the Web. Such applications create data that can be naturally modeled as graph streams, in which…

Databases · Computer Science 2011-12-01 Peixiang Zhao , Charu C. Aggarwal , Min Wang

Given the convenience of collecting information through online services, recommender systems now consume large scale data and play a more important role in improving user experience. With the recent emergence of Graph Neural Networks…

Information Retrieval · Computer Science 2020-09-03 Yishi Xu , Yingxue Zhang , Wei Guo , Huifeng Guo , Ruiming Tang , Mark Coates

This paper initializes the study of {\em range subgraph counting} and {\em range subgraph listing}, both of which are motivated by the significant demands in practice to perform graph analytics on subgraphs pertinent to only selected, as…

Data Structures and Algorithms · Computer Science 2023-01-10 Shiyuan Deng , Shangqi Lu , Yufei Tao

Recent advances in graph learning have paved the way for innovative retrieval-augmented generation (RAG) systems that leverage the inherent relational structures in graph data. However, many existing approaches suffer from rigid, fixed…

Information Retrieval · Computer Science 2025-03-26 Yuan Li , Jun Hu , Jiaxin Jiang , Zemin Liu , Bryan Hooi , Bingsheng He

Although machine learning (ML) shows potential in improving query optimization by generating and selecting more efficient plans, ensuring the robustness of learning-based cost models (LCMs) remains challenging. These LCMs currently lack…

Databases · Computer Science 2026-01-13 Baoming Chang , Amin Kamali , Verena Kantere

Continual Graph Learning (CGL), which aims to accommodate new tasks over evolving graph data without forgetting prior knowledge, is garnering significant research interest. Mainstream solutions adopt the memory replay-based idea, ie,…

Machine Learning · Computer Science 2025-02-11 Qi Wang , Tianfei Zhou , Ye Yuan , Rui Mao

Fine-tuning for large language models (LLMs) typically requires substantial amounts of high-quality supervised data, which is both costly and labor-intensive to acquire. While synthetic data generation has emerged as a promising solution,…

Computation and Language · Computer Science 2025-05-28 Zihong Chen , Wanli Jiang , Jinzhe Li , Zhonghang Yuan , Huanjun Kong , Wanli Ouyang , Nanqing Dong

Graph Neural Networks (GNNs) have emerged as powerful tools for supervised machine learning over graph-structured data, while sampling-based node representation learning is widely utilized in unsupervised learning. However, scalability…

Machine Learning · Computer Science 2024-07-23 Vipul Gupta , Xin Chen , Ruoyun Huang , Fanlong Meng , Jianjun Chen , Yujun Yan

The rapidly growing number and variety of Large Language Models (LLMs) present significant challenges in efficiently selecting the appropriate LLM for a given query, especially considering the trade-offs between performance and…

Artificial Intelligence · Computer Science 2025-03-18 Tao Feng , Yanzhen Shen , Jiaxuan You

The problem of handling adaptivity in data analysis, intentional or not, permeates a variety of fields, including test-set overfitting in ML challenges and the accumulation of invalid scientific discoveries. We propose a mechanism for…

Machine Learning · Computer Science 2019-04-03 Blake Woodworth , Vitaly Feldman , Saharon Rosset , Nathan Srebro

Graph Contrastive Learning (GCL) establishes a new paradigm for learning graph representations without human annotations. Although remarkable progress has been witnessed recently, the success behind GCL is still left somewhat mysterious. In…

Machine Learning · Computer Science 2021-10-27 Yanqiao Zhu , Yichen Xu , Qiang Liu , Shu Wu

Recent years have witnessed an upsurge in research interests and applications of machine learning on graphs. However, manually designing the optimal machine learning algorithms for different graph datasets and tasks is inflexible,…

Vector quantization(VQ) is a lossy data compression technique from signal processing for which simple competitive learning is one standard method to quantize patterns from the input space. Extending competitive learning VQ to the domain of…

Computer Vision and Pattern Recognition · Computer Science 2010-01-07 Brijnesh J. Jain , Klaus Obermayer

We present Text-to-OverpassQL, a task designed to facilitate a natural language interface for querying geodata from OpenStreetMap (OSM). The Overpass Query Language (OverpassQL) allows users to formulate complex database queries and is…

Computation and Language · Computer Science 2024-10-10 Michael Staniek , Raphael Schumann , Maike Züfle , Stefan Riezler

As more and more organizations rely on data-driven decision making, large-scale analytics become increasingly important. However, an analyst is often stuck waiting for an exact result. As such, organizations turn to Cloud providers that…

Databases · Computer Science 2020-03-17 Fotis Savva , Christos Anagnostopoulos , Peter Triantafillou

This paper introduces a cost-efficient active learning (AL) framework for classification, featuring a novel query design called candidate set query. Unlike traditional AL queries requiring the oracle to examine all possible classes, our…

Machine Learning · Computer Science 2025-08-20 Yeho Gwon , Sehyun Hwang , Hoyoung Kim , Jungseul Ok , Suha Kwak