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07/30/2023
IWEK: An Interpretable What-If Estimator for Database Knobs
The knobs of modern database management systems have significant impact ...
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07/25/2023
Duet: efficient and scalable hybriD neUral rElation undersTanding
Learned cardinality estimation methods have achieved high precision comp...
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07/13/2023
MaxCorrMGNN: A Multi-Graph Neural Network Framework for Generalized Multimodal Fusion of Medical Data for Outcome Prediction
With the emergence of multimodal electronic health records, the evidence...
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05/30/2023
Contrastive Shapelet Learning for Unsupervised Multivariate Time Series Representation Learning
Recent studies have shown great promise in unsupervised representation l...
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05/28/2023
One stone, two birds: A lightweight multidimensional learned index with cardinality support
Innovative learning based structures have recently been proposed to tack...
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04/11/2023
TodyNet: Temporal Dynamic Graph Neural Network for Multivariate Time Series Classification
Multivariate time series classification (MTSC) is an important data mini...
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03/24/2023
UniTS: A Universal Time Series Analysis Framework with Self-supervised Representation Learning
Machine learning has emerged as a powerful tool for time series analysis...
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02/25/2023
DCLP: Neural Architecture Predictor with Curriculum Contrastive Learning
Neural predictors currently show great potential in the performance eval...
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02/25/2023
TS-Cabinet: Hierarchical Storage for Cloud-Edge-End Time-series Database
Hierarchical data storage is crucial for cloud-edge-end time-series data...
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02/21/2023
FedST: Federated Shapelet Transformation for Interpretable Time Series Classification
This paper studies how to develop accurate and interpretable time series...
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10/25/2022
Fusing Modalities by Multiplexed Graph Neural Networks for Outcome Prediction in Tuberculosis
In a complex disease such as tuberculosis, the evidence for the disease ...
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10/19/2022
Differentiable Self-Adaptive Learning Rate
Learning rate adaptation is a popular topic in machine learning. Gradien...
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06/29/2022
AAE: An Active Auto-Estimator for Improving Graph Storage
Nowadays, graph becomes an increasingly popular model in many real appli...
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06/18/2022
EEML: Ensemble Embedded Meta-learning
To accelerate learning process with few samples, meta-learning resorts t...
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05/20/2022
FIND:Explainable Framework for Meta-learning
Meta-learning is used to efficiently enable the automatic selection of m...
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03/26/2022
AutoTS: Automatic Time Series Forecasting Model Design Based on Two-Stage Pruning
Automatic Time Series Forecasting (TSF) model design which aims to help ...
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02/21/2022
Dynamic Relation Repairing for Knowledge Enhancement
Dynamic relation repair aims to efficiently validate and repair the inst...
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01/24/2022
AutoMC: Automated Model Compression based on Domain Knowledge and Progressive search strategy
Model compression methods can reduce model complexity on the premise of ...
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01/09/2022
TPAD: Identifying Effective Trajectory Predictions Under the Guidance of Trajectory Anomaly Detection Model
Trajectory Prediction (TP) is an important research topic in computer vi...
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12/10/2021
Addressing Deep Learning Model Uncertainty in Long-Range Climate Forecasting with Late Fusion
Global warming leads to the increase in frequency and intensity of clima...
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11/21/2021
Experience-Enhanced Learning: One Size Still does not Fit All in Automatic Database
Recent years, the database committee has attempted to develop automatic ...
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09/21/2021
Search For Deep Graph Neural Networks
Current GNN-oriented NAS methods focus on the search for different layer...
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04/09/2021
FL-AGCNS: Federated Learning Framework for Automatic Graph Convolutional Network Search
Recently, some Neural Architecture Search (NAS) techniques are proposed ...
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01/08/2021
Approximate Query Processing for Group-By Queries based on Conditional Generative Models
The Group-By query is an important kind of query, which is common and wi...
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12/13/2020
A Dual-Store Structure for Knowledge Graphs
To effectively manage increasing knowledge graphs in various domains, a ...
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11/17/2020
Multi-SQL: An extensible multi-model data query language
Big data management aims to establish data hubs that support data in mul...
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10/22/2020
Efficient RDF Graph Storage based on Reinforcement Learning
Knowledge graph is an important cornerstone of artificial intelligence. ...
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10/19/2020
Musings about Constructions of Efficient Latin Hypercube Designs with Flexible Run-sizes
Efficient Latin hypercube designs (LHDs), including maximin distance LHD...
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10/15/2020
Auto-STGCN: Autonomous Spatial-Temporal Graph Convolutional Network Search Based on Reinforcement Learning and Existing Research Results
In recent years, many spatial-temporal graph convolutional network (STGC...
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09/18/2020
EM-RBR: a reinforced framework for knowledge graph completion from reasoning perspective
Knowledge graph completion aims to predict the new links in given entiti...
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08/15/2020
Automatic Storage Structure Selection for hybrid Workload
In the use of database systems, the design of the storage engine and dat...
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07/23/2020
Reachability Queries with Label and Substructure Constraints on Knowledge Graphs
Since knowledge graphs (KGs) describe and model the relationships betwee...
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07/07/2020
Auto-CASH: Autonomous Classification Algorithm Selection with Deep Q-Network
The great amount of datasets generated by various data sources have pose...
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07/06/2020
Multi-Objective Neural Architecture Search Based on Diverse Structures and Adaptive Recommendation
The search space of neural architecture search (NAS) for convolutional n...
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06/16/2020
Index Selection for NoSQL Database with Deep Reinforcement Learning
We propose a new approach of NoSQL database index selection. For differe...
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06/05/2020
Efficient Semi-External Depth-First Search
Computing Depth-First Search (DFS) results, i.e. depth-first order or DF...
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04/20/2020
Neural Network Segmentation of Cell Ultrastructure Using Incomplete Annotation
The Pancreatic beta cell is an important target in diabetes research. Fo...
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04/09/2020
ConsciousControlFlow(CCF): A Demonstration for conscious Artificial Intelligence
In this demo, we present ConsciousControlFlow(CCF), a prototype system t...
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03/05/2020
LAQP: Learning-based Approximate Query Processing
Querying on big data is a challenging task due to the rapid growth of da...
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03/03/2020
Automatic Hyper-Parameter Optimization Based on Mapping Discovery from Data to Hyper-Parameters
Machine learning algorithms have made remarkable achievements in the fie...
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12/02/2019
ExperienceThinking: Hyperparameter Optimization with Budget Constraints
The problem of hyperparameter optimization exists widely in the real lif...
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10/24/2019
Auto-Model: Utilizing Research Papers and HPO Techniques to Deal with the CASH problem
In many fields, a mass of algorithms with completely different hyperpara...
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09/21/2019
Automatic Weighted Matching Rectifying Rule Discovery for Data Repairing
Data repairing is a key problem in data cleaning which aims to uncover a...
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08/22/2019
A General Data Renewal Model for Prediction Algorithms in Industrial Data Analytics
In industrial data analytics, one of the fundamental problems is to util...
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08/10/2019
Autoregressive-Model-Based Methods for Online Time Series Prediction with Missing Values: an Experimental Evaluation
Time series prediction with missing values is an important problem of ti...
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08/09/2019
LSTM-based Flow Prediction
In this paper, a method of prediction on continuous time series variable...
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07/02/2019
Automated Detection and Type Classification of Central Venous Catheters in Chest X-Rays
Central venous catheters (CVCs) are commonly used in critical care setti...
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04/26/2019
Regular Expression Matching on billion-nodes Graphs
In many applications, it is necessary to retrieve pairs of vertices with...
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04/25/2019
GPU-based Efficient Join Algorithms on Hadoop
The growing data has brought tremendous pressure for query processing an...
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08/05/2018
