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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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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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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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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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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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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
