AutoML-GPT: Large Language Model for AutoML
Paper
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2309.01125
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Published
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1
AutoML/NAS
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SAI: Solving AI Tasks with Systematic Artificial Intelligence in Communication Network
Paper • 2310.09049 • Published • 1 -
Prompt2Model: Generating Deployable Models from Natural Language Instructions
Paper • 2308.12261 • Published • 1 -
LLMatic: Neural Architecture Search via Large Language Models and Quality Diversity Optimization
Paper • 2306.01102 • Published • 1 -
EvoPrompting: Language Models for Code-Level Neural Architecture Search
Paper • 2302.14838 • Published • 1 -
Neural Architecture Search on Efficient Transformers and Beyond
Paper • 2207.13955 • Published • 1 -
BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search
Paper • 2103.12424 • Published • 1 -
DARTS+: Improved Differentiable Architecture Search with Early Stopping
Paper • 1909.06035 • Published • 1 -
AutoML-GPT: Automatic Machine Learning with GPT
Paper • 2305.02499 • Published • 3 -
The Impact of Depth and Width on Transformer Language Model Generalization
Paper • 2310.19956 • Published • 9 -
AutoMoE: Heterogeneous Mixture-of-Experts with Adaptive Computation for Efficient Neural Machine Translation
Paper • 2210.07535 • Published • 1 -
Improving Differentiable Architecture Search via Self-Distillation
Paper • 2302.05629 • Published • 1 -
NASRec: Weight Sharing Neural Architecture Search for Recommender Systems
Paper • 2207.07187 • Published • 1 -
Efficient Model Adaptation for Continual Learning at the Edge
Paper • 2308.02084 • Published • 1 -
AutoDES: AutoML Pipeline Generation of Classification with Dynamic Ensemble Strategy Selection
Paper • 2201.00207 • Published • 1 -
Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML
Paper • 2307.08364 • Published • 1 -
A Scalable AutoML Approach Based on Graph Neural Networks
Paper • 2111.00083 • Published • 1 -
Assessing the Use of AutoML for Data-Driven Software Engineering
Paper • 2307.10774 • Published • 1 -
AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks
Paper • 2306.08107 • Published • 1 -
MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks
Paper • 2304.14979 • Published • 1 -
ChatGPT as your Personal Data Scientist
Paper • 2305.13657 • Published • 1 -
OmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System
Paper • 2303.00501 • Published • 1 -
OutRank: Speeding up AutoML-based Model Search for Large Sparse Data sets with Cardinality-aware Feature Ranking
Paper • 2309.01552 • Published • 1 -
AutoTransfer: AutoML with Knowledge Transfer -- An Application to Graph Neural Networks
Paper • 2303.07669 • Published • 1 -
Challenges and Barriers of Using Low Code Software for Machine Learning
Paper • 2211.04661 • Published • 1 -
Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
Paper • 2305.03403 • Published • 2 -
AutoML in Heavily Constrained Applications
Paper • 2306.16913 • Published • 1 -
The Technological Emergence of AutoML: A Survey of Performant Software and Applications in the Context of Industry
Paper • 2211.04148 • Published • 1 -
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning
Paper • 2007.04074 • Published • 1 -
FairAutoML: Embracing Unfairness Mitigation in AutoML
Paper • 2111.06495 • Published • 1 -
AutoMLBench: A Comprehensive Experimental Evaluation of Automated Machine Learning Frameworks
Paper • 2204.08358 • Published • 1 -
Adaptation Strategies for Automated Machine Learning on Evolving Data
Paper • 2006.06480 • Published • 1 -
End-to-End Neural Network Compression via ell_1{ell_2} Regularized Latency Surrogates
Paper • 2306.05785 • Published • 1 -
SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning
Paper • 2207.03677 • Published • 1 -
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search
Paper • 2201.11679 • Published • 1 -
Generative Model for Models: Rapid DNN Customization for Diverse Tasks and Resource Constraints
Paper • 2308.15003 • Published • 1 -
RARTS: An Efficient First-Order Relaxed Architecture Search Method
Paper • 2008.03901 • Published • 1 -
Growing Efficient Deep Networks by Structured Continuous Sparsification
Paper • 2007.15353 • Published • 1 -
Network Pruning via Transformable Architecture Search
Paper • 1905.09717 • Published • 1 -
Neural Architecture Search: Insights from 1000 Papers
Paper • 2301.08727 • Published • 2 -
DASS: Differentiable Architecture Search for Sparse neural networks
Paper • 2207.06968 • Published • 1 -
LLaMA-NAS: Efficient Neural Architecture Search for Large Language Models
Paper • 2405.18377 • Published • 18