VEGA

5 papers tagged archive 2025-07-28

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

VEGA is an AutoML framework that is compatible and optimized for multiple hardware platforms. It integrates various modules of AutoML, including Neural Architecture Search (NAS), Hyperparameter Optimization (HPO), Auto Data Augmentation, Model Compression, and Fully Train. To support a variety of search algorithms and tasks, it involves a fine-grained search space and a description language to enable easy adaptation to different search algorithms and tasks.

Source: VEGA: Towards an End-to-End Configurable AutoML Pipeline

Papers archive 2025-07-28

5 shown of 5, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Learning to Rank Pre-trained Vision-Language Models for Downstream Tasks
30 Dec 2024 · 0 repositories · arXiv:2412.20682
VEGA: Learning Interleaved Image-Text Comprehension in Vision-Language Large Models
14 Jun 2024 · 0 repositories · arXiv:2406.10228
A TinyML Platform for On-Device Continual Learning with Quantized Latent Replays
20 Oct 2021 · 0 repositories · arXiv:2110.10486
TransNAS-Bench-101: Improving Transferability and Generalizability of Cross-Task Neural Architecture Search
25 May 2021 · 4 repositories · arXiv:2105.11871

Syntology ran 0 of 9 samples · 9 unverified
VEGA: Towards an End-to-End Configurable AutoML Pipeline
3 Nov 2020 · 1 repository · arXiv:2011.01507

Tasks archive 2025-07-28

13 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

Task	Papers
Neural Architecture Search	2
AutoML	1
BIG-bench Machine Learning	1
Continual Learning	1
Data Augmentation	1
Diversity	1
Hyperparameter Optimization	1
Learning-To-Rank	1
Model Compression	1
Model Selection	1
Quantization	1
Reading Comprehension	1
Transfer Learning	1

Usage over time archive 2025-07-28

Papers per year the archive tags with this method, by the paper's archive date (5 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

AutoML

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections