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08/11/2023
Composable Function-preserving Expansions for Transformer Architectures
Training state-of-the-art neural networks requires a high cost in terms ...
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02/06/2023
Multipath agents for modular multitask ML systems
A standard ML model is commonly generated by a single method that specif...
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09/29/2022
A Multiagent Framework for the Asynchronous and Collaborative Extension of Multitask ML Systems
The traditional ML development methodology does not enable a large numbe...
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09/15/2022
A Continual Development Methodology for Large-scale Multitask Dynamic ML Systems
The traditional Machine Learning (ML) methodology requires to fragment t...
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05/25/2022
An Evolutionary Approach to Dynamic Introduction of Tasks in Large-scale Multitask Learning Systems
Multitask learning assumes that models capable of learning from multiple...
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05/22/2022
muNet: Evolving Pretrained Deep Neural Networks into Scalable Auto-tuning Multitask Systems
Most uses of machine learning today involve training a model from scratc...
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03/31/2022
Scaling Up Models and Data with and
Recent neural network-based language models have benefited greatly from ...
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09/09/2020
Routing Networks with Co-training for Continual Learning
The core challenge with continual learning is catastrophic forgetting, t...
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11/26/2019
Ranking architectures using meta-learning
Neural architecture search has recently attracted lots of research effor...
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10/10/2019
Gumbel-Matrix Routing for Flexible Multi-task Learning
This paper proposes a novel per-task routing method for multi-task appli...
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07/30/2019
Temporal coding in spiking neural networks with alpha synaptic function
The timing of individual neuronal spikes is essential for biological bra...
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06/19/2019
Transfer NAS: Knowledge Transfer between Search Spaces with Transformer Agents
Recent advances in Neural Architecture Search (NAS) have produced state-...
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02/15/2019
Fast Task-Aware Architecture Inference
Neural architecture search has been shown to hold great promise towards ...
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02/02/2019
Parameter-Efficient Transfer Learning for NLP
Fine-tuning large pre-trained models is an effective transfer mechanism ...
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12/27/2018
Neural Architecture Search Over a Graph Search Space
Neural architecture search (NAS) enabled the discovery of state-of-the-a...
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11/24/2018
Evolutionary-Neural Hybrid Agents for Architecture Search
Neural Architecture Search has recently shown potential to automate the ...
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03/07/2018
Transfer Automatic Machine Learning
Building effective neural networks requires many design choices. These i...
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01/23/2018
Analyzing Language Learned by an Active Question Answering Agent
We analyze the language learned by an agent trained with reinforcement l...
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10/30/2017
Transfer Learning to Learn with Multitask Neural Model Search
Deep learning models require extensive architecture design exploration a...
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05/22/2017