James Seale Smith

Orcid: 0000-0001-9210-0161

Affiliations:
  • Georgia Institute of Technology, Atlanta, GA, USA


According to our database1, James Seale Smith authored at least 25 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
Lifelong Machine Learning without Lifelong Data Retention.
PhD thesis, 2024

2023
Continual Diffusion with STAMINA: STack-And-Mask INcremental Adapters.
CoRR, 2023

HePCo: Data-Free Heterogeneous Prompt Consolidation for Continual Federated Learning.
CoRR, 2023

Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRA.
CoRR, 2023

Fast Trainable Projection for Robust Fine-tuning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Going Beyond Nouns With Vision & Language Models Using Synthetic Data.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

A Closer Look at Rehearsal-Free Continual Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

CODA-Prompt: COntinual Decomposed Attention-Based Prompting for Rehearsal-Free Continual Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

ConStruct-VL: Data-Free Continual Structured VL Concepts Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Continual Causality: A Retrospective of the Inaugural AAAI-23 Bridge Program.
Proceedings of the AAAI Bridge Program on Continual Causality, 2023

2022
On the Transferability of Visual Features in Generalized Zero-Shot Learning.
CoRR, 2022

FedFOR: Stateless Heterogeneous Federated Learning with First-Order Regularization.
CoRR, 2022

Lifelong Wandering: A realistic few-shot online continual learning setting.
CoRR, 2022

A Closer Look at Rehearsal-Free Continual Learning.
CoRR, 2022

A Closer Look at Knowledge Distillation with Features, Logits, and Gradients.
CoRR, 2022

Incremental Learning with Differentiable Architecture and Forgetting Search.
Proceedings of the International Joint Conference on Neural Networks, 2022


System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games.
Proceedings of the Second International Conference on AI-ML Systems, 2022

2021
Memory-Efficient Semi-Supervised Continual Learning: The World is its Own Replay Buffer.
Proceedings of the International Joint Conference on Neural Networks, 2021

Unsupervised Progressive Learning and the STAM Architecture.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2019
Neural Network Training With Levenberg-Marquardt and Adaptable Weight Compression.
IEEE Trans. Neural Networks Learn. Syst., 2019

DCMDS-RV: density-concentrated multi-dimensional scaling for relation visualization.
J. Vis., 2019

Unsupervised Continual Learning and Self-Taught Associative Memory Hierarchies.
CoRR, 2019

2018
Discrete Cosine Transform Spectral Pooling Layers for Convolutional Neural Networks.
Proceedings of the Artificial Intelligence and Soft Computing, 2018


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