James Seale Smith
James Seale Smith
Samsung Research America
Verified email at - Homepage
Cited by
Cited by
Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning
J Smith, YC Hsu, J Balloch, Y Shen, H Jin, Z Kira
International Conference on Computer Vision (ICCV), 2021
CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual Learning
JS Smith, L Karlinsky, V Gutta, P Cascante-Bonilla, D Kim, A Arbelle, ...
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Neural network training with Levenberg–Marquardt and adaptable weight compression
JS Smith, B Wu, BM Wilamowski
IEEE transactions on neural networks and learning systems 30 (2), 580-587, 2018
Continual diffusion: Continual customization of text-to-image diffusion with c-lora
JS Smith, YC Hsu, L Zhang, T Hua, Z Kira, Y Shen, H Jin
Transactions on Machine Learning Research, 2024
Unsupervised progressive learning and the stam architecture
J Smith, C Taylor, S Baer, C Dovrolis
International Joint Conference on Artificial Intelligence (IJCAI), 2019
A closer look at rehearsal-free continual learning
JS Smith, J Tian, YC Hsu, Z Kira
CVPR Workshop on Continual Learning in Computer Vision, 2023
Memory-Efficient Semi-Supervised Continual Learning: The World is its Own Replay Buffer
J Smith, J Balloch, YC Hsu, Z Kira
International Joint Conference on Neural Networks (IJCNN), 2021
Thin-wire antenna design using a novel branching scheme and genetic algorithm optimization
JS Smith, ME Baginski
IEEE Transactions on Antennas and Propagation 67 (5), 2934-2941, 2019
Going beyond nouns with vision & language models using synthetic data
P Cascante-Bonilla, K Shehada, JS Smith, S Doveh, D Kim, R Panda, ...
International Conference on Computer Vision (ICCV), 2023
Discrete cosine transform spectral pooling layers for convolutional neural networks
JS Smith, BM Wilamowski
International Conference on Artificial Intelligence and Soft Computing, 235-246, 2018
ConStruct-VL: Data-Free Continual Structured VL Concepts Learning
JS Smith, P Cascante-Bonilla, A Arbelle, D Kim, R Panda, D Cox, D Yang, ...
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
A closer look at knowledge distillation with features, logits, and gradients
YC Hsu, J Smith, Y Shen, Z Kira, H Jin
arXiv preprint arXiv:2203.10163, 2022
HePCo: Data-Free Heterogeneous Prompt Consolidation for Continual Federated Learning
S Halbe, JS Smith, J Tian, Z Kira
NeurIPS Workshop, 2023
Continual causality: A retrospective of the inaugural aaai-23 bridge program
M Mundt, KW Cooper, DS Dhami, A Ribeiro, JS Smith, A Bellot, T Hayes
AAAI Bridge Program on Continual Causality, 1-10, 2023
Incremental Learning with Differentiable Architecture and Forgetting Search
JS Smith, Z Seymour, HP Chiu
International Joint Conference on Neural Networks (IJCNN), 2022
Fast Trainable Projection for Robust Fine-Tuning
J Tian, YC Liu, JS Smith, Z Kira
Neural Information Processing Systems (NeurIPS), 2023
System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games
I Sur, Z Daniels, A Rahman, K Faber, GJ Gallardo, TL Hayes, CE Taylor, ...
International Conference on AIML Systems, 2022
Lifelong Wandering: A realistic few-shot online continual learning setting
M Lunayach, J Smith, Z Kira
CVPR Workshop on Continual Learning in Computer Vision, 2022
DCMDS-RV: density-concentrated multi-dimensional scaling for relation visualization
B Wu, JS Smith, BM Wilamowski, RM Nelms
Journal of Visualization 22, 341-357, 2019
Continual Diffusion with STAMINA: STack-And-Mask INcremental Adapters
JS Smith, YC Hsu, Z Kira, Y Shen, H Jin
CVPR Workshop, 2024
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