James Seale Smith

According to our database, James Seale Smith authored at least 28 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Lifelong Machine Learning without Lifelong Data Retention.

James Seale Smith

PhD thesis, 2024

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

James Seale Smith, Yen-Chang Hsu, Lingyu Zhang, Ting Hua, Zsolt Kira, Yilin Shen, Hongxia Jin

Trans. Mach. Learn. Res., 2024

MoDeGPT: Modular Decomposition for Large Language Model Compression.

Chi-Heng Lin, Shangqian Gao, James Seale Smith, Abhishek Patel, Shikhar Tuli, Yilin Shen, Hongxia Jin, Yen-Chang Hsu

CoRR, 2024

SLiM: Speculative Decoding with Hypothesis Reduction.

Chi-Heng Lin, Shikhar Tuli, James Seale Smith, Yen-Chang Hsu, Yilin Shen, Hongxia Jin

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

Adaptive Memory Replay for Continual Learning.

James Seale Smith, Lazar Valkov, Shaunak Halbe, Vyshnavi Gutta, Rogério Feris, Zsolt Kira, Leonid Karlinsky

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

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

James Seale Smith, Yen-Chang Hsu, Zsolt Kira, Yilin Shen, Hongxia Jin

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

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

Shaunak Halbe, James Seale Smith, Junjiao Tian, Zsolt Kira

CoRR, 2023

Fast Trainable Projection for Robust Fine-tuning.

Junjiao Tian, Yen-Cheng Liu, James Seale Smith, Zsolt Kira

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.

Paola Cascante-Bonilla, Khaled Shehada, James Seale Smith, Sivan Doveh, Donghyun Kim, Rameswar Panda, Gül Varol, Aude Oliva, Vicente Ordonez, Rogério Feris, Leonid Karlinsky

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

A Closer Look at Rehearsal-Free Continual Learning.

James Seale Smith, Junjiao Tian, Shaunak Halbe, Yen-Chang Hsu, Zsolt Kira

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.

James Seale Smith, Leonid Karlinsky, Vyshnavi Gutta, Paola Cascante-Bonilla, Donghyun Kim, Assaf Arbelle, Rameswar Panda, Rogério Feris, Zsolt Kira

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

ConStruct-VL: Data-Free Continual Structured VL Concepts Learning.

James Seale Smith, Paola Cascante-Bonilla, Assaf Arbelle, Donghyun Kim, Rameswar Panda, David D. Cox, Diyi Yang, Zsolt Kira, Rogério Feris, Leonid Karlinsky

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Continual Causality: A Retrospective of the Inaugural AAAI-23 Bridge Program.

Martin Mundt, Keiland W. Cooper, Devendra Singh Dhami, Adèle H. Ribeiro, James Seale Smith, Alexis Bellot, Tyler L. Hayes

Proceedings of the AAAI Bridge Program on Continual Causality, 2023

2022

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

Paola Cascante-Bonilla, Leonid Karlinsky, James Seale Smith, Yanjun Qi, Vicente Ordonez

CoRR, 2022

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

Junjiao Tian, James Seale Smith, Zsolt Kira

CoRR, 2022

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

Mayank Lunayach, James Seale Smith, Zsolt Kira

CoRR, 2022

A Closer Look at Rehearsal-Free Continual Learning.

James Seale Smith, Junjiao Tian, Yen-Chang Hsu, Zsolt Kira

CoRR, 2022

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

Yen-Chang Hsu, James Seale Smith, Yilin Shen, Zsolt Kira, Hongxia Jin

CoRR, 2022

Incremental Learning with Differentiable Architecture and Forgetting Search.

James Seale Smith, Zachary Seymour, Han-Pang Chiu

Proceedings of the International Joint Conference on Neural Networks, 2022

Model-Free Generative Replay for Lifelong Reinforcement Learning: Application to Starcraft-2.

Zachary Alan Daniels, Aswin Raghavan, Jesse Hostetler, Abrar Rahman, Indranil Sur, Michael R. Piacentino, Ajay Divakaran, Roberto Corizzo, Kamil Faber, Nathalie Japkowicz, Michael Baron, James Seale Smith, Sahana Pramod Joshi, Zsolt Kira, Cameron Ethan Taylor, Mustafa Burak Gurbuz, Constantine Dovrolis, Tyler L. Hayes, Christopher Kanan, Jhair Gallardo

Proceedings of the Conference on Lifelong Learning Agents, 2022

System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games.

Indranil Sur, Zachary Daniels, Abrar Rahman, Kamil Faber, Gianmarco J. Gallardo, Tyler L. Hayes, Cameron E. Taylor, Mustafa Burak Gurbuz, James Seale Smith, Sahana Pramod Joshi, Nathalie Japkowicz, Michael Baron, Zsolt Kira, Christopher Kanan, Roberto Corizzo, Ajay Divakaran, Michael R. Piacentino, Jesse Hostetler, Aswin Raghavan

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.

James Seale Smith, Jonathan Balloch, Yen-Chang Hsu, Zsolt Kira

Proceedings of the International Joint Conference on Neural Networks, 2021

Unsupervised Progressive Learning and the STAM Architecture.

James Seale Smith, Cameron E. Taylor, Seth Baer, Constantine Dovrolis

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning.

James Seale Smith, Yen-Chang Hsu, Jonathan Balloch, Yilin Shen, Hongxia Jin, Zsolt Kira

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2019

Neural Network Training With Levenberg-Marquardt and Adaptable Weight Compression.

James Seale Smith, Bo Wu, Bogdan M. Wilamowski

IEEE Trans. Neural Networks Learn. Syst., 2019

DCMDS-RV: density-concentrated multi-dimensional scaling for relation visualization.

Bo Wu, James Seale Smith, Bogdan M. Wilamowski, R. M. Nelms

J. Vis., 2019

Unsupervised Continual Learning and Self-Taught Associative Memory Hierarchies.

James Seale Smith, Seth Baer, Zsolt Kira, Constantine Dovrolis

CoRR, 2019

2018

Discrete Cosine Transform Spectral Pooling Layers for Convolutional Neural Networks.

James Seale Smith, Bogdan M. Wilamowski

Proceedings of the Artificial Intelligence and Soft Computing, 2018