Bartlomiej Twardowski

Orcid: 0000-0003-2117-8679

According to our database1, Bartlomiej Twardowski authored at least 36 papers between 2012 and 2024.

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

Timeline

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PhD thesis 
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Bibliography

2024
Accelerated Inference and Reduced Forgetting: The Dual Benefits of Early-Exit Networks in Continual Learning.
CoRR, 2024

GUIDE: Guidance-based Incremental Learning with Diffusion Models.
CoRR, 2024

Divide and not forget: Ensemble of selectively trained experts in Continual Learning.
CoRR, 2024

Looking Through the Past: Better Knowledge Retention for Generative Replay in Continual Learning.
IEEE Access, 2024

Plasticity-Optimized Complementary Networks for Unsupervised Continual Learning.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023
Class-Incremental Learning: Survey and Performance Evaluation on Image Classification.
IEEE Trans. Pattern Anal. Mach. Intell., May, 2023

Revisiting Supervision for Continual Representation Learning.
CoRR, 2023

Technical Report for ICCV 2023 Visual Continual Learning Challenge: Continuous Test-time Adaptation for Semantic Segmentation.
CoRR, 2023

Bayesian Flow Networks in Continual Learning.
CoRR, 2023

FedFNN: Faster Training Convergence Through Update Predictions in Federated Recommender Systems.
CoRR, 2023

Generalized Continual Category Discovery.
CoRR, 2023

MM-GEF: Multi-modal representation meet collaborative filtering.
CoRR, 2023

Augmentation-aware Self-supervised Learning with Guided Projector.
CoRR, 2023

FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Planckian Jitter: countering the color-crippling effects of color jitter on self-supervised training.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Looking through the past: better knowledge retention for generative replay in continual learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

ICICLE: Interpretable Class Incremental Continual Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Exploiting Graph Structured Cross-Domain Representation for Multi-domain Recommendation.
Proceedings of the Advances in Information Retrieval, 2023

2022
Online Meta-Learning for Model Update Aggregation in Federated Learning for Click-Through Rate Prediction.
CoRR, 2022

Planckian jitter: enhancing the color quality of self-supervised visual representations.
CoRR, 2022

Continually Learning Self-Supervised Representations with Projected Functional Regularization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021
On the importance of cross-task features for class-incremental learning.
CoRR, 2021

Reducing Label Effort: Self-Supervised meets Active Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

Metric Learning for Session-Based Recommendations.
Proceedings of the Advances in Information Retrieval, 2021

2020
Class-incremental learning: survey and performance evaluation.
CoRR, 2020

On Class Orderings for Incremental Learning.
CoRR, 2020

RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Orderless Recurrent Models for Multi-Label Classification.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Semantic Drift Compensation for Class-Incremental Learning.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Deep Learning Optimization Tasks and Metaheuristic Methods.
Fundam. Informaticae, 2019

2016
Modelling Contextual Information in Session-Aware Recommender Systems with Neural Networks.
Proceedings of the 10th ACM Conference on Recommender Systems, 2016

2015
IoT and Context-Aware Mobile Recommendations Using Multi-agent Systems.
Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2015

2014
Multi-agent Architecture for Real-Time Big Data Processing.
Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), Warsaw, Poland, August 11-14, 2014, 2014

2012
Domain Dependent Product Feature and Opinion Extraction Based on E-Commerce Websites.
Proceedings of the Multimedia and Internet Systems: Theory and Practice, 2012


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