Scalable continual deep learning with computational cost considerations

Scalable continual deep learning with computational cost considerations

<p>Continual Learning (CL) is a emerging field that focuses on developing models capable of learning continuously from a incoming stream of data, as opposed to hundreds of passes over static, curated datasets. These models aim to retain previously acquired knowledge while seamlessly integrati...

وصف كامل

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Prabhu, AP
مؤلفون آخرون:	Torr, P
التنسيق:	أطروحة
اللغة:	English
منشور في:	2025
الموضوعات:	Deep learning (Machine learning)

مواد مشابهة

High performance deep learning on resource constrained platforms
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Structure and uncertainty in deep learning
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منشور في: (2022)

Deep Reinforcement Learning in complex environments
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منشور في: (2021)

Deep learning algorithms for predicting association between antibody sequence, structure, and antibody properties
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Robustness, structure and hierarchy in deep generative models
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On kernel and feature learning in neural networks
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Learning with partial labels: an exploratory study of data scarcity for medical images
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Deep vision for indoor understanding and localisation
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Deep Antimicrobial Susceptibility Phenotyping (DASP) Training and Evaluation Dataset, and Trained Models.
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Toward efficient deep learning with sparse neural networks
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Deep learning approach with image noise reduction to determine planting density and defected paddy seedlings
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Efficient and scalable methods for deep reinforcement learning
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Generation of 12-lead patient-specific electrocardiogram and risk prediction of cardiovascular disease using deep learning
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Non-parametric deep learning with applications in active learning
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Measuring Laser Beams with a Neural Network (Data)
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Neural networks as data
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Understanding Gaussian noise injections in neural networks
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Counting with limited supervision
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Efficient neural network verification and training
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Generative modelling on constrained manifolds
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Sign language understanding using multimodal learning
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Quantification of fetal brain development from ultrasound images using interpretable deep learning
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End-to-end learning, and audio-visual human-centric video understanding
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Deep learning-based construction activity classification
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Learning and inference over relational data
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Geometry and representation learning in deep generative models
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Deep learning for causal inference on electronic health records
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A minimalist approach to deep multi-task learning
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Spectral machine learning
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