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08/28/2023
Continual Learning with Dynamic Sparse Training: Exploring Algorithms for Effective Model Updates
Continual learning (CL) refers to the ability of an intelligent system t...
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02/24/2023
The Dormant Neuron Phenomenon in Deep Reinforcement Learning
In this work we identify the dormant neuron phenomenon in deep reinforce...
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02/13/2023
Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning
Tomorrow's robots will need to distinguish useful information from noise...
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11/26/2022
Where to Pay Attention in Sparse Training for Feature Selection?
A new line of research for feature selection based on neural networks ha...
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10/11/2021
Addressing the Stability-Plasticity Dilemma via Knowledge-Aware Continual Learning
Continual learning agents should incrementally learn a sequence of tasks...
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06/28/2021
FreeTickets: Accurate, Robust and Efficient Deep Ensemble by Training with Dynamic Sparsity
Recent works on sparse neural networks have demonstrated that it is poss...
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06/08/2021
Dynamic Sparse Training for Deep Reinforcement Learning
Deep reinforcement learning has achieved significant success in many dec...
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01/28/2021
Self-Attention Meta-Learner for Continual Learning
Continual learning aims to provide intelligent agents capable of learnin...
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01/15/2021
Learning Invariant Representation for Continual Learning
Continual learning aims to provide intelligent agents that are capable o...
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12/01/2020
Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for Autoencoders
Major complications arise from the recent increase in the amount of high...
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07/15/2020
SpaceNet: Make Free Space For Continual Learning
The continual learning (CL) paradigm aims to enable neural networks to l...
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06/24/2020
