Multi-Armed Bandit Algorithms Improve Structured Pruning of Neural Networks
Researchers developed a structured pruning framework that uses multi-armed bandit (MAB) algorithms to remove entire neurons from deep neural networks, treating each neuron as a decision arm to evaluate. The method tests various MAB policies including UCB1, Thompson Sampling, and Epsilon-Greedy across tabular and deep learning tasks. Results show MAB-based pruning significantly outperforms unpruned models and traditional magnitude-based pruning approaches.
The paper presents a novel approach to neural network compression by applying multi-armed bandit algorithms to structured neuron pruning. Rather than removing individual weights (unstructured sparsity), the framework removes complete neurons, which is more compatible with standard hardware implementations. The method works by treating each candidate neuron as an arm in a bandit problem: temporarily masking a neuron, measuring the resulting loss change on a mini-batch, and updating a reward estimate for safe removal. The researchers evaluated multiple MAB policies—including stochastic approaches (Epsilon-Greedy, Softmax, UCB1, Thompson Sampling) and multiplicative-weight methods (Hedge, EXP3)—across diverse benchmarks spanning tabular classification, tabular regression, and deep learning tasks covering images, text, and reasoning. Statistical analysis using Friedman and Nemenyi tests revealed that UCB1 and Thompson Sampling achieved the strongest performance ranks on deep learning tasks, with several MAB policies significantly outperforming both unpruned baselines and existing pruning methods.
What's missing
The study does not discuss computational overhead of the MAB-based pruning process itself compared to simpler magnitude-based methods, wall-clock training time comparisons, or scalability to very large models (e.g., billion-parameter networks). The paper also does not address how the method performs under different hardware constraints or provide guidance on hyperparameter selection for the various MAB policies.
What different sources said
- arXiv cs.AICenter
Structured Neuron Pruning in Deep Neural Networks Using Multi-Armed Bandits
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