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Found 4 papers, 1 papers with code
Bandit-Driven Batch Selection for Robust Learning under Label Noise
We introduce a novel approach for batch selection in Stochastic Gradient Descent (SGD) training, leveraging combinatorial bandit algorithms.
Empirical analysis of representation learning and exploration in neural kernel bandits
We consider policies based on a GP and a Student's t-process (TP).
Evaluating Curriculum Learning Strategies in Neural Combinatorial Optimization
Neural combinatorial optimization (NCO) aims at designing problem-independent and efficient neural network-based strategies for solving combinatorial problems.
Structure Optimization for Deep Multimodal Fusion Networks using Graph-Induced Kernels
A popular testbed for deep learning has been multimodal recognition of human activity or gesture involving diverse inputs such as video, audio, skeletal pose and depth images.
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