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Found 5 papers, 0 papers with code
Reproducing Kernel Hilbert Space Pruning for Sparse Hyperspectral Abundance Prediction
Our approach is benchmarked against standard pruning and least squares as well as deep learning methods.
In What Ways Are Deep Neural Networks Invariant and How Should We Measure This?
It is often said that a deep learning model is "invariant" to some specific type of transformation.
Reward-Free Attacks in Multi-Agent Reinforcement Learning
We investigate how effective an attacker can be when it only learns from its victim's actions, without access to the victim's reward.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Argumentative Topology: Finding Loop(holes) in Logic
Advances in natural language processing have resulted in increased capabilities with respect to multiple tasks.
Gradual DropIn of Layers to Train Very Deep Neural Networks
In particular, an untrainable deep network starts as a trainable shallow network and newly added layers are slowly, organically added during training, thereby increasing the network's depth.
