GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent — mentioned by sitkack

Sat, 22 Jun 2024 06:10:48 GMT

There is some work to convert NNs to decision trees. https://towardsdatascience.com/neural-networks-as-decision-t... https://arxiv.org/abs/2210.05189 I haven't reviewed any of it, I only know of it tangentially. https://www.semanticscholar.org/paper/Converting-A-Trained-N... Distilling a Neural Network Into a Soft Decision Tree https://arxiv.org/abs/1711.09784 GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent https://arxiv.org/abs/2305.03515

Paper and discussion history. A mention is not an endorsement.

GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent — mentioned by cgreerrun

Sun, 05 Nov 2023 16:51:38 GMT

You can use the straight through operator! During the forward pass you sample a discrete outcome given your NN weights to get an error for backprop. During the backward pass you directly propogate through the weights. This GradTree paper[1] does a good job covering how to do discrete gradient-based optimization (i.e. NNs w/ discrete representations). Another option is to use a GFlowNet[2]. Then you have a NN policy that takes discrete actions like you're playing an RL game. You're not back-propogating through something that isn't continuous, but you're utilizing a NN to make informed…

Paper and discussion history. A mention is not an endorsement.

GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent · HackerPapers discussions

GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent — mentioned by sitkack

GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent — mentioned by cgreerrun