Deep neural decision trees
Y Yang, IG Morillo, TM Hospedales - arXiv preprint arXiv:1806.06988, 2018 - arxiv.org
… Deep Neural Decision Tree (DNDT) – and explore its connections to each. DNDTs are neural
… a specific decision tree, and is therefore interpretable1. However, as DNDT is realised by …
… a specific decision tree, and is therefore interpretable1. However, as DNDT is realised by …
Deep neural decision forests
P Kontschieder, M Fiterau… - Proceedings of the …, 2015 - openaccess.thecvf.com
… , we introduce a stochastic and differentiable decision tree model, which steers the … (deep)
convolutional network. Our model differs from conventional deep networks because a decision …
convolutional network. Our model differs from conventional deep networks because a decision …
Neural decision trees
R Balestriero - arXiv preprint arXiv:1702.07360, 2017 - arxiv.org
… a synergistic melting of neural networks and decision trees (DT) we call neural … of deep
neural networks. We now describe briefly the standard univariate and multivariate decision trees, …
neural networks. We now describe briefly the standard univariate and multivariate decision trees, …
Deep neural network initialization with decision trees
KD Humbird, JL Peterson… - … transactions on neural …, 2018 - ieeexplore.ieee.org
… Based on this observation, we propose a novel mapping from decision trees to deep neural
… weights that reflect the decision tree structure. The neural network is subsequently trained …
… weights that reflect the decision tree structure. The neural network is subsequently trained …
Currency crises prediction using deep neural decision trees
D Alaminos, R Becerra-Vicario… - Applied Sciences, 2019 - mdpi.com
… The method used was deep neural decision trees (DNDTs), a technique based on decision
trees implemented by deep learning neural networks, which was compared with other …
trees implemented by deep learning neural networks, which was compared with other …
NBDT: Neural-backed decision trees
… Alternatively, we can gain insight into the model’s decision … decisions as in rule-based
models like decision trees. However, existing efforts to fuse deep learning and decision trees …
models like decision trees. However, existing efforts to fuse deep learning and decision trees …
Distilling a neural network into a soft decision tree
N Frosst, G Hinton - arXiv preprint arXiv:1711.09784, 2017 - arxiv.org
… a deep neural network makes its decisions, we use the deep neural network to train a decision
tree that mimics the input-output function discovered by the neural network but works in a …
tree that mimics the input-output function discovered by the neural network but works in a …
Neural networks are decision trees
C Aytekin - arXiv preprint arXiv:2210.05189, 2022 - arxiv.org
… Deep neural decision forests. In Proceedings of the IEEE international conference on
computer vision, pages 1467–1475, 2015. 1 [10] Mason McGill and Pietro Perona. …
computer vision, pages 1467–1475, 2015. 1 [10] Mason McGill and Pietro Perona. …
A Survey of Neural Trees: Co-Evolving Neural Networks and Decision Trees
… [35] note that solely optimizing the leaf parameters is a convex optimization problem and
proposed a derivativefree strategy, named deep neural decision forests (DNDFs). DNDFs …
proposed a derivativefree strategy, named deep neural decision forests (DNDFs). DNDFs …
A survey of neural trees
… In the filed of DT-based interpretations, neural decision trees (NDTs) are … trees with latent
representation learned by a trained deep CNN. Their model is termed as deep neural decision …
representation learned by a trained deep CNN. Their model is termed as deep neural decision …
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