Neuroscientists Discover a Hidden Brain Circuit That Shapes Every Decision
Your brain constantly juggles sensory information to make split-second decisions, but how? A new latent circuit model ...
IEEE19d
A Decision-Making Algorithm of Multiple Reactive Tasks for Autonomous Driving Sweepers Based on Behavior Trees
Consequently, in this article, a novel decision-making method designed to meet the demands of multiple reactive tasks is proposed to serve autonomous driving sweepers. Smart nodes (smart sequence and ...
GitHub23d
GBDT-MO: Gradient Boosted Decision Tree for Multiple Outputs
Gradient boosted decision tree (GBDT) is a popular machine learning algorithm. Current open-sourced GBDT implementations are mainly designed for single output. When there are multiple outputs, they ...
IEEE25d
On the Adversarial Robustness of Decision Trees and a Symmetry Defense
Abstract: Gradient-boosting decision tree classifiers (GBDTs) are susceptible to adversarial perturbation attacks that change inputs slightly to cause misclassification. GBDTs are customarily used on ...
www.cs.utexas.edu28d
On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search
In this paper, we focus on how values are backpropagated in the MCTS tree, and apply complex return strategies from the Reinforcement Learning (RL) literature to MCTS, producing 4 new MCTS variants.
Medicine Buffalo2mon
PowerPoint Slideshows
Streamline your presentation slideshow—and keep it consistent with the UB brand guidelines—by starting with one of our PowerPoint templates. Looking to include general information on some of the ...
GitHub1y
STreeD: Separable Trees with Dynamic programming
STreeD is a framework for optimal binary decision trees with separable optimization tasks ... Some optimization tasks specify their custom tuning method, such as cost-complex-accuracy which tunes the ...