141 citations · 597 across the 22 of their papers we have counts for
5 papers · 1 filter
Linear TreeShap
Peng Yu, Chao Xu, Albert Bifet +1
Decision trees are well-known due to their ease of interpretability. To improve accuracy, we need to grow deep trees or ensembles of trees. These are hard to interpret, offsetting…
Conv-NILM-Net, a causal and multi-appliance model for energy source separation
Simo Alami C., Jérémie Decock, Rim Kaddah +1
Non-Intrusive Load Monitoring (NILM) seeks to save energy by estimating individual appliance power usage from a single aggregate measurement. Deep neural networks have become incre…
On Merging Feature Engineering and Deep Learning for Diagnosis, Risk-Prediction and Age Estimation Based on the 12-Lead ECG
Eran Zvuloni, Jesse Read, Antônio H. Ribeiro +2
Objective: Machine learning techniques have been used extensively for 12-lead electrocardiogram (ECG) analysis. For physiological time series, deep learning (DL) superiority to fea…
CAMEO: Curiosity Augmented Metropolis for Exploratory Optimal Policies
Simo Alami. C, Fernando Llorente, Rim Kaddah +2
Reinforcement Learning has drawn huge interest as a tool for solving optimal control problems. Solving a given problem (task or environment) involves converging towards an optimal…
Optimality in Noisy Importance Sampling
Fernando Llorente, Luca Martino, Jesse Read +1
In this work, we analyze the noisy importance sampling (IS), i.e., IS working with noisy evaluations of the target density. We present the general framework and derive optimal prop…