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Found 7 papers, 1 papers with code
Qd-tree: Learning Data Layouts for Big Data Analytics
For a given workload, however, such techniques are unable to optimize for the important metric of the number of blocks accessed by a query.
Continuous Motion Planning with Temporal Logic Specifications using Deep Neural Networks
A na\"ive way of solving a motion planning problem with LTL specifications using reinforcement learning is to sample a trajectory and then assign a high reward for training if the trajectory satisfies the entire LTL formula.
ALEX: An Updatable Adaptive Learned Index
The original work by Kraska et al. shows that a learned index beats a B+Tree by a factor of up to three in search time and by an order of magnitude in memory footprint.
PANDA: AdaPtive Noisy Data Augmentation for Regularization of Undirected Graphical Models
We propose an AdaPtive Noise Augmentation (PANDA) technique to regularize the estimation and construction of undirected graphical models.
Distinguishing Unitary Gates on the IBM Quantum Processor
We program these two schemes on the \emph{ibmqx4}, a $5$-qubit superconducting quantum processor via IBM cloud, with the help of the $QSI$ modules [S. Liu et al.,~arXiv:1710. 09500, 2017].
Quantum Physics
Learning Image Conditioned Label Space for Multilabel Classification
This work addresses the task of multilabel image classification.
Whiteout: Gaussian Adaptive Noise Regularization in Deep Neural Networks
Noise injection (NI) is an efficient technique to mitigate over-fitting in neural networks (NNs).
