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Found 5 papers, 3 papers with code
Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization
We consider the problem of multi-objective (MO) blackbox optimization using expensive function evaluations, where the goal is to approximate the true Pareto set of solutions while minimizing the number of function evaluations.
SETGAN: Scale and Energy Trade-off GANs for Image Applications on Mobile Platforms
The key idea behind SETGAN for an image generation task is for a given input image, we train a GAN on a remote server and use the trained model on edge devices.
Trading-off Accuracy and Energy of Deep Inference on Embedded Systems: A Co-Design Approach
Deep neural networks have seen tremendous success for different modalities of data including images, videos, and speech.
Effectiveness of Tree-based Ensembles for Anomaly Discovery: Insights, Batch and Streaming Active Learning
Our results show that active learning allows us to discover significantly more anomalies than state-of-the-art unsupervised baselines, our batch active learning algorithm discovers diverse anomalies, and our algorithms under the streaming-data setup are competitive with the batch setup.
Active Anomaly Detection via Ensembles
First, we present an important insight into how anomaly detector ensembles are naturally suited for active learning.
