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Found 11 papers, 6 papers with code
Strategic Decisions Survey, Taxonomy, and Future Directions from Artificial Intelligence Perspective
Strategic Decision-Making is always challenging because it is inherently uncertain, ambiguous, risky, and complex.
Thermal Prediction for Efficient Energy Management of Clouds using Machine Learning
Specifically, we propose a gradient boosting machine learning model for temperature prediction.
Learning Non-Unique Segmentation with Reward-Penalty Dice Loss
Semantic segmentation is one of the key problems in the field of computer vision, as it enables computer image understanding.
Segmented Pairwise Distance for Time Series with Large Discontinuities
Time series with large discontinuities are common in many scenarios.
Databases
Dynamic Scheduling for Stochastic Edge-Cloud Computing Environments using A3C learning and Residual Recurrent Neural Networks
The ubiquitous adoption of Internet-of-Things (IoT) based applications has resulted in the emergence of the Fog computing paradigm, which allows seamlessly harnessing both mobile-edge and cloud resources.
MurTree: Optimal Classification Trees via Dynamic Programming and Search
Heuristic methods are traditionally used to quickly produce models with reasonably high accuracy.
Generative Image Inpainting with Submanifold Alignment
Image inpainting aims at restoring missing regions of corrupted images, which has many applications such as image restoration and object removal.
A Jointly Learned Context-Aware Place of Interest Embedding for Trip Recommendations
We propose two trip recommendation algorithms based on our context-aware POI embedding.
Learning with Bounded Instance- and Label-dependent Label Noise
Inspired by the idea of learning with distilled examples, we then propose a learning algorithm with theoretical guarantees for its robustness to BILN.
Tensor Canonical Correlation Analysis for Multi-view Dimension Reduction
As a consequence, the high order correlation information contained in the different views is explored and thus a more reliable common subspace shared by all features can be obtained.
