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Found 6 papers, 2 papers with code
One-Step Forward and Backtrack: Overcoming Zig-Zagging in Loss-Aware Quantization Training
During the gradient descent learning, a one-step forward search is designed to find the trial gradient of the next-step, which is adopted to adjust the gradient of current step towards the direction of fast convergence.
Survey on Evolutionary Deep Learning: Principles, Algorithms, Applications and Open Issues
Specifically, we firstly illuminate EDL from machine learning and EC and regard EDL as an optimization problem.
Towards Fairness-Aware Multi-Objective Optimization
Recent years have seen the rapid development of fairness-aware machine learning in mitigating unfairness or discrimination in decision-making in a wide range of applications.
Pareto-wise Ranking Classifier for Multi-objective Evolutionary Neural Architecture Search
In the deployment of deep neural models, how to effectively and automatically find feasible deep models under diverse design objectives is fundamental.
Effective Cascade Dual-Decoder Model for Joint Entity and Relation Extraction
The popular way of existing methods is to jointly extract entities and relations using a single model, which often suffers from the overlapping triple problem.
Composing Knowledge Graph Embeddings via Word Embeddings
As $(\mathbf{h},\mathbf{r},\mathbf{t})$ is learned from the existing facts within a knowledge graph, these representations can not be used to detect unknown facts (if the entities or relations never occur in the knowledge graph).
