Search Results for author: Hui Song

Found 9 papers, 2 papers with code

RuDi: Explaining Behavior Sequence Models by Automatic Statistics Generation and Rule Distillation

1 code implementation12 Aug 2022 Yao Zhang, Yun Xiong, Yiheng Sun, Caihua Shan, Tian Lu, Hui Song, Yangyong Zhu

We propose a two-stage method, RuDi, that distills the knowledge of black-box teacher models into rule-based student models.

Fairness

Multi-task Optimization Based Co-training for Electricity Consumption Prediction

no code implementations31 May 2022 Hui Song, A. K. Qin, Chenggang Yan

The performance of MTO-CT is evaluated on solving each of these two sets of tasks in comparison to solving each task in the set independently without knowledge sharing under the same settings, which demonstrates the superiority of MTO-CT in terms of prediction accuracy.

Transfer Learning

Evolutionary Ensemble Learning for Multivariate Time Series Prediction

no code implementations22 Aug 2021 Hui Song, A. K. Qin, Flora D. Salim

In this framework, a specific pipeline is encoded as a candidate solution and a multi-objective evolutionary algorithm is applied under different population sizes to produce multiple Pareto optimal sets (POSs).

Ensemble Learning Time Series Prediction

Multi-objective Scheduling of Electric Vehicle Charging/Discharging with Time of Use Tariff

no code implementations11 Aug 2021 Hui Song, Chen Liu, Mahdi Jalili, Xinghuo Yu, Peter McTaggart

Optimal coordinated charging is a multi-objective optimization problem (MOOP) in nature, with objective functions such as minimum price charging and minimum disruptions to the grid.

Deep Multi-task Network for Delay Estimation and Echo Cancellation

no code implementations4 Nov 2020 Yi Zhang, Chengyun Deng, Shiqian Ma, Yongtao Sha, Hui Song

In this paper, a multi-task network is proposed to address both ref-delay estimation and echo cancellation tasks.

Acoustic echo cancellation Data Augmentation

Robust Speaker Extraction Network Based on Iterative Refined Adaptation

no code implementations4 Nov 2020 Chengyun Deng, Shiqian Ma, Yi Zhang, Yongtao Sha, HUI ZHANG, Hui Song, Xiangang Li

dataset confirm the superior performance of the proposed method over the network without IRA in terms of SI-SDR and PESQ improvement.

On Loss Functions and Recurrency Training for GAN-based Speech Enhancement Systems

no code implementations29 Jul 2020 Zhuohuang Zhang, Chengyun Deng, Yi Shen, Donald S. Williamson, Yongtao Sha, Yi Zhang, Hui Song, Xiangang Li

Recent work has shown that it is feasible to use generative adversarial networks (GANs) for speech enhancement, however, these approaches have not been compared to state-of-the-art (SOTA) non GAN-based approaches.

Audio and Speech Processing Sound

Cannot find the paper you are looking for? You can Submit a new open access paper.