InstructME: An Instruction Guided Music Edit And Remix Framework with Latent Diffusion Models

no code implementations • 28 Aug 2023 • Bing Han, Junyu Dai, Weituo Hao, Xinyan He, Dong Guo, Jitong Chen, Yuxuan Wang, Yanmin Qian, Xuchen Song

We tested InstructME in instrument-editing, remixing, and multi-round editing.

ALCAP: Alignment-Augmented Music Captioner

1 code implementation • 21 Dec 2022 • Zihao He, Weituo Hao, Wei-Tsung Lu, Changyou Chen, Kristina Lerman, Xuchen Song

Music captioning has gained significant attention in the wake of the rising prominence of streaming media platforms.

Contrastive Learning Music Captioning +1

Towards Fair Federated Learning with Zero-Shot Data Augmentation

no code implementations • 27 Apr 2021 • Weituo Hao, Mostafa El-Khamy, Jungwon Lee, Jianyi Zhang, Kevin J Liang, Changyou Chen, Lawrence Carin

Federated learning has emerged as an important distributed learning paradigm, where a server aggregates a global model from many client-trained models while having no access to the client data.

Data Augmentation Fairness +1

Improving Zero-shot Voice Style Transfer via Disentangled Representation Learning

1 code implementation • ICLR 2021 • Siyang Yuan, Pengyu Cheng, Ruiyi Zhang, Weituo Hao, Zhe Gan, Lawrence Carin

Voice style transfer, also called voice conversion, seeks to modify one speaker's voice to generate speech as if it came from another (target) speaker.

Representation Learning Style Transfer +1

FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders

no code implementations • ICLR 2021 • Pengyu Cheng, Weituo Hao, Siyang Yuan, Shijing Si, Lawrence Carin

Pretrained text encoders, such as BERT, have been applied increasingly in various natural language processing (NLP) tasks, and have recently demonstrated significant performance gains.

Contrastive Learning Fairness +1

FLOP: Federated Learning on Medical Datasets using Partial Networks

no code implementations • 10 Feb 2021 • Qian Yang, Jianyi Zhang, Weituo Hao, Gregory Spell, Lawrence Carin

While different data-driven deep learning models have been developed to mitigate the diagnosis of COVID-19, the data itself is still scarce due to patient privacy concerns.

Federated Learning

MixKD: Towards Efficient Distillation of Large-scale Language Models

no code implementations • ICLR 2021 • Kevin J Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin

Large-scale language models have recently demonstrated impressive empirical performance.

Data Augmentation Knowledge Distillation

WAFFLe: Weight Anonymized Factorization for Federated Learning

no code implementations • 13 Aug 2020 • Weituo Hao, Nikhil Mehta, Kevin J Liang, Pengyu Cheng, Mostafa El-Khamy, Lawrence Carin

Experiments on MNIST, FashionMNIST, and CIFAR-10 demonstrate WAFFLe's significant improvement to local test performance and fairness while simultaneously providing an extra layer of security.

Fairness Federated Learning

CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information

2 code implementations • ICML 2020 • Pengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan, Lawrence Carin

In this paper, we propose a novel Contrastive Log-ratio Upper Bound (CLUB) of mutual information.

Domain Adaptation

Towards Learning a Generic Agent for Vision-and-Language Navigation via Pre-training

1 code implementation • CVPR 2020 • Weituo Hao, Chunyuan Li, Xiujun Li, Lawrence Carin, Jianfeng Gao

By training on a large amount of image-text-action triplets in a self-supervised learning manner, the pre-trained model provides generic representations of visual environments and language instructions.

Navigate Self-Supervised Learning +2

Adaptive Power System Emergency Control using Deep Reinforcement Learning

1 code implementation • 9 Mar 2019 • Qiuhua Huang, Renke Huang, Weituo Hao, Jie Tan, Rui Fan, Zhenyu Huang

Power system emergency control is generally regarded as the last safety net for grid security and resiliency.

Benchmarking reinforcement-learning +1