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20172023
most citedFairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders

51 citations · 137 across the 26 of their papers we have counts for

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Showing 2022Show all

16 papers · 1 filter

cs.IR2022★ 1 cited

Efficient Document Retrieval by End-to-End Refining and Quantizing BERT Embedding with Contrastive Product Quantization

Zexuan Qiu, Qinliang Su, Jianxing Yu +1

Efficient document retrieval heavily relies on the technique of semantic hashing, which learns a binary code for every document and employs Hamming distance to evaluate document di…

cs.CV2022

Pushing the Efficiency Limit Using Structured Sparse Convolutions

Vinay Kumar Verma, Nikhil Mehta, Shijing Si +2

Weight pruning is among the most popular approaches for compressing deep convolutional neural networks. Recent work suggests that in a randomly initialized deep neural network, the…

cs.CV2022★ 1 cited

Pose Guided Human Image Synthesis with Partially Decoupled GAN

Jianhan Wu, Jianzong Wang, Shijing Si +2

Pose Guided Human Image Synthesis (PGHIS) is a challenging task of transforming a human image from the reference pose to a target pose while preserving its style. Most existing met…

cs.LG2022

Machine Unlearning Method Based On Projection Residual

Zihao Cao, Jianzong Wang, Shijing Si +2

Machine learning models (mainly neural networks) are used more and more in real life. Users feed their data to the model for training. But these processes are often one-way. Once t…

cs.LG2022

RL-MD: A Novel Reinforcement Learning Approach for DNA Motif Discovery

Wen Wang, Jianzong Wang, Shijing Si +2

The extraction of sequence patterns from a collection of functionally linked unlabeled DNA sequences is known as DNA motif discovery, and it is a key task in computational biology.…

eess.AS2022

Boosting Star-GANs for Voice Conversion with Contrastive Discriminator

Shijing Si, Jianzong Wang, Xulong Zhang +3

Nonparallel multi-domain voice conversion methods such as the StarGAN-VCs have been widely applied in many scenarios. However, the training of these models usually poses a challeng…

cs.IR2022

Debias the Black-box: A Fair Ranking Framework via Knowledge Distillation

Zhitao Zhu, Shijing Si, Jianzong Wang +2

Deep neural networks can capture the intricate interaction history information between queries and documents, because of their many complicated nonlinear units, allowing them to pr…

cs.SD2022

Uncertainty Calibration for Deep Audio Classifiers

Tong Ye, Shijing Si, Jianzong Wang +2

Although deep Neural Networks (DNNs) have achieved tremendous success in audio classification tasks, their uncertainty calibration are still under-explored. A well-calibrated model…

cs.SE2022★ 1 cited

Leveraging Causal Inference for Explainable Automatic Program Repair

Jianzong Wang, Shijing Si, Zhitao Zhu +3

Deep learning models have made significant progress in automatic program repair. However, the black-box nature of these methods has restricted their practical applications. To addr…

cs.LG2022

A Fair Federated Learning Framework With Reinforcement Learning

Yaqi Sun, Shijing Si, Jianzong Wang +3

Federated learning (FL) is a paradigm where many clients collaboratively train a model under the coordination of a central server, while keeping the training data locally stored. H…

cs.CL2022★ 1 cited

Federated Non-negative Matrix Factorization for Short Texts Topic Modeling with Mutual Information

Shijing Si, Jianzong Wang, Ruiyi Zhang +2

Non-negative matrix factorization (NMF) based topic modeling is widely used in natural language processing (NLP) to uncover hidden topics of short text documents. Usually, training…

cs.IR2022

Cali3F: Calibrated Fast Fair Federated Recommendation System

Zhitao Zhu, Shijing Si, Jianzong Wang +1

The increasingly stringent regulations on privacy protection have sparked interest in federated learning. As a distributed machine learning framework, it bridges isolated data isla…

cs.LG2022

Augmentation-induced Consistency Regularization for Classification

Jianhan Wu, Shijing Si, Jianzong Wang +1

Deep neural networks have become popular in many supervised learning tasks, but they may suffer from overfitting when the training dataset is limited. To mitigate this, many resear…

cs.CV2022

Improving Human Image Synthesis with Residual Fast Fourier Transformation and Wasserstein Distance

Jianhan Wu, Shijing Si, Jianzong Wang +1

With the rapid development of the Metaverse, virtual humans have emerged, and human image synthesis and editing techniques, such as pose transfer, have recently become popular. Mos…

cs.SD2022

Towards Speaker Age Estimation with Label Distribution Learning

Shijing Si, Jianzong Wang, Junqing Peng +1

Existing methods for speaker age estimation usually treat it as a multi-class classification or a regression problem. However, precise age identification remains a challenge due to…

cs.CL2022

VU-BERT: A Unified framework for Visual Dialog

Tong Ye, Shijing Si, Jianzong Wang +3

The visual dialog task attempts to train an agent to answer multi-turn questions given an image, which requires the deep understanding of interactions between the image and dialog…