22 citations · 77 across the 18 of their papers we have counts for
18 papers
Cross-domain Cross-architecture Black-box Attacks on Fine-tuned Models with Transferred Evolutionary Strategies
Yinghua Zhang, Yangqiu Song, Kun Bai +1
Fine-tuning can be vulnerable to adversarial attacks. Existing works about black-box attacks on fine-tuned models (BAFT) are limited by strong assumptions. To fill the gap, we prop…
Uncertainty-Aware Learning Against Label Noise on Imbalanced Datasets
Yingsong Huang, Bing Bai, Shengwei Zhao +2
Learning against label noise is a vital topic to guarantee a reliable performance for deep neural networks. Recent research usually refers to dynamic noise modeling with model outp…
Contrastive Multi-view Hyperbolic Hierarchical Clustering
Fangfei Lin, Bing Bai, Kun Bai +3
Hierarchical clustering recursively partitions data at an increasingly finer granularity. In real-world applications, multi-view data have become increasingly important. This raise…
MultiFace: A Generic Training Mechanism for Boosting Face Recognition Performance
Jing Xu, Tszhang Guo, Yong Xu +2
Deep Convolutional Neural Networks (DCNNs) and their variants have been widely used in large scale face recognition(FR) recently. Existing methods have achieved good performance on…
Domain Agnostic Learning for Unbiased Authentication
Jian Liang, Yuren Cao, Shuang Li +4
Authentication is the task of confirming the matching relationship between a data instance and a given identity. Typical examples of authentication problems include face recognitio…
Reliable Evaluations for Natural Language Inference based on a Unified Cross-dataset Benchmark
Guanhua Zhang, Bing Bai, Jian Liang +3
Recent studies show that crowd-sourced Natural Language Inference (NLI) datasets may suffer from significant biases like annotation artifacts. Models utilizing these superficial cl…
Hybrid Differentially Private Federated Learning on Vertically Partitioned Data
Chang Wang, Jian Liang, Mingkai Huang +3
We present HDP-VFL, the first hybrid differentially private (DP) framework for vertical federated learning (VFL) to demonstrate that it is possible to jointly learn a generalized l…
Relation-Guided Representation Learning
Zhao Kang, Xiao Lu, Jian Liang +2
Deep auto-encoders (DAEs) have achieved great success in learning data representations via the powerful representability of neural networks. But most DAEs only focus on the most do…
Adversarial Infidelity Learning for Model Interpretation
Jian Liang, Bing Bai, Yuren Cao +2
Model interpretation is essential in data mining and knowledge discovery. It can help understand the intrinsic model working mechanism and check if the model has undesired characte…
General-Purpose User Embeddings based on Mobile App Usage
Junqi Zhang, Bing Bai, Ye Lin +3
In this paper, we report our recent practice at Tencent for user modeling based on mobile app usage. User behaviors on mobile app usage, including retention, installation, and unin…
CSRN: Collaborative Sequential Recommendation Networks for News Retrieval
Bing Bai, Guanhua Zhang, Ye Lin +3
Nowadays, news apps have taken over the popularity of paper-based media, providing a great opportunity for personalization. Recurrent Neural Network (RNN)-based sequential recommen…
Demographics Should Not Be the Reason of Toxicity: Mitigating Discrimination in Text Classifications with Instance Weighting
Guanhua Zhang, Bing Bai, Junqi Zhang +3
With the recent proliferation of the use of text classifications, researchers have found that there are certain unintended biases in text classification datasets. For example, text…
Fisher Deep Domain Adaptation
Yinghua Zhang, Yu Zhang, Ying Wei +3
Deep domain adaptation models learn a neural network in an unlabeled target domain by leveraging the knowledge from a labeled source domain. This can be achieved by learning a doma…
Mitigating Annotation Artifacts in Natural Language Inference Datasets to Improve Cross-dataset Generalization Ability
Guanhua Zhang, Bing Bai, Junqi Zhang +3
Natural language inference (NLI) aims at predicting the relationship between a given pair of premise and hypothesis. However, several works have found that there widely exists a bi…
Selection Bias Explorations and Debias Methods for Natural Language Sentence Matching Datasets
Guanhua Zhang, Bing Bai, Jian Liang +5
Natural Language Sentence Matching (NLSM) has gained substantial attention from both academics and the industry, and rich public datasets contribute a lot to this process. However,…
Additive Adversarial Learning for Unbiased Authentication
Jian Liang, Yuren Cao, Chenbin Zhang +3
Authentication is a task aiming to confirm the truth between data instances and personal identities. Typical authentication applications include face recognition, person re-identif…
Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition
Yu Pan, Jing Xu, Maolin Wang +4
Recurrent Neural Networks (RNNs) and their variants, such as Long-Short Term Memory (LSTM) networks, and Gated Recurrent Unit (GRU) networks, have achieved promising performance in…
Improving Reinforcement Learning Based Image Captioning with Natural Language Prior
Tszhang Guo, Shiyu Chang, Mo Yu +1
Recently, Reinforcement Learning (RL) approaches have demonstrated advanced performance in image captioning by directly optimizing the metric used for testing. However, this shaped…