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Hongliang Fei
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2020 – today
- 2024
- [c46]Xin Yuan, Hongliang Fei, Jinoo Baek:
Efficient Transformer Adaptation with Soft Token Merging. CVPR Workshops 2024: 3658-3668 - [c45]Xin Yuan, Jinoo Baek, Keyang Xu, Omer Tov, Hongliang Fei:
Inflation with Diffusion: Efficient Temporal Adaptation for Text-to-Video Super-Resolution. WACV (Workshops) 2024: 489-496 - [i8]Xin Yuan, Jinoo Baek, Keyang Xu, Omer Tov, Hongliang Fei:
Inflation with Diffusion: Efficient Temporal Adaptation for Text-to-Video Super-Resolution. CoRR abs/2401.10404 (2024) - [i7]Cristina Nader Vasconcelos, Abdullah Rashwan, Austin Waters, Trevor Walker, Keyang Xu, Jimmy Yan, Rui Qian, Shixin Luo, Zarana Parekh, Andrew Bunner, Hongliang Fei, Roopal Garg, Mandy Guo, Ivana Kajic, Yeqing Li, Henna Nandwani, Jordi Pont-Tuset, Yasumasa Onoe, Sarah Rosston, Su Wang, Wenlei Zhou, Kevin Swersky, David J. Fleet, Jason M. Baldridge, Oliver Wang:
Greedy Growing Enables High-Resolution Pixel-Based Diffusion Models. CoRR abs/2405.16759 (2024) - [i6]Jason Baldridge, Jakob Bauer, Mukul Bhutani, Nicole Brichtova, Andrew Bunner, Kelvin Chan, Yichang Chen, Sander Dieleman, Yuqing Du, Zach Eaton-Rosen, Hongliang Fei, Nando de Freitas, Yilin Gao, Evgeny Gladchenko, Sergio Gómez Colmenarejo, Mandy Guo, Alex Haig, Will Hawkins, Hexiang Hu, Huilian Huang, Tobenna Peter Igwe, Christos Kaplanis, Siavash Khodadadeh, Yelin Kim, Ksenia Konyushkova, Karol Langner, Eric Lau, Shixin Luo, Sona Mokrá, Henna Nandwani, Yasumasa Onoe, Aäron van den Oord, Zarana Parekh, Jordi Pont-Tuset, Hang Qi, Rui Qian, Deepak Ramachandran, Poorva Rane, Abdullah Rashwan, Ali Razavi, Robert Riachi, Hansa Srinivasan, Srivatsan Srinivasan, Robin Strudel, Benigno Uria, Oliver Wang, Su Wang, Austin Waters, Chris Wolff, Auriel Wright, Zhisheng Xiao, Hao Xiong, Keyang Xu, Marc van Zee, Junlin Zhang, Katie Zhang, Wenlei Zhou, Konrad Zolna, Ola Aboubakar, Canfer Akbulut, Oscar Akerlund, Isabela Albuquerque, Nina Anderson, Marco Andreetto, Lora Aroyo, Ben Bariach, David Barker, Sherry Ben, Dana Berman, Courtney Biles, Irina Blok, Pankil Botadra, Jenny Brennan, Karla Brown, John Buckley, Rudy Bunel, Elie Bursztein, Christina Butterfield, Ben Caine, Viral Carpenter, Norman Casagrande, Ming-Wei Chang, Solomon Chang, Shamik Chaudhuri, Tony Chen, John Choi, Dmitry Churbanau, Nathan Clement, Matan Cohen, Forrester Cole, Mikhail Dektiarev, Vincent Du, Praneet Dutta, Tom Eccles, Ndidi Elue, Ashley Feden, Shlomi Fruchter, Frankie Garcia, Roopal Garg:
Imagen 3. CoRR abs/2408.07009 (2024) - 2023
- [c44]Yue Zhang, Hongliang Fei, Ping Li:
Denoising Enhanced Distantly Supervised Ultrafine Entity Typing. ACL (Findings) 2023: 9880-9892 - [c43]Shaogang Ren, Hongliang Fei, Dingcheng Li, Ping Li:
Learning Latent Structural Relations with Message Passing Prior. WACV 2023: 5323-5332 - 2022
- [c42]Tan Yu, Zhipeng Jin, Jie Liu, Yi Yang, Hongliang Fei, Ping Li:
Boost CTR Prediction for New Advertisements via Modeling Visual Content. IEEE Big Data 2022: 2140-2149 - [c41]Tan Yu, Jie Liu, Yi Yang, Yi Li, Hongliang Fei, Ping Li:
Tree-based Text-Vision BERT for Video Search in Baidu Video Advertising. IEEE Big Data 2022: 2150-2159 - [c40]Tan Yu, Jun Zhi, Yufei Zhang, Jian Li, Hongliang Fei, Ping Li:
Decomposing User-APP Graph into Subgraphs for Effective APP and User Embedding Learning. IEEE Big Data 2022: 2441-2445 - [c39]Tan Yu, Jie Liu, Zhipeng Jin, Yi Yang, Hongliang Fei, Ping Li:
Multi-scale Multi-modal Dictionary BERT For Effective Text-image Retrieval in Multimedia Advertising. CIKM 2022: 4655-4660 - [c38]Tan Yu, Hongliang Fei, Ping Li:
U-BERT for Fast and Scalable Text-Image Retrieval. ICTIR 2022: 193-203 - [c37]Siamak Zamany, Dingcheng Li, Hongliang Fei, Ping Li:
Towards Deeper Understanding of Variational Auto-encoders for Binary Collaborative Filtering. ICTIR 2022: 254-263 - [c36]Tan Yu, Jie Liu, Yi Yang, Yi Li, Hongliang Fei, Ping Li:
EGM: Enhanced Graph-based Model for Large-scale Video Advertisement Search. KDD 2022: 4443-4451 - [c35]Yue Zhang, Hongliang Fei, Dingcheng Li, Ping Li:
PromptGen: Automatically Generate Prompts using Generative Models. NAACL-HLT (Findings) 2022: 30-37 - [c34]Tan Yu, Hongliang Fei, Ping Li:
Cross-Probe BERT for Fast Cross-Modal Search. SIGIR 2022: 2178-2183 - [c33]Yue Zhang, Hongliang Fei, Ping Li:
End-to-end Distantly Supervised Information Extraction with Retrieval Augmentation. SIGIR 2022: 2449-2455 - [i5]Tan Yu, Jie Liu, Yi Yang, Yi Li, Hongliang Fei, Ping Li:
Tree-based Text-Vision BERT for Video Search in Baidu Video Advertising. CoRR abs/2209.08759 (2022) - [i4]Tan Yu, Zhipeng Jin, Jie Liu, Yi Yang, Hongliang Fei, Ping Li:
Boost CTR Prediction for New Advertisements via Modeling Visual Content. CoRR abs/2209.11727 (2022) - [i3]Tan Yu, Jun Zhi, Yufei Zhang, Jian Li, Hongliang Fei, Ping Li:
Decomposing User-APP Graph into Subgraphs for Effective APP and User Embedding Learning. CoRR abs/2210.07232 (2022) - [i2]Yue Zhang, Hongliang Fei, Ping Li:
Denoising Enhanced Distantly Supervised Ultrafine Entity Typing. CoRR abs/2210.09599 (2022) - [i1]Yue Zhang, Hongliang Fei, Dingcheng Li, Tan Yu, Ping Li:
Prompting through Prototype: A Prototype-based Prompt Learning on Pretrained Vision-Language Models. CoRR abs/2210.10841 (2022) - 2021
- [c32]Tan Yu, Yi Yang
, Hongliang Fei, Yi Li, Xiaodong Chen, Ping Li:
Assorted Attention Network for Cross-Lingual Language-to-Vision Retrieval. CIKM 2021: 2444-2454 - [c31]Dingcheng Li, Hongliang Fei, Shaogang Ren, Ping Li:
A Deep Decomposable Model for Disentangling Syntax and Semantics in Sentence Representation. EMNLP (Findings) 2021: 4300-4310 - [c30]Shulong Tan, Zhaozhuo Xu, Weijie Zhao
Norm Adjusted Proximity Graph for Fast Inner Product Retrieval. KDD 2021: 1552-1560 - [c29]Hongliang Fei, Tan Yu, Ping Li:
Cross-lingual Cross-modal Pretraining for Multimodal Retrieval. NAACL-HLT 2021: 3644-3650 - [c28]Tan Yu, Yi Yang
Heterogeneous Attention Network for Effective and Efficient Cross-modal Retrieval. SIGIR 2021: 1146-1156 - [c27]Hongliang Fei, Jingyuan Zhang, Xingxuan Zhou, Junhao Zhao, Xinyang Qi, Ping Li:
GemNN: Gating-enhanced Multi-task Neural Networks with Feature Interaction Learning for CTR Prediction. SIGIR 2021: 2166-2171 - [c26]Yue Zhang, Hongliang Fei, Ping Li:
ReadsRE: Retrieval-Augmented Distantly Supervised Relation Extraction. SIGIR 2021: 2257-2262 - [c25]Puxuan Yu, Hongliang Fei, Ping Li:
Cross-lingual Language Model Pretraining for Retrieval. WWW 2021: 1029-1039 - 2020
- [c24]Hongliang Fei, Ping Li:
Cross-Lingual Unsupervised Sentiment Classification with Multi-View Transfer Learning. ACL 2020: 5759-5771 - [c23]Hongliang Fei, Shulong Tan, Pengju Guo, Wenbo Zhang, Hongfang Zhang, Ping Li:
Sample Optimization For Display Advertising. CIKM 2020: 2017-2020
2010 – 2019
- 2019
- [c22]Hongliang Fei, Xu Li, Dingcheng Li, Ping Li:
End-to-end Deep Reinforcement Learning Based Coreference Resolution. ACL (1) 2019: 660-665 - [c21]Zeyu Dai, Hongliang Fei, Ping Li:
Coreference Aware Representation Learning for Neural Named Entity Recognition. IJCAI 2019: 4946-4953 - [c20]Hongliang Fei, Shulong Tan, Ping Li:
Hierarchical Multi-Task Word Embedding Learning for Synonym Prediction. KDD 2019: 834-842 - [c19]Chaochun Liu, Yaliang Li, Hongliang Fei, Ping Li:
Deep Skip-Gram Networks for Text Classification. SDM 2019: 145-153 - 2018
- [c18]Yaowei Yan, Dongsheng Luo, Jingchao Ni, Hongliang Fei, Wei Fan, Xiong Bill Yu
Local Graph Clustering by Multi-network Random Walk with Restart. PAKDD (3) 2018: 490-501 - 2017
- [c17]Jingchao Ni, Hongliang Fei, Wei Fan, Xiang Zhang:
Cross-Network Clustering and Cluster Ranking for Medical Diagnosis. ICDE 2017: 163-166 - [c16]Jingchao Ni, Hongliang Fei, Wei Fan, Xiang Zhang:
Automated Medical Diagnosis by Ranking Clusters Across the Symptom-Disease Network. ICDM 2017: 1009-1014 - 2016
- [j5]Younghun Kim, Aleksandr Y. Aravkin, Hongliang Fei, A. Zondervan, M. Wolf:
Analytics for understanding customer behavior in the energy and utility industry. IBM J. Res. Dev. 60(1) (2016) - [c15]Chaochun Liu, Huan Sun, Nan Du, Shulong Tan, Hongliang Fei, Wei Fan, Tao Yang, Hao Wu, Yaliang Li, Chenwei Zhang:
Augmented LSTM Framework to Construct Medical Self-Diagnosis Android. ICDM 2016: 251-260 - 2014
- [j4]Hongliang Fei, Jun Huan:
Structured Sparse Boosting for Graph Classification. ACM Trans. Knowl. Discov. Data 9(1): 4:1-4:22 (2014) - [c14]Yu Cheng, Zhengzhang Chen
Batch Mode Active Learning with Hierarchical-Structured Embedded Variance. SDM 2014: 10-18 - 2013
- [j3]Meenakshi Mishra, Hongliang Fei, Jun Huan:
Computational prediction of toxicity. Int. J. Data Min. Bioinform. 8(3): 338-348 (2013) - [j2]Hongliang Fei, Jun Huan:
Structured feature selection and task relationship inference for multi-task learning. Knowl. Inf. Syst. 35(2): 345-364 (2013) - [j1]Ruoyi Jiang, Hongliang Fei, Jun Huan:
A Family of Joint Sparse PCA Algorithms for Anomaly Localization in Network Data Streams. IEEE Trans. Knowl. Data Eng. 25(11): 2421-2433 (2013) - [c13]Hongliang Fei, Younghun Kim, Sambit Sahu, Milind R. Naphade, Sanjay K. Mamidipalli, John Hutchinson:
Heat pump detection from coarse grained smart meter data with positive and unlabeled learning. KDD 2013: 1330-1338 - 2012
- [b1]Hongliang Fei:
Learning from Structured Data with High Dimensional Structured Input and Output Domain. University of Kansas, USA, 2012 - [c12]Xin Huang, Hong Cheng, Jiong Yang, Jeffrey Xu Yu, Hongliang Fei, Jun Huan:
Semi-supervised Clustering of Graph Objects: A Subgraph Mining Approach. DASFAA (1) 2012: 197-212 - 2011
- [c11]Hongliang Fei, Ruoyi Jiang, Yuhao Yang, Bo Luo
Content based social behavior prediction: a multi-task learning approach. CIKM 2011: 995-1000 - [c10]Hongliang Fei, Jun Huan:
Structured Feature Selection and Task Relationship Inference for Multi-task Learning. ICDM 2011: 171-180 - [c9]Ruoyi Jiang, Hongliang Fei, Jun Huan:
Anomaly localization for network data streams with graph joint sparse PCA. KDD 2011: 886-894 - 2010
- [c8]Meenakshi Mishra, Hongliang Fei, Jun Huan:
Computational prediction of toxicity. BIBM 2010: 686-691 - [c7]Hongliang Fei, Brian Quanz
Regularization and feature selection for networked features. CIKM 2010: 1893-1896 - [c6]Hongliang Fei, Jun Huan:
Boosting with structure information in the functional space: an application to graph classification. KDD 2010: 643-652
2000 – 2009
- 2009
- [c5]Hongliang Fei, Jun Huan:
L2 norm regularized feature kernel regression for graph data. CIKM 2009: 593-600 - [c4]Brian Quanz
Anomaly Detection with Sensor Data for Distributed Security. ICCCN 2009: 1-6 - [c3]Hongliang Fei, Brian Quanz
GLSVM: Integrating Structured Feature Selection and Large Margin Classification. ICDM Workshops 2009: 362-367 - 2008
- [c2]Hongliang Fei, Jun Huan:
Structure feature selection for chemical compound classification. BIBE 2008: 1-6 - [c1]Hongliang Fei, Jun Huan:
Structure feature selection for graph classification. CIKM 2008: 991-1000
Coauthor Index
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last updated on 2024-11-06 20:27 CET by the dblp team
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