Guannan Zhang

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 88

Top Topics

Partial Differential Equations

Data Assimilation

Gaussian Smoothing

Top Venues

Publications

Yue Wang, Zilong Zheng, Juntao Li, Zhihui Liu, Jinxiong Chang, Qishen Zhang, Zhongyi Liu, Guannan Zhang, Min Zhang
Towards More Realistic Chinese Spell Checking with New Benchmark and Specialized Expert Model. LREC/COLING (2024)
Zezhong Zhang, Feng Bao, Lili Ju, Guannan Zhang
Transferable Neural Networks for Partial Differential Equations. J. Sci. Comput. 99 (1) (2024)
Feng Bao, Zezhong Zhang, Guannan Zhang
A score-based filter for nonlinear data assimilation. J. Comput. Phys. 514 (2024)
Songhao Wu, Quan Tu, Hong Liu, Jia Xu, Zhongyi Liu, Guannan Zhang, Ran Wang, Xiuying Chen, Rui Yan
Unify Graph Learning with Text: Unleashing LLM Potentials for Session Search. WWW (2024)
Zhitian Xie, Yinger Zhang, Chenyi Zhuang, Qitao Shi, Zhining Liu, Jinjie Gu, Guannan Zhang
MoDE: A Mixture-of-Experts Model with Mutual Distillation among the Experts. AAAI (2024)
Mingzhe Li, Xiuying Chen, Jing Xiang, Qishen Zhang, Changsheng Ma, Chenchen Dai, Jinxiong Chang, Zhongyi Liu, Guannan Zhang
Multi-Intent Attribute-Aware Text Matching in Searching. WSDM (2024)
Zhitian Xie, Yinger Zhang, Chenyi Zhuang, Qitao Shi, Zhining Liu, Jinjie Gu, Guannan Zhang
MoDE: A Mixture-of-Experts Model with Mutual Distillation among the Experts. CoRR (2024)
Mingzhe Li, Xiuying Chen, Jing Xiang, Qishen Zhang, Changsheng Ma, Chenchen Dai, Jinxiong Chang, Zhongyi Liu, Guannan Zhang
Multi-Intent Attribute-Aware Text Matching in Searching. CoRR (2024)
Minglei Yang, Pengjun Wang, Ming Fan, Dan Lu, Yanzhao Cao, Guannan Zhang
Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation. CoRR (2024)
Kaiming Shen, Xichen Ding, Zixiang Zheng, Yuqi Gong, Qianqian Li, Zhongyi Liu, Guannan Zhang
SEMINAR: Search Enhanced Multi-modal Interest Network and Approximate Retrieval for Lifelong Sequential Recommendation. CoRR (2024)
Junqi Yin, Siming Liang, Siyan Liu, Feng Bao, Hristo G. Chipilski, Dan Lu, Guannan Zhang
A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics. CoRR (2024)
Chunjing Gan, Bo Huang, Binbin Hu, Jian Ma, Zhiqiang Zhang, Jun Zhou, Guannan Zhang, Wenliang Zhong
PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation. WSDM (2024)
Xiaojie Sun, Keping Bi, Jiafeng Guo, Sihui Yang, Qishen Zhang, Zhongyi Liu, Guannan Zhang, Xueqi Cheng
A Multi-Granularity-Aware Aspect Learning Model for Multi-Aspect Dense Retrieval. WSDM (2024)
Yue Liu, Shihao Zhu, Jun Xia, Yingwei Ma, Jian Ma, Wenliang Zhong, Guannan Zhang, Kejun Zhang, Xinwang Liu
End-to-end Learnable Clustering for Intent Learning in Recommendation. CoRR (2024)
Zhaoxin Huan, Ke Ding, Ang Li, Xiaolu Zhang, Xu Min, Yong He, Liang Zhang, Jun Zhou, Linjian Mo, Jinjie Gu, Zhongyi Liu, Wenliang Zhong, Guannan Zhang, Chenliang Li, Fajie Yuan
Exploring Multi-Scenario Multi-Modal CTR Prediction with a Large Scale Dataset. SIGIR (2024)
Yiming Wang, Yu Lin, Xiaodong Zeng, Guannan Zhang
MultiLoRA: Democratizing LoRA for Better Multi-Task Learning. CoRR (2023)
Dan Yang, Binbin Hu, Xiaoyan Yang, Yue Shen, Zhiqiang Zhang, Jinjie Gu, Guannan Zhang
Who Would be Interested in Services? An Entity Graph Learning System for User Targeting. ICDE (2023)
Qiang Li, Xiaoyan Yang, Haowen Wang, Qin Wang, Lei Liu, Junjie Wang, Yang Zhang, Mingyuan Chu, Sen Hu, Yicheng Chen, Yue Shen, Cong Fan, Wangshu Zhang, Teng Xu, Jinjie Gu, Jing Zheng, Guannan Zhang
From Beginner to Expert: Modeling Medical Knowledge into General LLMs. CoRR (2023)
Tianchi Cai, Shenliao Bao, Jiyan Jiang, Shiji Zhou, Wenpeng Zhang, Lihong Gu, Jinjie Gu, Guannan Zhang
Model-free Reinforcement Learning with Stochastic Reward Stabilization for Recommender Systems. CoRR (2023)
Zezhong Zhang, Feng Bao, Guannan Zhang
Improving the Expressive Power of Deep Neural Networks through Integral Activation Transform. CoRR (2023)
Xiaojie Sun, Keping Bi, Jiafeng Guo, Sihui Yang, Qishen Zhang, Zhongyi Liu, Guannan Zhang, Xueqi Cheng
A Multi-Granularity-Aware Aspect Learning Model for Multi-Aspect Dense Retrieval. CoRR (2023)
You Zhou, Xiujing Lin, Xiang Zhang, Maolin Wang, Gangwei Jiang, Huakang Lu, Yupeng Wu, Kai Zhang, Zhe Yang, Kehang Wang, Yongduo Sui, Fengwei Jia, Zuoli Tang, Yao Zhao, Hongxuan Zhang, Tiannuo Yang, Weibo Chen, Yunong Mao, Yi Li, De Bao, Yu Li, Hongrui Liao, Ting Liu, Jingwen Liu, Jinchi Guo, Xiangyu Zhao, Ying Wei, Hong Qian, Qi Liu, Xiang Wang, Wai Kin Chan, Chenliang Li, Yusen Li, Shiyu Yang, Jining Yan, Chao Mou, Shuai Han, Wuxia Jin, Guannan Zhang, Xiaodong Zeng
On the Opportunities of Green Computing: A Survey. CoRR (2023)
Minglei Yang, Guannan Zhang, Diego del-Castillo-Negrete, Yanzhao Cao
A Probabilistic Scheme for Semilinear Nonlocal Diffusion Equations with Volume Constraints. SIAM J. Numer. Anal. 61 (6) (2023)
Tianchi Cai, Shenliao Bao, Jiyan Jiang, Shiji Zhou, Wenpeng Zhang, Lihong Gu, Jinjie Gu, Guannan Zhang
Model-free Reinforcement Learning with Stochastic Reward Stabilization for Recommender Systems. SIGIR (2023)
Yao Zhao, Haipeng Zhang, Shiwei Lyu, Ruiying Jiang, Jinjie Gu, Guannan Zhang
Multiple Instance Learning for Uplift Modeling. CoRR (2023)
Weifan Wang, Binbin Hu, Zhicheng Peng, Mingjie Zhong, Zhiqiang Zhang, Zhongyi Liu, Guannan Zhang, Jun Zhou
GARCIA: Powering Representations of Long-tail Query with Multi-granularity Contrastive Learning. ICDE (2023)
Chunjing Gan, Bo Huang, Binbin Hu, Jian Ma, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Guannan Zhang, Wenliang Zhong
PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation. CoRR (2023)
Yanfang Liu, Minglei Yang, Zezhong Zhang, Feng Bao, Yanzhao Cao, Guannan Zhang
Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation. CoRR (2023)
Zezhong Zhang, Feng Bao, Lili Ju, Guannan Zhang
TransNet: Transferable Neural Networks for Partial Differential Equations. CoRR (2023)
Zexi Li, Qunwei Li, Yi Zhou, Wenliang Zhong, Guannan Zhang, Chao Wu
Edge-cloud Collaborative Learning with Federated and Centralized Features. CoRR (2023)
Ke Tu, Wei Qu, Zhengwei Wu, Zhiqiang Zhang, Zhongyi Liu, Yiming Zhao, Le Wu, Jun Zhou, Guannan Zhang
Disentangled Interest importance aware Knowledge Graph Neural Network for Fund Recommendation. CIKM (2023)
Hoang Tran, Qiang Du, Guannan Zhang
Convergence analysis for a nonlocal gradient descent method via directional Gaussian smoothing. CoRR (2023)
Yankun Ren, Xinxing Yang, Xingyu Lu, Longfei Li, Jun Zhou, Jinjie Gu, Guannan Zhang
GreenSeq: Automatic Design of Green Networks for Sequential Recommendation Systems. SIGIR (2023)
Xiaoling Zang, Binbin Hu, Jun Chu, Zhiqiang Zhang, Guannan Zhang, Jun Zhou, Wenliang Zhong
Commonsense Knowledge Graph towards Super APP and Its Applications in Alipay. KDD (2023)
Lei Liu, Xiaoyan Yang, Yue Shen, Binbin Hu, Zhiqiang Zhang, Jinjie Gu, Guannan Zhang
Think-in-Memory: Recalling and Post-thinking Enable LLMs with Long-Term Memory. CoRR (2023)
Dan Yang, Binbin Hu, Xiaoyan Yang, Yue Shen, Zhiqiang Zhang, Jinjie Gu, Guannan Zhang
Who Would be Interested in Services? An Entity Graph Learning System for User Targeting. CoRR (2023)
Yuqi Gong, Xichen Ding, Yehui Su, Kaiming Shen, Zhongyi Liu, Guannan Zhang
An Unified Search and Recommendation Foundation Model for Cold-Start Scenario. CoRR (2023)
Chunjing Gan, Dan Yang, Binbin Hu, Ziqi Liu, Yue Shen, Zhiqiang Zhang, Jinjie Gu, Jun Zhou, Guannan Zhang
Making Large Language Models Better Knowledge Miners for Online Marketing with Progressive Prompting Augmentation. CoRR (2023)
Xiaoyan Yang, Dong Wang, Binbin Hu, Dan Yang, Yue Shen, Jinjie Gu, Zhiqiang Zhang, Shiwei Lyu, Haipeng Zhang, Guannan Zhang
Movie Ticket, Popcorn, and Another Movie Next Weekend: Time-Aware Service Sequential Recommendation for User Retention. WWW (Companion Volume) (2023)
Yue Wang, Dan Qiao, Juntao Li, Jinxiong Chang, Qishen Zhang, Zhongyi Liu, Guannan Zhang, Min Zhang
Towards Better Hierarchical Text Classification with Data Generation. ACL (Findings) (2023)
Tianchi Cai, Jiyan Jiang, Wenpeng Zhang, Shiji Zhou, Xierui Song, Li Yu, Lihong Gu, Xiaodong Zeng, Jinjie Gu, Guannan Zhang
Marketing Budget Allocation with Offline Constrained Deep Reinforcement Learning. CoRR (2023)
Guannan Zhang, Dinghuang Hu, Dezun Dong
Rately: Accurate Data Center CC based on One-Way Delay. ICPADS (2023)
Tianchi Cai, Xierui Song, Jiyan Jiang, Fei Teng, Jinjie Gu, Guannan Zhang
ULMA: Unified Language Model Alignment with Demonstration and Point-wise Human Preference. CoRR (2023)
Minglei Yang, Pengjun Wang, Diego del-Castillo-Negrete, Yanzhao Cao, Guannan Zhang
A pseudo-reversible normalizing flow for stochastic dynamical systems with various initial distributions. CoRR (2023)
Jianqiao Sheng, Yuan Fang, Guannan Zhang, Xin Ding
Data Flow Risk Monitoring for Novel Power System Based on Bidirectional Interactive Protocol Traffic. CAIBDA (2023)
Yiming Wang, Yu Lin, Xiaodong Zeng, Guannan Zhang
PrivateLoRA For Efficient Privacy Preserving LLM. CoRR (2023)
Yang Zhang, Yue Shen, Dong Wang, Jinjie Gu, Guannan Zhang
Connecting Unseen Domains: Cross-Domain Invariant Learning in Recommendation. SIGIR (2023)
Xingyu Lu, Zhining Liu, Yanchu Guan, Hongxuan Zhang, Chenyi Zhuang, Wenqi Ma, Yize Tan, Jinjie Gu, Guannan Zhang
GreenFlow: A Computation Allocation Framework for Building Environmentally Sound Recommendation System. IJCAI (2023)
Feng Bao, Zezhong Zhang, Guannan Zhang
An Ensemble Score Filter for Tracking High-Dimensional Nonlinear Dynamical Systems. CoRR (2023)
Xingyu Lu, Zhining Liu, Yanchu Guan, Hongxuan Zhang, Chenyi Zhuang, Wenqi Ma, Yize Tan, Jinjie Gu, Guannan Zhang
GreenFlow: A Computation Allocation Framework for Building Environmentally Sound Recommendation System. CoRR (2023)
Weifan Wang, Binbin Hu, Zhicheng Peng, Mingjie Zhong, Zhiqiang Zhang, Zhongyi Liu, Guannan Zhang, Jun Zhou
GARCIA: Powering Representations of Long-tail Query with Multi-granularity Contrastive Learning. CoRR (2023)
Zexi Li, Qunwei Li, Yi Zhou, Wenliang Zhong, Guannan Zhang, Chao Wu
Edge-cloud Collaborative Learning with Federated and Centralized Features. SIGIR (2023)
Yue Wang, Xinrui Wang, Juntao Li, Jinxiong Chang, Qishen Zhang, Zhongyi Liu, Guannan Zhang, Min Zhang
Harnessing the Power of David against Goliath: Exploring Instruction Data Generation without Using Closed-Source Models. CoRR (2023)
Zhaoxin Huan, Ke Ding, Ang Li, Xiaolu Zhang, Xu Min, Yong He, Liang Zhang, Jun Zhou, Linjian Mo, Jinjie Gu, Zhongyi Liu, Wenliang Zhong, Guannan Zhang
C: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction. CoRR (2023)
Tianchi Cai, Jiyan Jiang, Wenpeng Zhang, Shiji Zhou, Xierui Song, Li Yu, Lihong Gu, Xiaodong Zeng, Jinjie Gu, Guannan Zhang
Marketing Budget Allocation with Offline Constrained Deep Reinforcement Learning. WSDM (2023)
Yuankai Teng, Zhu Wang, Lili Ju, Anthony D. Gruber, Guannan Zhang
Level Set Learning with Pseudoreversible Neural Networks for Nonlinear Dimension Reduction in Function Approximation. SIAM J. Sci. Comput. 45 (3) (2023)
Hongyu Shan, Qishen Zhang, Zhongyi Liu, Guannan Zhang, Chenliang Li
Beyond Two-Tower: Attribute Guided Representation Learning for Candidate Retrieval. WWW (2023)
Yuqi Gong, Xichen Ding, Yehui Su, Kaiming Shen, Zhongyi Liu, Guannan Zhang
An Unified Search and Recommendation Foundation Model for Cold-Start Scenario. CIKM (2023)
Shiwei Lyu, Hongbo Cai, Chaohe Zhang, Shuai Ling, Yue Shen, Xiaodong Zeng, Jinjie Gu, Guannan Zhang, Haipeng Zhang
See Clicks Differently: Modeling User Clicking Alternatively with Multi Classifiers for CTR Prediction. CIKM (2022)
Junqi Yin, Guannan Zhang, Huibo Cao, Sajal Dash, Bryan C. Chakoumakos, Feiyi Wang
Toward an Autonomous Workflow for Single Crystal Neutron Diffraction. SMC (2022)
Yao Zhao, Haipeng Zhang, Shiwei Lyu, Ruiying Jiang, Jinjie Gu, Guannan Zhang
Multiple Instance Learning for Uplift Modeling. CIKM (2022)
Minglei Yang, Guannan Zhang, Diego del-Castillo-Negrete, Yanzhao Cao
A probabilistic scheme for semilinear nonlocal diffusion equations with volume constraints. CoRR (2022)
Majdi I. Radaideh, Hoang Tran, Lianshan Lin, Hao Jiang, Drew Winder, Sarma Gorti, Guannan Zhang, Justin Mach, Sarah Cousineau
Model Calibration of the Liquid Mercury Spallation Target using Evolutionary Neural Networks and Sparse Polynomial Expansions. CoRR (2022)
Hoang Tran, Dan Lu, Guannan Zhang
Exploiting the Local Parabolic Landscapes of Adversarial Losses to Accelerate Black-Box Adversarial Attack. ECCV (5) (2022)
Siyan Liu, Pei Zhang, Dan Lu, Guannan Zhang
PI3NN: Out-of-distribution-aware Prediction Intervals from Three Neural Networks. ICLR (2022)
Jiaxin Zhang, Sirui Bi, Guannan Zhang
A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models. CoRR (2021)
Jiaxin Zhang, Sirui Bi, Guannan Zhang
A Scalable Gradient-Free Method for Bayesian Experimental Design with Implicit Models. CoRR (2021)
Minglei Yang, Guannan Zhang, Diego del-Castillo-Negrete, Miroslav Stoyanov
A Feynman-Kac based numerical method for the exit time probability of a class of transport problems. CoRR (2021)
Jiaxin Zhang, Sirui Bi, Guannan Zhang
A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models. AISTATS (2021)
Minglei Yang, Guannan Zhang, Diego del-Castillo-Negrete, Miroslav Stoyanov
A Feynman-Kac based numerical method for the exit time probability of a class of transport problems. J. Comput. Phys. 444 (2021)
Qilu Wang, Guannan Zhang, Hanyuan Zhang, Yongqing Duan, Yongan Huang
Electrohydrodynamically Printed Multicolor Perovskite Image Sensor Array. NEMS (2021)
Jiaxin Zhang, Hoang Tran, Dan Lu, Guannan Zhang
Enabling long-range exploration in minimization of multimodal functions. UAI (2021)
Siyan Liu, Pei Zhang, Dan Lu, Guannan Zhang
PI3NN: Prediction intervals from three independently trained neural networks. CoRR (2021)
Yuankai Teng, Zhu Wang, Lili Ju, Anthony Gruber, Guannan Zhang
Level set learning with pseudo-reversible neural networks for nonlinear dimension reduction in function approximation. CoRR (2021)
Chenyi Zhuang, Ziqi Liu, Zhiqiang Zhang, Yize Tan, Zhengwei Wu, Zhining Liu, Jianping Wei, Jinjie Gu, Guannan Zhang, Jun Zhou, Yuan Qi
Hubble: An Industrial System for Audience Expansion in Mobile Marketing. KDD (2020)
Sirui Bi, Jiaxin Zhang, Guannan Zhang
Scalable Deep-Learning-Accelerated Topology Optimization for Additively Manufactured Materials. CoRR (2020)
Hoang Tran, Guannan Zhang
AdaDGS: An adaptive black-box optimization method with a nonlocal directional Gaussian smoothing gradient. CoRR (2020)
Jiaxing Zhang, Hoang Tran, Guannan Zhang
Accelerating Reinforcement Learning with a Directional-Gaussian-Smoothing Evolution Strategy. CoRR (2020)
Zhining Liu, Xiao-Fan Niu, Chenyi Zhuang, Yize Tan, Yixiang Mu, Jinjie Gu, Guannan Zhang
Two-Stage Audience Expansion for Financial Targeting in Marketing. CIKM (2020)
Jiaxin Zhang, Hoang Tran, Dan Lu, Guannan Zhang
A Scalable Evolution Strategy with Directional Gaussian Smoothing for Blackbox Optimization. CoRR (2020)
Lin Mu, Guannan Zhang
A Domain Decomposition Model Reduction Method for Linear Convection-Diffusion Equations with Random Coefficients. SIAM J. Sci. Comput. 41 (3) (2019)
Max D. Gunzburger, Michael Schneier, Clayton G. Webster, Guannan Zhang
An Improved Discrete Least-Squares/Reduced-Basis Method for Parameterized Elliptic PDEs. J. Sci. Comput. 81 (1) (2019)
Guannan Zhang, Jiaxin Zhang, Jacob D. Hinkle
Learning nonlinear level sets for dimensionality reduction in function approximation. NeurIPS (2019)
Hoang Tran, Clayton G. Webster, Guannan Zhang
Analysis of quasi-optimal polynomial approximations for parameterized PDEs with deterministic and stochastic coefficients. Numerische Mathematik 137 (2) (2017)
Diego Galindo, Peter Jantsch, Clayton G. Webster, Guannan Zhang
Accelerating Stochastic Collocation Methods for Partial Differential Equations with Random Input Data. SIAM/ASA J. Uncertain. Quantification 4 (1) (2016)
Nick C. Dexter, Clayton G. Webster, Guannan Zhang
Explicit cost bounds of stochastic Galerkin approximations for parameterized PDEs with random coefficients. Comput. Math. Appl. 71 (11) (2016)
Guannan Zhang, Weidong Zhao, Clayton G. Webster, Max D. Gunzburger
Numerical methods for a class of nonlocal diffusion problems with the use of backward SDEs. Comput. Math. Appl. 71 (11) (2016)
Guannan Zhang, Clayton G. Webster, Max D. Gunzburger, John V. Burkardt
Hyperspherical Sparse Approximation Techniques for High-Dimensional Discontinuity Detection. SIAM Rev. 58 (3) (2016)
Guannan Zhang, Clayton G. Webster, Max D. Gunzburger, John V. Burkardt
A Hyperspherical Adaptive Sparse-Grid Method for High-Dimensional Discontinuity Detection. SIAM J. Numer. Anal. 53 (3) (2015)
Feng Bao, Yanzhao Cao, Clayton G. Webster, Guannan Zhang
A Hybrid Sparse-Grid Approach for Nonlinear Filtering Problems Based on Adaptive-Domain of the Zakai Equation Approximations. SIAM/ASA J. Uncertain. Quantification 2 (1) (2014)
Max D. Gunzburger, Clayton G. Webster, Guannan Zhang
Stochastic finite element methods for partial differential equations with random input data. Acta Numer. 23 (2014)
Clayton G. Webster, Guannan Zhang, Max D. Gunzburger
An adaptive sparse-grid iterative ensemble Kalman filter approach for parameter field estimation. Int. J. Comput. Math. 91 (4) (2014)
Guannan Zhang, Max D. Gunzburger
Error Analysis of a Stochastic Collocation Method for Parabolic Partial Differential Equations with Random Input Data. SIAM J. Numer. Anal. 50 (4) (2012)
Weidong Zhao, Guannan Zhang, Lili Ju
A Stable Multistep Scheme for Solving Backward Stochastic Differential Equations. SIAM J. Numer. Anal. 48 (4) (2010)
Yan Liu, Mingguang Zhuang, Qingling Wang, Guannan Zhang
A New Approach to Web Services Characterization. APSCC (2008)
Yan Liu, Mingguang Zhuang, Biao Yu, Guannan Zhang, Xiaojing Meng
Services Characterization with Statistical Study on Existing Web Services. ICWS (2008)