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2020 – today
- 2024
[j19]Feng Bao, Zezhong Zhang, Guannan Zhang
:
A score-based filter for nonlinear data assimilation. J. Comput. Phys. 514: 113207 (2024)- [j18]Zezhong Zhang, Feng Bao, Lili Ju, Guannan Zhang:
Transferable Neural Networks for Partial Differential Equations. J. Sci. Comput. 99(1): 2 (2024) - [j17]Minglei Yang, Pengjun Wang, Diego del-Castillo-Negrete, Yanzhao Cao, Guannan Zhang:
A Pseudoreversible Normalizing Flow for Stochastic Dynamical Systems with Various Initial Distributions. SIAM J. Sci. Comput. 46(4): 508- (2024) - [c41]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: 16067-16075 - [c40]Yuan Lu, Dinghuang Hu, Guannan Zhang, Jie Shen, Dezun Dong:
Power of Insensitivity: Fixing Threshold Truncation of Switch Buffer Management Policies. CCGrid 2024: 640-641 - [c39]Jianxing Ma, Zhibo Xiao, Luwei Yang, Hansheng Xue, Xuanzhou Liu, Wen Jiang, Wei Ning, Guannan Zhang:
Modeling User Intent Beyond Trigger: Incorporating Uncertainty for Trigger-Induced Recommendation. CIKM 2024: 4743-4751 - [c38]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: 16570-16580 - [c37]Yichen Li, Qunwei Li, Haozhao Wang, Ruixuan Li, Wenliang Zhong, Guannan Zhang:
Towards Efficient Replay in Federated Incremental Learning. CVPR 2024: 12820-12829 - [c36]Yufei Ma, Zihan Liang, Huangyu Dai, Ben Chen, Dehong Gao, Zhuoran Ran, Zihan Wang, Linbo Jin, Wen Jiang, Guannan Zhang, Xiaoyan Cai, Libin Yang:
MoDULA: Mixture of Domain-Specific and Universal LoRA for Multi-Task Learning. EMNLP 2024: 2758-2770 - [c35]Zhiming Yang, Haining Gao, Dehong Gao, Luwei Yang, Libin Yang, Xiaoyan Cai, Wei Ning, Guannan Zhang:
MLoRA: Multi-Domain Low-Rank Adaptive Network for CTR Prediction. RecSys 2024: 287-297 - [c34]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: 1232-1241 - [c33]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: 228-237 - [c32]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: 360-368 - [c31]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: 674-682 - [c30]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: 1509-1518 - [i48]Yue Liu, Shihao Zhu, Jun Xia, Yingwei Ma, Jian Ma, Wenliang Zhong, Guannan Zhang, Kejun Zhang, Xinwang Liu:
Online Differentiable Clustering for Intent Learning in Recommendation. CoRR abs/2401.05975 (2024) - [i47]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 abs/2402.00893 (2024) - [i46]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 abs/2402.07788 (2024) - [i45]Yichen Li, Qunwei Li, Haozhao Wang, Ruixuan Li, Wenliang Zhong, Guannan Zhang:
Towards Efficient Replay in Federated Incremental Learning. CoRR abs/2403.05890 (2024) - [i44]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 abs/2404.00502 (2024) - [i43]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 abs/2407.10714 (2024) - [i42]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 abs/2407.12168 (2024) - [i41]Jianxing Ma, Zhibo Xiao, Luwei Yang, Hansheng Xue, Xuanzhou Liu, Wen Jiang, Wei Ning, Guannan Zhang:
Modeling User Intent Beyond Trigger: Incorporating Uncertainty for Trigger-Induced Recommendation. CoRR abs/2408.03091 (2024) - [i40]Zhiming Yang, Haining Gao, Dehong Gao, Luwei Yang, Libin Yang, Xiaoyan Cai, Wei Ning, Guannan Zhang:
MLoRA: Multi-Domain Low-Rank Adaptive Network for CTR Prediction. CoRR abs/2408.08913 (2024) - [i39]Konstantin Pieper, Zezhong Zhang, Guannan Zhang:
Nonuniform random feature models using derivative information. CoRR abs/2410.02132 (2024) - [i38]Yanfang Liu, Yuan Chen, Dongbin Xiu, Guannan Zhang:
A Training-Free Conditional Diffusion Model for Learning Stochastic Dynamical Systems. CoRR abs/2410.03108 (2024) - [i37]Yuwei Geng, Olena Burkovska, Lili Ju, Guannan Zhang, Max D. Gunzburger:
An End-to-End Deep Learning Method for Solving Nonlocal Allen-Cahn and Cahn-Hilliard Phase-Field Models. CoRR abs/2410.08914 (2024) - 2023
- [j16]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): 2718-2743 (2023) - [j15]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): 1148-1171 (2023) - [c29]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: 7722-7739 - [c28]Jianqiao Sheng, Yuan Fang, Guannan Zhang, Xin Ding:
Data Flow Risk Monitoring for Novel Power System Based on Bidirectional Interactive Protocol Traffic. CAIBDA 2023: 451-458 - [c27]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: 2482-2491 - [c26]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: 4595-4601 - [c25]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: 3182-3195 - [c24]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: 3248-3254 - [c23]Guannan Zhang, Dinghuang Hu, Dezun Dong:
Rately: Accurate Data Center CC based on One-Way Delay. ICPADS 2023: 2759-2760 - [c22]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: 6103-6111 - [c21]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: 5509-5519 - [c20]Yang Zhang, Yue Shen, Dong Wang, Jinjie Gu, Guannan Zhang:
Connecting Unseen Domains: Cross-Domain Invariant Learning in Recommendation. SIGIR 2023: 1894-1898 - [c19]Zexi Li, Qunwei Li, Yi Zhou, Wenliang Zhong, Guannan Zhang, Chao Wu:
Edge-cloud Collaborative Learning with Federated and Centralized Features. SIGIR 2023: 1949-1953 - [c18]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: 2179-2183 - [c17]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: 3364-3368 - [c16]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: 186-194 - [c15]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: 361-365 - [c14]Hongyu Shan, Qishen Zhang, Zhongyi Liu, Guannan Zhang, Chenliang Li:
Beyond Two-Tower: Attribute Guided Representation Learning for Candidate Retrieval. WWW 2023: 3173-3181 - [i36]Zezhong Zhang, Feng Bao, Lili Ju, Guannan Zhang:
TransNet: Transferable Neural Networks for Partial Differential Equations. CoRR abs/2301.11701 (2023) - [i35]Hoang Tran, Qiang Du, Guannan Zhang:
Convergence analysis for a nonlocal gradient descent method via directional Gaussian smoothing. CoRR abs/2302.06404 (2023) - [i34]Zexi Li, Qunwei Li, Yi Zhou, Wenliang Zhong, Guannan Zhang, Chao Wu:
Edge-cloud Collaborative Learning with Federated and Centralized Features. CoRR abs/2304.05871 (2023) - [i33]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 abs/2304.12537 (2023) - [i32]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 abs/2305.18780 (2023) - [i31]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 abs/2306.05580 (2023) - [i30]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 abs/2308.12711 (2023) - [i29]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 abs/2308.13246 (2023) - [i28]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:
AntM2C: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction. CoRR abs/2308.16437 (2023) - [i27]Feng Bao, Zezhong Zhang, Guannan Zhang:
An Ensemble Score Filter for Tracking High-Dimensional Nonlinear Dynamical Systems. CoRR abs/2309.00983 (2023) - [i26]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 abs/2309.02669 (2023) - [i25]Yuqi Gong, Xichen Ding, Yehui Su, Kaiming Shen, Zhongyi Liu, Guannan Zhang:
An Unified Search and Recommendation Foundation Model for Cold-Start Scenario. CoRR abs/2309.08939 (2023) - [i24]Yanfang Liu, Minglei Yang, Zezhong Zhang, Feng Bao, Yanzhao Cao, Guannan Zhang:
Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation. CoRR abs/2310.14458 (2023) - [i23]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 abs/2311.00447 (2023) - [i22]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 abs/2311.08719 (2023) - [i21]Yiming Wang, Yu Lin, Xiaodong Zeng, Guannan Zhang:
MultiLoRA: Democratizing LoRA for Better Multi-Task Learning. CoRR abs/2311.11501 (2023) - [i20]Yiming Wang, Yu Lin, Xiaodong Zeng, Guannan Zhang:
PrivateLoRA For Efficient Privacy Preserving LLM. CoRR abs/2311.14030 (2023) - [i19]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 abs/2312.01040 (2023) - [i18]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 abs/2312.01916 (2023) - [i17]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 abs/2312.02538 (2023) - [i16]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 abs/2312.02554 (2023) - [i15]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 abs/2312.05276 (2023) - [i14]Yao Zhao, Haipeng Zhang, Shiwei Lyu, Ruiying Jiang, Jinjie Gu, Guannan Zhang:
Multiple Instance Learning for Uplift Modeling. CoRR abs/2312.09639 (2023) - [i13]Zezhong Zhang, Feng Bao, Guannan Zhang:
Improving the Expressive Power of Deep Neural Networks through Integral Activation Transform. CoRR abs/2312.12578 (2023) - [i12]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 abs/2312.16176 (2023) - 2022
- [c13]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: 4299-4303 - [c12]Yao Zhao, Haipeng Zhang, Shiwei Lyu, Ruiying Jiang, Jinjie Gu, Guannan Zhang:
Multiple Instance Learning for Uplift Modeling. CIKM 2022: 4727-4731 - [c11]Hoang Tran, Dan Lu, Guannan Zhang:
Exploiting the Local Parabolic Landscapes of Adversarial Losses to Accelerate Black-Box Adversarial Attack. ECCV (5) 2022: 317-334 - [c10]Siyan Liu, Pei Zhang, Dan Lu, Guannan Zhang:
PI3NN: Out-of-distribution-aware Prediction Intervals from Three Neural Networks. ICLR 2022 - [c9]Junqi Yin, Guannan Zhang, Huibo Cao, Sajal Dash, Bryan C. Chakoumakos, Feiyi Wang:
Toward an Autonomous Workflow for Single Crystal Neutron Diffraction. SMC 2022: 244-256 - [i11]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 abs/2202.09353 (2022) - [i10]Minglei Yang, Guannan Zhang, Diego del-Castillo-Negrete, Yanzhao Cao:
A probabilistic scheme for semilinear nonlocal diffusion equations with volume constraints. CoRR abs/2205.00516 (2022) - 2021
- [j14]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: 110564 (2021) - [c8]Jiaxin Zhang, Sirui Bi, Guannan Zhang:
A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models. AISTATS 2021: 3745-3753 - [c7]Qilu Wang, Guannan Zhang, Hanyuan Zhang, Yongqing Duan, Yongan Huang:
Electrohydrodynamically Printed Multicolor Perovskite Image Sensor Array. NEMS 2021: 652-655 - [c6]Jiaxin Zhang, Hoang Tran, Dan Lu, Guannan Zhang:
Enabling long-range exploration in minimization of multimodal functions. UAI 2021: 1639-1649 - [i9]Jiaxin Zhang, Sirui Bi, Guannan Zhang:
A Scalable Gradient-Free Method for Bayesian Experimental Design with Implicit Models. CoRR abs/2103.08026 (2021) - [i8]Jiaxin Zhang, Sirui Bi, Guannan Zhang:
A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models. CoRR abs/2103.08594 (2021) - [i7]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 abs/2104.14561 (2021) - [i6]Siyan Liu, Pei Zhang, Dan Lu, Guannan Zhang:
PI3NN: Prediction intervals from three independently trained neural networks. CoRR abs/2108.02327 (2021) - [i5]Yuankai Teng, Zhu Wang, Lili Ju, Anthony D. Gruber, Guannan Zhang:
Level set learning with pseudo-reversible neural networks for nonlinear dimension reduction in function approximation. CoRR abs/2112.01438 (2021) - 2020
- [c5]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: 2629-2636 - [c4]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: 2455-2463 - [i4]Jiaxin Zhang, Hoang Tran, Dan Lu, Guannan Zhang:
A Scalable Evolution Strategy with Directional Gaussian Smoothing for Blackbox Optimization. CoRR abs/2002.03001 (2020) - [i3]Jiaxing Zhang, Hoang Tran, Guannan Zhang:
Accelerating Reinforcement Learning with a Directional-Gaussian-Smoothing Evolution Strategy. CoRR abs/2002.09077 (2020) - [i2]Hoang Tran, Guannan Zhang:
AdaDGS: An adaptive black-box optimization method with a nonlocal directional Gaussian smoothing gradient. CoRR abs/2011.02009 (2020) - [i1]Sirui Bi, Jiaxin Zhang, Guannan Zhang:
Scalable Deep-Learning-Accelerated Topology Optimization for Additively Manufactured Materials. CoRR abs/2011.14177 (2020)
2010 – 2019
- 2019
- [j13]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): 76-91 (2019) - [j12]Lin Mu, Guannan Zhang:
A Domain Decomposition Model Reduction Method for Linear Convection-Diffusion Equations with Random Coefficients. SIAM J. Sci. Comput. 41(3): A1984-A2011 (2019) - [c3]Guannan Zhang, Jiaxin Zhang, Jacob D. Hinkle:
Learning nonlinear level sets for dimensionality reduction in function approximation. NeurIPS 2019: 13199-13208 - 2017
- [j11]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): 451-493 (2017) - 2016
- [j10]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): 2231-2256 (2016) - [j9]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): 2479-2496 (2016) - [j8]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): 1111-1137 (2016) - [j7]Guannan Zhang, Clayton G. Webster, Max D. Gunzburger, John V. Burkardt:
Hyperspherical Sparse Approximation Techniques for High-Dimensional Discontinuity Detection. SIAM Rev. 58(3): 517-551 (2016) - 2015
- [j6]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): 1508-1536 (2015) - 2014
- [j5]Max D. Gunzburger, Clayton G. Webster, Guannan Zhang:
Stochastic finite element methods for partial differential equations with random input data. Acta Numer. 23: 521-650 (2014) - [j4]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): 798-817 (2014) - [j3]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): 784-804 (2014) - 2012
- [j2]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): 1922-1940 (2012) - 2010
- [j1]Weidong Zhao, Guannan Zhang, Lili Ju:
A Stable Multistep Scheme for Solving Backward Stochastic Differential Equations. SIAM J. Numer. Anal. 48(4): 1369-1394 (2010)
2000 – 2009
- 2008
- [c2]Yan Liu, Mingguang Zhuang, Qingling Wang, Guannan Zhang:
A New Approach to Web Services Characterization. APSCC 2008: 404-409 - [c1]Yan Liu, Mingguang Zhuang, Biao Yu, Guannan Zhang, Xiaojing Meng:
Services Characterization with Statistical Study on Existing Web Services. ICWS 2008: 803-804
Coauthor Index
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last updated on 2024-12-02 22:28 CET by the dblp team
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