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2020 – today
- 2023
[c25]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- [c24]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 - [c23]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 - [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 - [i23]Zezhong Zhang, Feng Bao, Lili Ju, Guannan Zhang:
TransNet: Transferable Neural Networks for Partial Differential Equations. CoRR abs/2301.11701 (2023) - [i22]Hoang Tran, Qiang Du, Guannan Zhang:
Convergence analysis for a nonlocal gradient descent method via directional Gaussian smoothing. CoRR abs/2302.06404 (2023) - [i21]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) - [i20]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) - [i19]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) - [i18]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) - [i17]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) - [i16]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) - [i15]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) - [i14]Feng Bao, Zezhong Zhang, Guannan Zhang:
An Ensemble Score Filter for Tracking High-Dimensional Nonlinear Dynamical Systems. CoRR abs/2309.00983 (2023) - [i13]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) - [i12]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) - 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 2023-09-24 22:11 CEST by the dblp team
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