Guannan Zhang

Orcid: 0000-0002-7091-2318

According to our database1, Guannan Zhang authored at least 91 papers between 2008 and 2024.

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Bibliography

2024
Transferable Neural Networks for Partial Differential Equations.
J. Sci. Comput., April, 2024

A Pseudoreversible Normalizing Flow for Stochastic Dynamical Systems with Various Initial Distributions.
SIAM J. Sci. Comput., 2024

A score-based filter for nonlinear data assimilation.
J. Comput. Phys., 2024

An End-to-End Deep Learning Method for Solving Nonlocal Allen-Cahn and Cahn-Hilliard Phase-Field Models.
CoRR, 2024

A Training-Free Conditional Diffusion Model for Learning Stochastic Dynamical Systems.
CoRR, 2024

Nonuniform random feature models using derivative information.
CoRR, 2024

A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics.
CoRR, 2024

SEMINAR: Search Enhanced Multi-modal Interest Network and Approximate Retrieval for Lifelong Sequential Recommendation.
CoRR, 2024

Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation.
CoRR, 2024

Online Differentiable Clustering for Intent Learning in Recommendation.
CoRR, 2024

Unify Graph Learning with Text: Unleashing LLM Potentials for Session Search.
Proceedings of the ACM on Web Conference 2024, 2024

A Multi-Granularity-Aware Aspect Learning Model for Multi-Aspect Dense Retrieval.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Multi-Intent Attribute-Aware Text Matching in Searching.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Exploring Multi-Scenario Multi-Modal CTR Prediction with a Large Scale Dataset.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

MLoRA: Multi-Domain Low-Rank Adaptive Network for CTR Prediction.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024

MoDULA: Mixture of Domain-Specific and Universal LoRA for Multi-Task Learning.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Towards Efficient Replay in Federated Incremental Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Towards More Realistic Chinese Spell Checking with New Benchmark and Specialized Expert Model.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

Modeling User Intent Beyond Trigger: Incorporating Uncertainty for Trigger-Induced Recommendation.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Power of Insensitivity: Fixing Threshold Truncation of Switch Buffer Management Policies.
Proceedings of the 24th IEEE International Symposium on Cluster, 2024

MoDE: A Mixture-of-Experts Model with Mutual Distillation among the Experts.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
A Probabilistic Scheme for Semilinear Nonlocal Diffusion Equations with Volume Constraints.
SIAM J. Numer. Anal., December, 2023

Level Set Learning with Pseudoreversible Neural Networks for Nonlinear Dimension Reduction in Function Approximation.
SIAM J. Sci. Comput., June, 2023

Improving the Expressive Power of Deep Neural Networks through Integral Activation Transform.
CoRR, 2023

Making Large Language Models Better Knowledge Miners for Online Marketing with Progressive Prompting Augmentation.
CoRR, 2023

ULMA: Unified Language Model Alignment with Demonstration and Point-wise Human Preference.
CoRR, 2023

PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation.
CoRR, 2023

From Beginner to Expert: Modeling Medical Knowledge into General LLMs.
CoRR, 2023

PrivateLoRA For Efficient Privacy Preserving LLM.
CoRR, 2023

MultiLoRA: Democratizing LoRA for Better Multi-Task Learning.
CoRR, 2023

Think-in-Memory: Recalling and Post-thinking Enable LLMs with Long-Term Memory.
CoRR, 2023

On the Opportunities of Green Computing: A Survey.
CoRR, 2023

Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation.
CoRR, 2023

An Ensemble Score Filter for Tracking High-Dimensional Nonlinear Dynamical Systems.
CoRR, 2023

AntM<sup>2</sup>C: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction.
CoRR, 2023

Harnessing the Power of David against Goliath: Exploring Instruction Data Generation without Using Closed-Source Models.
CoRR, 2023

A pseudo-reversible normalizing flow for stochastic dynamical systems with various initial distributions.
CoRR, 2023

Convergence analysis for a nonlocal gradient descent method via directional Gaussian smoothing.
CoRR, 2023

TransNet: Transferable Neural Networks for Partial Differential Equations.
CoRR, 2023

Movie Ticket, Popcorn, and Another Movie Next Weekend: Time-Aware Service Sequential Recommendation for User Retention.
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Beyond Two-Tower: Attribute Guided Representation Learning for Candidate Retrieval.
Proceedings of the ACM Web Conference 2023, 2023

Marketing Budget Allocation with Offline Constrained Deep Reinforcement Learning.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Connecting Unseen Domains: Cross-Domain Invariant Learning in Recommendation.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

GreenSeq: Automatic Design of Green Networks for Sequential Recommendation Systems.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Edge-cloud Collaborative Learning with Federated and Centralized Features.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Model-free Reinforcement Learning with Stochastic Reward Stabilization for Recommender Systems.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Commonsense Knowledge Graph towards Super APP and Its Applications in Alipay.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

GreenFlow: A Computation Allocation Framework for Building Environmentally Sound Recommendation System.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Rately: Accurate Data Center CC based on One-Way Delay.
Proceedings of the 29th IEEE International Conference on Parallel and Distributed Systems, 2023

Who Would be Interested in Services? An Entity Graph Learning System for User Targeting.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

GARCIA: Powering Representations of Long-tail Query with Multi-granularity Contrastive Learning.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Disentangled Interest importance aware Knowledge Graph Neural Network for Fund Recommendation.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

An Unified Search and Recommendation Foundation Model for Cold-Start Scenario.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Data Flow Risk Monitoring for Novel Power System Based on Bidirectional Interactive Protocol Traffic.
Proceedings of the Advances in Artificial Intelligence, Big Data and Algorithms - Proceedings of the 3rd International Conference on Artificial Intelligence, Big Data and Algorithms (CAIBDA 2023), 2023

Towards Better Hierarchical Text Classification with Data Generation.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Model Calibration of the Liquid Mercury Spallation Target using Evolutionary Neural Networks and Sparse Polynomial Expansions.
CoRR, 2022

Toward an Autonomous Workflow for Single Crystal Neutron Diffraction.
Proceedings of the Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation, 2022

PI3NN: Out-of-distribution-aware Prediction Intervals from Three Neural Networks.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Exploiting the Local Parabolic Landscapes of Adversarial Losses to Accelerate Black-Box Adversarial Attack.
Proceedings of the Computer Vision - ECCV 2022, 2022

Multiple Instance Learning for Uplift Modeling.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

See Clicks Differently: Modeling User Clicking Alternatively with Multi Classifiers for CTR Prediction.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
A Feynman-Kac based numerical method for the exit time probability of a class of transport problems.
J. Comput. Phys., 2021

Level set learning with pseudo-reversible neural networks for nonlinear dimension reduction in function approximation.
CoRR, 2021

PI3NN: Prediction intervals from three independently trained neural networks.
CoRR, 2021

A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models.
CoRR, 2021

Enabling long-range exploration in minimization of multimodal functions.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Electrohydrodynamically Printed Multicolor Perovskite Image Sensor Array.
Proceedings of the 16th IEEE International Conference on Nano/Micro Engineered and Molecular Systems, 2021

A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Scalable Deep-Learning-Accelerated Topology Optimization for Additively Manufactured Materials.
CoRR, 2020

AdaDGS: An adaptive black-box optimization method with a nonlocal directional Gaussian smoothing gradient.
CoRR, 2020

Accelerating Reinforcement Learning with a Directional-Gaussian-Smoothing Evolution Strategy.
CoRR, 2020

A Scalable Evolution Strategy with Directional Gaussian Smoothing for Blackbox Optimization.
CoRR, 2020

Hubble: An Industrial System for Audience Expansion in Mobile Marketing.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Two-Stage Audience Expansion for Financial Targeting in Marketing.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019
A Domain Decomposition Model Reduction Method for Linear Convection-Diffusion Equations with Random Coefficients.
SIAM J. Sci. Comput., 2019

An Improved Discrete Least-Squares/Reduced-Basis Method for Parameterized Elliptic PDEs.
J. Sci. Comput., 2019

Learning nonlinear level sets for dimensionality reduction in function approximation.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2017
Analysis of quasi-optimal polynomial approximations for parameterized PDEs with deterministic and stochastic coefficients.
Numerische Mathematik, 2017

2016
Hyperspherical Sparse Approximation Techniques for High-Dimensional Discontinuity Detection.
SIAM Rev., 2016

Accelerating Stochastic Collocation Methods for Partial Differential Equations with Random Input Data.
SIAM/ASA J. Uncertain. Quantification, 2016

Numerical methods for a class of nonlocal diffusion problems with the use of backward SDEs.
Comput. Math. Appl., 2016

Explicit cost bounds of stochastic Galerkin approximations for parameterized PDEs with random coefficients.
Comput. Math. Appl., 2016

2015
A Hyperspherical Adaptive Sparse-Grid Method for High-Dimensional Discontinuity Detection.
SIAM J. Numer. Anal., 2015

2014
A Hybrid Sparse-Grid Approach for Nonlinear Filtering Problems Based on Adaptive-Domain of the Zakai Equation Approximations.
SIAM/ASA J. Uncertain. Quantification, 2014

An adaptive sparse-grid iterative ensemble Kalman filter approach for parameter field estimation.
Int. J. Comput. Math., 2014

Stochastic finite element methods for partial differential equations with random input data.
Acta Numer., 2014

2012
Error Analysis of a Stochastic Collocation Method for Parabolic Partial Differential Equations with Random Input Data.
SIAM J. Numer. Anal., 2012

2010
A Stable Multistep Scheme for Solving Backward Stochastic Differential Equations.
SIAM J. Numer. Anal., 2010

2008
Services Characterization with Statistical Study on Existing Web Services.
Proceedings of the 2008 IEEE International Conference on Web Services (ICWS 2008), 2008

A New Approach to Web Services Characterization.
Proceedings of the 3rd IEEE Asia-Pacific Services Computing Conference, 2008


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