We stand with Ukraine

We stand with Ukraine

Huanyu Zhang

This page is a disambiguation page, it actually contains mutiple papers from persons of the same or a similar name.

Bibliography

2025

TimeRAF: Retrieval-Augmented Foundation Model for Zero-Shot Time Series Forecasting.

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IEEE Trans. Knowl. Data Eng., September, 2025

Memory-Efficient Differentially Private Training with Gradient Random Projection.

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Murali Annavaram

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Meisam Razaviyayn

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CoRR, June, 2025

A Call for New Recipes to Enhance Spatial Reasoning in MLLMs.

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CoRR, April, 2025

MM-RLHF: The Next Step Forward in Multimodal LLM Alignment.

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CoRR, February, 2025

Imagine while Reasoning in Space: Multimodal Visualization-of-Thought.

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CoRR, January, 2025

Revisit of the Temperature and Emissivity Separation (TES) Algorithm Toward Model Refinement.

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Kanishka Mallick

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Patrik Hitzelberger

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Yuanliang Cheng

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IEEE Trans. Geosci. Remote. Sens., 2025

A New Cloud Base Height Retrieval Method and Its Application in Cloudy-Sky Surface Downwelling Longwave Radiation Estimation.

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IEEE Trans. Geosci. Remote. Sens., 2025

Semantic relation-aware graph attention network with noise augmented layer-wise contrastive learning for recommendation.

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Knowl. Based Syst., 2025

A Plug-in Critiquing Approach for Knowledge Graph Recommendation Systems via Representative Sampling.

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Proceedings of the ACM on Web Conference 2025, 2025

MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?

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Shuangqing Zhang

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Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

LogoRA: Local-Global Representation Alignment for Robust Time Series Classification.

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IEEE Trans. Knowl. Data Eng., December, 2024

Contraction of Locally Differentially Private Mechanisms.

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IEEE J. Sel. Areas Inf. Theory, 2024

Knowledge-aware fine-grained attention networks with refined knowledge graph embedding for personalized recommendation.

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Expert Syst. Appl., 2024

Contrastive multi-interest graph attention network for knowledge-aware recommendation.

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Expert Syst. Appl., 2024

TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecasting.

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CoRR, 2024

MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?

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Shuangqing Zhang

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CoRR, 2024

Causal Feature-Enhanced Collaborative Filtering Algorithm.

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Proceedings of the International Joint Conference on Neural Networks, 2024

Statler: State-Maintaining Language Models for Embodied Reasoning.

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Tianchong Jiang

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Matthew R. Walter

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Semantic Feature Compression and Adaption for Latency-Sensitive Semantic Communication.

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Proceedings of the IEEE Globecom Workshops 2024, 2024

2023

RIECN: learning relation-based interactive embedding convolutional network for knowledge graph.

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Neural Comput. Appl., April, 2023

Research on Communication Technology of OPGW Line in Distribution Network under Interference Environment.

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EAI Endorsed Trans. Scalable Inf. Syst., 2023

Generalized Linear Models in Non-interactive Local Differential Privacy with Public Data.

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J. Mach. Learn. Res., 2023

KGAN: Knowledge Grouping Aggregation Network for course recommendation in MOOCs.

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Expert Syst. Appl., 2023

DP-HyPO: An Adaptive Private Hyperparameter Optimization Framework.

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CoRR, 2023

Challenges towards the Next Frontier in Privacy.

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CoRR, 2023

DP-HyPO: An Adaptive Private Framework for Hyperparameter Optimization.

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Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Federated Linear Contextual Bandits with User-level Differential Privacy.

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Meisam Hejazinia

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Proceedings of the International Conference on Machine Learning, 2023

2022

Retrieval of Daytime Surface Upward Longwave Radiation Under All-Sky Conditions With Remote Sensing and Meteorological Reanalysis Data.

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IEEE Trans. Geosci. Remote. Sens., 2022

Analytical Composition of Differential Privacy via the Edgeworth Accountant.

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CoRR, 2022

Maxwell's Demon in Tail-tolerant, Resource-efficient Serverless Computing.

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Proceedings of the 28th IEEE International Conference on Parallel and Distributed Systems, 2022

Improved Rates for Differentially Private Stochastic Convex Optimization with Heavy-Tailed Data.

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Proceedings of the International Conference on Machine Learning, 2022

Robust Estimation for Random Graphs.

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[DOI]

Jayadev Acharya

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Ananda Theertha Suresh

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Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

INFless: a native serverless system for low-latency, high-throughput inference.

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Proceedings of the ASPLOS '22: 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Lausanne, Switzerland, 28 February 2022, 2022

2021

Statistical Inference in the Differential Privacy Model.

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CoRR, 2021

Wide Network Learning with Differential Privacy.

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Meisam Hejazinia

CoRR, 2021

Joint Design of Transmit Waveforms and Receive Filters for MIMO Radar via Manifold Optimization.

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CoRR, 2021

Globally Convergent Algorithms for Learning Multivariate Generalized Gaussian Distributions.

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Proceedings of the IEEE Statistical Signal Processing Workshop, 2021

Robust Testing and Estimation under Manipulation Attacks.

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[DOI]

Jayadev Acharya

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Proceedings of the 38th International Conference on Machine Learning, 2021

Differentially Private Assouad, Fano, and Le Cam.

[BibT_eX]

[DOI]

Jayadev Acharya

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Proceedings of the Algorithmic Learning Theory, 2021

2020

INSPECTRE: Privately Estimating the Unseen.

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[DOI]

Jayadev Acharya

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J. Priv. Confidentiality, 2020

Privately Learning Markov Random Fields.

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Janardhan Kulkarni

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Zhiwei Steven Wu

Proceedings of the 37th International Conference on Machine Learning, 2020

Locally Private Hypothesis Selection.

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Janardhan Kulkarni

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Aleksandar Nikolov

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Zhiwei Steven Wu

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Proceedings of the Conference on Learning Theory, 2020

2019

Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled Data.

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CoRR, 2019

Hadamard Response: Estimating Distributions Privately, Efficiently, and with Little Communication.

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[DOI]

Jayadev Acharya

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Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Communication Efficient, Sample Optimal, Linear Time Locally Private Discrete Distribution Estimation.

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[DOI]

Jayadev Acharya

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CoRR, 2018

Differentially Private Testing of Identity and Closeness of Discrete Distributions.

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[DOI]

Jayadev Acharya

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Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016

Reliability and longer range for low power transmitters with on demand network MIMO.

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[DOI]

Mary Ann Weitnauer

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Gedeon Nyengele

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Sajith Mohan Chakkedath

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Proceedings of the 2016 IEEE International Conference on RFID, 2016

Design and implementation of device-to-device software-defined networks.

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Proceedings of the 2016 IEEE International Conference on Communications, 2016

2015

Demo: Software-Defined Device to Device Communication in Multiple Cells.

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Proceedings of the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing, 2015

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