Hu, Yifan

24 publications

AAAI 2025 Adaptive Multi-Scale Decomposition Framework for Time Series Forecasting Yifan Hu, Peiyuan Liu, Peng Zhu, Dawei Cheng, Tao Dai

ICML 2025 Efficiently Serving Large Multimodal Models Using EPD Disaggregation Gursimran Singh, Xinglu Wang, Yifan Hu, Timothy Tin Long Yu, Linzi Xing, Wei Jiang, Zhefeng Wang, Bai Xiaolong, Yi Li, Ying Xiong, Yong Zhang, Zhenan Fan

AISTATS 2025 Global Group Fairness in Federated Learning via Function Tracking Yves Rychener, Daniel Kuhn, Yifan Hu

ICML 2025 MPO: An Efficient Post-Processing Framework for Mixing Diverse Preference Alignment Tianze Wang, Dongnan Gui, Yifan Hu, Shuhang Lin, Linjun Zhang

AAAI 2025 Multi-Modal and Multi-Scale Spatial Environment Understanding for Immersive Visual Text-to-Speech Rui Liu, Shuwei He, Yifan Hu, Haizhou Li

ICML 2025 TimeBridge: Non-Stationarity Matters for Long-Term Time Series Forecasting Peiyuan Liu, Beiliang Wu, Yifan Hu, Naiqi Li, Tao Dai, Jigang Bao, Shu-Tao Xia

ICML 2025 TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting Yifan Hu, Guibin Zhang, Peiyuan Liu, Disen Lan, Naiqi Li, Dawei Cheng, Tao Dai, Shu-Tao Xia, Shirui Pan

NeurIPS 2025 Vanish into Thin Air: Cross-Prompt Universal Adversarial Attacks for SAM2 Ziqi Zhou, Yifan Hu, Yufei Song, Zijing Li, Shengshan Hu, Leo Yu Zhang, Dezhong Yao, Long Zheng, Hai Jin

ICMLW 2024 Bilevel Optimization with Lower-Level Contextual MDPs Vinzenz Thoma, Barna Pásztor, Andreas Krause, Giorgia Ramponi, Yifan Hu

NeurIPS 2024 Contextual Bilevel Reinforcement Learning for Incentive Alignment Vinzenz Thoma, Barna Pasztor, Andreas Krause, Giorgia Ramponi, Yifan Hu

AISTATS 2024 Distributionally Robust Model-Based Reinforcement Learning with Large State Spaces Shyam Sundhar Ramesh, Pier Giuseppe Sessa, Yifan Hu, Andreas Krause, Ilija Bogunovic

AAAI 2024 Emotion Rendering for Conversational Speech Synthesis with Heterogeneous Graph-Based Context Modeling Rui Liu, Yifan Hu, Yi Ren, Xiang Yin, Haizhou Li

AISTATS 2024 Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax Optimization Siqi Zhang, Yifan Hu, Liang Zhang, Niao He

NeurIPS 2024 Group Robust Preference Optimization in Reward-Free RLHF Shyam Sundhar Ramesh, Yifan Hu, Iason Chaimalas, Viraj Mehta, Pier Giuseppe Sessa, Haitham Bou Ammar, Ilija Bogunovic

NeurIPS 2024 Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data Xuxing Chen, Abhishek Roy, Yifan Hu, Krishnakumar Balasubramanian

NeurIPS 2023 Contextual Stochastic Bilevel Optimization Yifan Hu, Jie Wang, Yao Xie, Andreas Krause, Daniel Huhn

ICCV 2023 Deep Directly-Trained Spiking Neural Networks for Object Detection Qiaoyi Su, Yuhong Chou, Yifan Hu, Jianing Li, Shijie Mei, Ziyang Zhang, Guoqi Li

NeurIPSW 2023 Distributionally Robust Model-Based Reinforcement Learning with Large State Spaces Shyam Sundhar Ramesh, Pier Giuseppe Sessa, Yifan Hu, Andreas Krause, Ilija Bogunovic

NeurIPSW 2023 Stochastic Optimization Under Hidden Convexity Ilyas Fatkhullin, Niao He, Yifan Hu

NeurIPSW 2022 Uniform Convergence and Generalization for Nonconvex Stochastic Minimax Problems Siqi Zhang, Yifan Hu, Liang Zhang, Niao He

AAAI 2021 Going Deeper with Directly-Trained Larger Spiking Neural Networks Hanle Zheng, Yujie Wu, Lei Deng, Yifan Hu, Guoqi Li

NeurIPS 2021 On the Bias-Variance-Cost Tradeoff of Stochastic Optimization Yifan Hu, Xin Chen, Niao He

NeurIPS 2020 Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning Yifan Hu, Siqi Zhang, Xin Chen, Niao He

AAAI 2018 HARP: Hierarchical Representation Learning for Networks Haochen Chen, Bryan Perozzi, Yifan Hu, Steven Skiena