Liu, Chenghao

31 publications

NeurIPS 2025 Fast Projection-Free Approach (without Optimization Oracle) for Optimization over Compact Convex Set Chenghao Liu, Enming Liang, Minghua Chen

ICML 2025 Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts Xu Liu, Juncheng Liu, Gerald Woo, Taha Aksu, Yuxuan Liang, Roger Zimmermann, Chenghao Liu, Junnan Li, Silvio Savarese, Caiming Xiong, Doyen Sahoo

NeurIPS 2025 Multi-Scale Finetuning for Encoder-Based Time Series Foundation Models Zhongzheng Qiao, Chenghao Liu, Yiming Zhang, Ming Jin, Quang Pham, Qingsong Wen, Ponnuthurai Nagaratnam Suganthan, Xudong Jiang, Savitha Ramasamy

NeurIPS 2025 ShapeX: Shapelet-Driven Post Hoc Explanations for Time Series Classification Models Bosong Huang, Ming Jin, Yuxuan Liang, Johan Barthelemy, Debo Cheng, Qingsong Wen, Chenghao Liu, Shirui Pan

TMLR 2025 UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting Juncheng Liu, Chenghao Liu, Gerald Woo, Yiwei Wang, Bryan Hooi, Caiming Xiong, Doyen Sahoo

ICML 2025 VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters Mouxiang Chen, Lefei Shen, Zhuo Li, Xiaoyun Joy Wang, Jianling Sun, Chenghao Liu

ICML 2024 Characterizing ResNet’s Universal Approximation Capability Chenghao Liu, Enming Liang, Minghua Chen

NeurIPSW 2024 GIFT-Eval: A Benchmark for General Time Series Forecasting Model Evaluation Taha Aksu, Gerald Woo, Juncheng Liu, Xu Liu, Chenghao Liu, Silvio Savarese, Caiming Xiong, Doyen Sahoo

ICML 2024 Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank Mouxiang Chen, Chenghao Liu, Zemin Liu, Zhuo Li, Jianling Sun

NeurIPSW 2024 Mixture of Experts for Time Series Foundation Models Xu Liu, Juncheng Liu, Gerald Woo, Taha Aksu, Chenghao Liu, Silvio Savarese, Caiming Xiong, Doyen Sahoo

ICML 2024 ReLU Network with Width $d+\mathcal{O}(1)$ Can Achieve Optimal Approximation Rate Chenghao Liu, Minghua Chen

NeurIPS 2024 Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting Qingxiang Liu, Xu Liu, Chenghao Liu, Qingsong Wen, Yuxuan Liang

NeurIPSW 2024 UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting Juncheng Liu, Chenghao Liu, Gerald Woo, Yiwei Wang, Bryan Hooi, Caiming Xiong, Doyen Sahoo

ICML 2024 Unified Training of Universal Time Series Forecasting Transformers Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, Doyen Sahoo

IJCAI 2023 FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer Chenghao Liu, Xiaoyang Qu, Jianzong Wang, Jing Xiao

ICML 2023 Learning Deep Time-Index Models for Time Series Forecasting Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven Hoi

ICLR 2023 Learning Fast and Slow for Online Time Series Forecasting Quang Pham, Chenghao Liu, Doyen Sahoo, Steven Hoi

MLOSS 2023 Merlion: End-to-End Machine Learning for Time Series Aadyot Bhatnagar, Paul Kassianik, Chenghao Liu, Tian Lan, Wenzhuo Yang, Rowan Cassius, Doyen Sahoo, Devansh Arpit, Sri Subramanian, Gerald Woo, Amrita Saha, Arun Kumar Jagota, Gokulakrishnan Gopalakrishnan, Manpreet Singh, K C Krithika, Sukumar Maddineni, Daeki Cho, Bo Zong, Yingbo Zhou, Caiming Xiong, Silvio Savarese, Steven Hoi, Huan Wang

ICLR 2022 CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven Hoi

ICLR 2022 Continual Normalization: Rethinking Batch Normalization for Online Continual Learning Quang Pham, Chenghao Liu, Steven Hoi

NeurIPS 2022 LBD: Decouple Relevance and Observation for Individual-Level Unbiased Learning to Rank Mouxiang Chen, Chenghao Liu, Zemin Liu, Jianling Sun

ICLR 2021 Contextual Transformation Networks for Online Continual Learning Quang Pham, Chenghao Liu, Doyen Sahoo, Steven Hoi

NeurIPS 2021 DualNet: Continual Learning, Fast and Slow Quang Pham, Chenghao Liu, Steven C. Hoi

IJCAI 2021 Node-Wise Localization of Graph Neural Networks Zemin Liu, Yuan Fang, Chenghao Liu, Steven C. H. Hoi

AAAI 2021 Relative and Absolute Location Embedding for Few-Shot Node Classification on Graph Zemin Liu, Yuan Fang, Chenghao Liu, Steven C. H. Hoi

ECCV 2020 Adaptive Task Sampling for Meta-Learning Chenghao Liu, Zhihao Wang, Doyen Sahoo, Yuan Fang Kun Zhang, Steven C.H. Hoi

AAAI 2019 Discrete Social Recommendation Chenghao Liu, Xin Wang, Tao Lu, Wenwu Zhu, Jianling Sun, Steven C. H. Hoi

AAAI 2018 Unified Locally Linear Classifiers with Diversity-Promoting Anchor Points Chenghao Liu, Teng Zhang, Peilin Zhao, Jianling Sun, Steven C. H. Hoi

MLJ 2017 Collaborative Topic Regression for Online Recommender Systems: An Online and Bayesian Approach Chenghao Liu, Tao Jin, Steven C. H. Hoi, Peilin Zhao, Jianling Sun

IJCAI 2017 Locally Linear Factorization Machines Chenghao Liu, Teng Zhang, Peilin Zhao, Jun Zhou, Jianling Sun

AAAI 2016 Online ARIMA Algorithms for Time Series Prediction Chenghao Liu, Steven C. H. Hoi, Peilin Zhao, Jianling Sun