Publications

@misc{ankireddy2026timesqueeze4786,
  title = {TimeSqueeze: Dynamic Patching for Efficient Time Series Forecasting},
  author = {Sravan Kumar Ankireddy and Nikita Seleznev and Nam H. Nguyen and Yulun Wu and Senthil Kumar and Furong Huang and C. Bayan Bruss},
  year = {2026},
  eprint = {2603.11352},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.11352},
}

@misc{chen2025bridginge7fe,
  title = {Bridging the Divide: End-to-End Sequence-Graph Learning},
  author = {Yuen Chen and Yulun Wu and Samuel Sharpe and Igor Melnyk and Nam H. Nguyen and Furong Huang and C. Bayan Bruss and Rizal Fathony},
  year = {2025},
  eprint = {2510.25126},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.25126},
}

@inproceedings{mcclellan2025penguin7ada,
  title = {PEnGUiN: Partially Equivariant Graph NeUral Networks for Sample Efficient MARL},
  author = {Greyson Brothers Joshua McClellan and Furong Huang and Pratap Tokekar},
  booktitle = {Reinforcement Learning Conference (RLC), 2025},
  year = {2025},
  eprint = {2503.15615},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.15615},
}

@inproceedings{zhang2025statistical638a,
  title = {Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayesian Theory},
  author = {Zhi Zhang and Chris Chow and Yasi Zhang and Yanchao Sun and Haochen Zhang and Eric Hanchen Jiang and Han Liu and Furong Huang and Yuchen Cui and Oscar Hernan Madrid Padilla},
  booktitle = {The 28th International Conference on Artificial Intelligence and Statistics (AISTATS), 2025},
  year = {2025},
  eprint = {2411.00401},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2411.00401},
}

@inproceedings{liu2025world9aa2,
  title = {World Models with Hints of Large Language Models for Goal Achieving},
  author = {Zeyuan Liu and Maggie Z. Huan and Xiyao Wang and Jiafei Lyu and Jian Tao and Xiu Li and Furong Huang and Huazhe Xu},
  booktitle = {The 2025 Annual Conference of the Nations of the Americas Chapter of the ACL (NAACL), 2025},
  year = {2025},
  eprint = {2406.07381},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2406.07381},
}

@inproceedings{ding2025onlyb70c,
  title = {You Only Train Once: Efficient Tokenizer Selection for Arithmetic in Language Models},
  author = {Mucong Ding and Sean Michael McLeish and Kazem Meidani and Igor Melnyk and Nam H Nguyen and C. Bayan Bruss and Furong Huang},
  booktitle = {Tokenization Workshop (TokShop), ICML 2025},
  year = {2025},
  url = {https://openreview.net/forum?id=syvdPYbdTI},
}

@inproceedings{yue2025zero4e17,
  title = {Zero-Shot Vision Encoder Grafting via LLM Surrogates},
  author = {Kaiyu Yue and Vasu Singla and Menglin Jia and John Kirchenbauer and Rifaa Qadri and Zikui Cai and Abhinav Bhatele and Furong Huang and Tom Goldstein},
  booktitle = {International Conference on Computer Vision (ICCV), 2025},
  year = {2025},
  eprint = {2505.22664},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2505.22664},
}

@article{ghosal2024surveyfe94,
  title = {A Survey on the Possibilities \& Impossibilities of AI-generated Text Detection},
  author = {Soumya Suvra Ghosal and Souradip Chakraborty and Jonas Geiping and Furong Huang and Dinesh Manocha and Amrit Bedi},
  journal = {Transactions on Machine Learning Research (TMLR), 2024},
  year = {2024},
  eprint = {2310.15264},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2310.15264},
}

@inproceedings{sang2024balancingbd0e,
  title = {Balancing Label Imbalance in Federated Environments Using Only Mixup and Artificially-Labeled Noise},
  author = {Kyle Sang and Tahseen Rabbani and Furong Huang},
  booktitle = {4th International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI), 2024},
  year = {2024},
  eprint = {2409.13235},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.13235},
}

@inproceedings{ding2024easy2hard55f2,
  title = {Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization},
  author = {Mucong Ding and Chenghao Deng and Jocelyn Choo and Zichu Wu and Aakriti Agrawal and Avi Schwarzschild and Tianyi Zhou and Tom Goldstein and John Langford and Anima Anandkumar and Furong Huang},
  booktitle = {The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, 2024},
  year = {2024},
  eprint = {2409.18433},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.18433},
}

@inproceedings{agrawal2024ensemw2s699b,
  title = {EnsemW2S: Can an Ensemble of LLMs be Leveraged to Obtain a Stronger LLM?},
  author = {Aakriti Agrawal and Mucong Ding and Zora Che and Chenghao Deng and Anirudh Satheesh and John Langford and Furong Huang},
  booktitle = {Safe Generative AI Workshop, NeurIPS 2024},
  year = {2024},
}

@inproceedings{bornstein2024fact64b9,
  title = {FACT or Fiction: Can Truthful Mechanisms Eliminate Federated Free Riding?},
  author = {Marco Bornstein and Amrit Bedi and Abdirisak Mohamed and Furong Huang},
  booktitle = {The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024},
  year = {2024},
  eprint = {2405.13879},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2405.13879},
}

@misc{liu2024hashevictb2d1,
  title = {HashEvict: A Pre-Attention KV Cache Eviction Strategy using Locality-Sensitive Hashing},
  author = {Minghui Liu and Tahseen Rabbani and Tony O'Halloran and Ananth Sankaralingam and Mary-Anne Hartley and Furong Huang and Cornelia Fermüller and Yiannis Aloimonos},
  year = {2024},
  eprint = {2412.16187},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.16187},
}

@inproceedings{rabbani2024tells8423,
  title = {LSH-E Tells You What To Discard: An Adaptive Locality-Sensitive Strategy for KV Cache Compression},
  author = {Tahseen Rabbani and Minghui Liu and Tony O'Halloran and Ananth Sankaralingam and Mary-Anne Hartley and Furong Huang},
  booktitle = {Workshop on Machine Learning and Compression, NeurIPS 2024},
  year = {2024},
}

@inproceedings{an2024moref3dd,
  title = {More Context, Less Distraction: Zero-shot Visual Classification by Inferring and Conditioning on Contextual Attributes},
  author = {Bang An and Sicheng Zhu and Michael-Andrei Panaitescu-Liess and Chaithanya Kumar Mummadi and Furong Huang},
  booktitle = {The Twelfth International Conference on Learning Representations (ICLR), 2024},
  year = {2024},
  eprint = {2308.01313},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2308.01313},
}

@inproceedings{zhou2024multi5172,
  title = {Multi-Stage Balanced Distillation: Addressing Long-Tail Challenges in Sequence-Level Knowledge Distillation},
  author = {Yuhang Zhou and Jing Zhu and Paiheng Xu and Xiaoyu Liu and Xiyao Wang and Danai Koutra and Wei Ai and Furong Huang},
  booktitle = {The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024},
  year = {2024},
  eprint = {2406.13114},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2406.13114},
}

@misc{li2024political0b36,
  title = {Political-LLM: Large Language Models in Political Science},
  author = {Lincan Li and Jiaqi Li and Catherine Chen and Fred Gui and Hongjia Yang and Chenxiao Yu and Zhengguang Wang and Jianing Cai and Junlong Aaron Zhou and Bolin Shen and Alex Qian and Weixin Chen and Zhongkai Xue and Lichao Sun and Lifang He and Hanjie Chen and Kaize Ding and Zijian Du and Fangzhou Mu and Jiaxin Pei and Jieyu Zhao and Swabha Swayamdipta and Willie Neiswanger and Hua Wei and Xiyang Hu and Shixiang Zhu and Tianlong Chen and Yingzhou Lu and Yang Shi and Lianhui Qin and Tianfan Fu and Zhengzhong Tu and Yuzhe Yang and Jaemin Yoo and Jiaheng Zhang and Ryan Rossi and Liang Zhan and Liang Zhao and Emilio Ferrara and Yan Liu and Furong Huang and Xiangliang Zhang and Lawrence Rothenberg and Shuiwang Ji and Philip S. Yu and Yue Zhao and Yushun Dong},
  year = {2024},
  eprint = {2412.06864},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.06864},
}

@inproceedings{zheng2024premierdd07,
  title = {Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss},
  author = {Ruijie Zheng and Yongyuan Liang and Xiyao Wang and Shuang Ma and Hal Daume III and Huazhe Xu and John Langford and Praveen Palanisamy and Kalyan Shankar Basu and Furong Huang},
  booktitle = {Proceedings of the 41st International Conference on Machine Learning (ICML), 2024},
  year = {2024},
  eprint = {2402.06187},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2402.06187},
}

@inproceedings{zheng2024prise34fa,
  title = {PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control},
  author = {Ruijie Zheng and Ching-An Cheng and Hal Daume III and Furong Huang and Andrey Kolobov},
  booktitle = {Proceedings of the 41st International Conference on Machine Learning (ICML), 2024},
  year = {2024},
  eprint = {2402.10450},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2402.10450},
}

@inproceedings{ding2024saflex00a5,
  title = {SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation},
  author = {Mucong Ding and Bang An and Yuancheng Xu and Anirudh Satheesh and Furong Huang},
  booktitle = {The Twelfth International Conference on Learning Representations (ICLR), 2024},
  year = {2024},
  eprint = {2410.02512},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2410.02512},
}

@inproceedings{bornstein2024shrinking6cf5,
  title = {Shrinking the Size of Extreme Multi-Label Classification},
  author = {Marco Bornstein and Tahseen Rabbani and Brian Joseph Gravelle and Furong Huang},
  booktitle = {Workshop on Machine Learning and Compression, NeurIPS 2024},
  year = {2024},
}

@inproceedings{bansal2023cold419d,
  title = {Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise},
  author = {Arpit Bansal and Eitan Borgnia and Hong-Min Chu and Jie S. Li and Hamid Kazemi and Furong Huang and Micah Goldblum and Jonas Geiping and Tom Goldstein},
  booktitle = {The Thirty-seventh Annual Conference on Neural Information Processing Systems (NeurIPS), 2023},
  year = {2023},
  eprint = {2208.09392},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2208.09392},
}

@inproceedings{zheng2023model2d7a,
  title = {Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function},
  author = {Ruijie Zheng and Xiyao Wang and Huazhe Xu and Furong Huang},
  booktitle = {The Eleventh International Conference on Learning Representations (ICLR), 2023},
  year = {2023},
  eprint = {2302.01244},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2302.01244},
}

@inproceedings{rabbani2023largeb1a5,
  title = {Large-Scale Distributed Learning via Private On-Device LSH},
  author = {Tahseen Rabbani and Marco Bornstein and Furong Huang},
  booktitle = {The Thirty-seventh Annual Conference on Neural Information Processing Systems (NeurIPS), 2023},
  year = {2023},
  eprint = {2306.02563},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2306.02563},
}

@inproceedings{wang2023liveb7ff,
  title = {Live in the Moment: Learning Dynamics Model Adapted to Evolving Policy},
  author = {Xiyao Wang and Wichayaporn Wongkamjan and Furong Huang},
  booktitle = {Proceedings of the 40th International Conference on Machine Learning (ICML), 2023},
  year = {2023},
  eprint = {2207.12141},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2207.12141},
}

@inproceedings{an2023mentale6f0,
  title = {Mental Calibration: Discovering and Adjusting for Latent Factors Improves Zero-Shot Inference of CLIP},
  author = {Bang An and Sicheng Zhu and Michael-Andrei Panaitescu-Liess and Chaithanya Kumar Mummadi and Furong Huang},
  booktitle = {Workshop on Efficient Systems for Foundation Models (ES-FoMO), ICML 2023},
  year = {2023},
}

@inproceedings{rabbani2023pghashe17f,
  title = {PGHash: Large-Scale Distributed Learning via Private On-Device Locally Sensitive Hashing},
  author = {Tahseen Rabbani and Marco Bornstein and Furong Huang},
  booktitle = {Sparsity in Neural Networks 2023 workshop, ICLR 2023},
  year = {2023},
}

@inproceedings{chakraborty2023posterior45a8,
  title = {Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning},
  author = {Souradip Chakraborty and Amrit Bedi and Pratap Tokekar and Alec Koppel and Brian Sadler and Furong Huang and Dinesh Manocha},
  booktitle = {Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023},
  year = {2023},
  eprint = {2206.01162},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2206.01162},
}

@inproceedings{nguyen2023progressivelyeb94,
  title = {Progressively Efficient Communication},
  author = {Khanh Nguyen and Ruijie Zheng and Hal Daume III and Furong Huang and Karthik Narasimhan},
  booktitle = {Intrinsically Motivated Open-ended Learning (IMOL) Workshop, NeurIPS 2023},
  year = {2023},
}

@misc{zheng2023progressively1647,
  title = {Progressively Efficient Learning},
  author = {Ruijie Zheng and Khanh Nguyen and Hal Daume III and Furong Huang and Karthik Narasimhan},
  howpublished = {arXiv preprint arXiv:2310.13004},
  year = {2023},
  eprint = {2310.13004},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2310.13004},
}

@inproceedings{bornstein2023realfm6941,
  title = {RealFM: A Realistic Mechanism to Incentivize Data Contribution and Device Participation},
  author = {Marco Bornstein and Amrit Bedi and Anit Kumar Sahu and Furqan Khan and Furong Huang},
  booktitle = {Workshop on Federated Learning in the Age of Foundation Models (FL@FM-NeurIPS'23), NeurIPS 2023},
  year = {2023},
  eprint = {2310.13681},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2310.13681},
}

@inproceedings{ding2023reviving2693,
  title = {Reviving Shift Equivariance in Vision Transformers},
  author = {Peijian Ding and Davit Soselia and Thomas Armstrong and Jiahao Su and Furong Huang},
  booktitle = {The Second Workshop on Spurious Correlations, Invariance and Stability (SCIS), ICML 2023},
  year = {2023},
  eprint = {2306.07470},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2306.07470},
}

@inproceedings{sun2023smart65af,
  title = {SMART: Self-supervised Multi-task pretrAining with contRol Transformers},
  author = {Yanchao Sun and Shuang Ma and Ratnesh Madaan and Rogerio Bonatti and Furong Huang and Ashish Kapoor},
  booktitle = {The Eleventh International Conference on Learning Representations (ICLR), 2023},
  year = {2023},
  eprint = {2301.09816},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2301.09816},
}

@inproceedings{chakraborty2023steeringfc48,
  title = {STEERING: Stein Information Directed Exploration for Model-Based Reinforcement Learning},
  author = {Souradip Chakraborty and Amrit Singh Bedi and Alec Koppel and Mengdi Wang and Furong Huang and Dinesh Manocha},
  booktitle = {Proceedings of the 40th International Conference on Machine Learning (ICML), 2023},
  year = {2023},
  eprint = {2301.12038},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2301.12038},
}

@inproceedings{chakraborty2023steinfb5f,
  title = {Stein Information Directed Sampling for Efficient Exploration in Model-Based Reinforcement Learning},
  author = {Souradip Chakraborty and Amrit Singh Bedi and Alec Koppel and Furong Huang and Dinesh Manocha},
  booktitle = {Oral, AAAI Reinforcement Learning Ready for Production Workshop, 2023},
  year = {2023},
}

@inproceedings{bornstein2023swiftb0bb,
  title = {SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication},
  author = {Marco Bornstein and Tahseen Rabbani and Evan Wang and Amrit Singh Bedi and Furong Huang},
  booktitle = {The Eleventh International Conference on Learning Representations (ICLR), 2023},
  year = {2023},
  eprint = {2210.14026},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2210.14026},
}

@inproceedings{rabbani2022comfetchf98e,
  title = {Comfetch: Federated Learning of Large Networks on Memory-Constrained Clients via Sketching},
  author = {Tahseen Rabbani and Brandon Feng and Yifan Yang and Arjun Rajkumar and Amitabh Varshney and Furong Huang},
  booktitle = {Workshop on Trustable, Verifiable and Auditable Federated Learning, AAAI 2022},
  year = {2022},
  eprint = {2109.08346},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2109.08346},
}

@article{su2022compactaab3,
  title = {Compact Neural Architecture Designs by Tensor Representations},
  author = {Jiahao Su and Jingling Li and Xiaoyu Liu and Teresa Ranadive and Christopher Coley and Tai-Ching Tuan and Furong Huang},
  journal = {Frontiers in Artificial Intelligence-Machine Learning and Artificial Intelligence, 2022},
  year = {2022},
}

@inproceedings{borgnia2022instahide3575,
  title = {DP-InstaHide: Data Augmentations Provably Enhance Guarantees Against Dataset Manipulations},
  author = {Eitan Borgnia and Jonas Geiping and Valeriia Cherepanova and Liam H. Fowl and Arjun Gupta and Amin Ghiasi and Furong Huang and Micah Goldblum and Tom Goldstein},
  booktitle = {ML Safety workshop, NeurIPS 2022},
  year = {2022},
}

@inproceedings{bansal2022algorithm27ea,
  title = {End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking},
  author = {Arpit Bansal and Avi Schwarzschild and Eitan Borgnia and Zeyad Emam and Furong Huang and Micah Goldblum and Tom Goldstein},
  booktitle = {Neural Information Processing System (NeurIPS), 2022},
  year = {2022},
  eprint = {2202.05826},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2202.05826},
}

@misc{bornstein2022escaping5118,
  title = {Escaping From Saddle Points Using Asynchronous Coordinate Gradient Descent},
  author = {Marco Bornstein and Jin-Peng Liu and Jingling Li and Furong Huang},
  howpublished = {arXiv preprint arXiv:2211.09908},
  year = {2022},
  eprint = {2211.09908},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2211.09908},
}

@misc{bedi2022fedbcf732,
  title = {FedBC: Calibrating Global and Local Models via Federated Learning Beyond Consensus},
  author = {Amrit Singh Bedi and Chen Fan and Alec Koppel and Anit Kumar Sahu and Brian M Sadler and Furong Huang and Dinesh Manocha},
  howpublished = {arXiv preprint arXiv:2206.10815},
  year = {2022},
  eprint = {2206.10815},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2206.10815},
}

@inproceedings{su2022scaling2247,
  title = {Scaling-up Diverse Orthogonal Convolutional Networks by a Paraunitary Framework},
  author = {Jiahao Su and Wonmin Byeon and Furong Huang},
  booktitle = {Proceedings of the 39th International Conference on Machine Learning (ICML), 2022},
  year = {2022},
  eprint = {2106.09121},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2106.09121},
}

@inproceedings{ding2022sketch1a99,
  title = {Sketch-GNN: Efficient GNNs with Graph Size-Independent Scalability},
  author = {Mucong Ding and Tahseen Rabbani and Bang An and Evan Wang and Furong Huang},
  booktitle = {Neural Information Processing System (NeurIPS), 2022},
  year = {2022},
  eprint = {2406.15575},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2406.15575},
}

@inproceedings{ding2022sketch0670,
  title = {Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity},
  author = {Mucong Ding and Tahseen Rabbani and Bang An and Evan Wang and Furong Huang},
  booktitle = {GLFrontiers Workshop, NeurIPS 2022},
  year = {2022},
}

@article{bientinesi2022tensore94e,
  title = {Tensor Computations: Applications and Optimization},
  author = {Paolo Bientinesi and David Ham and Furong Huang and Paul HJ Kelly and P Saday Sadayappan and Edward Stow},
  year = {2022},
}

@inproceedings{sun2022transferbe1e,
  title = {Transfer RL across Observation Feature Spaces via Model-Based Regularization},
  author = {Yanchao Sun and Ruijie Zheng and Xiyao Wang and Andrew Cohen and Furong Huang},
  booktitle = {Tenth International Conference on Learning Representations (ICLR), 2022},
  year = {2022},
  eprint = {2201.00248},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2201.00248},
}

@inproceedings{liu2022tuformer1741,
  title = {Tuformer: Data-driven Design of Transformers for Improved Generalization or Efficiency},
  author = {Xiaoyu Liu and Jiahao Su and Furong Huang},
  booktitle = {Tenth International Conference on Learning Representations (ICLR), 2022},
  year = {2022},
  url = {https://openreview.net/pdf?id=V0A5g83gdQ_},
}

@inproceedings{levin2022where500b,
  title = {Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability},
  author = {Roman Levin and Manli Shu and Eitan Borgnia and Furong Huang and Micah Goldblum and Tom Goldstein},
  booktitle = {Neural Information Processing System (NeurIPS), 2022},
  year = {2022},
  eprint = {2108.01335},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2108.01335},
}

@inproceedings{ding2021closerf2c5,
  title = {A Closer Look at Distribution Shifts and Out-of-Distribution Generalization on Graphs},
  author = {Mucong Ding and Kezhi Kong and Jiuhai Chen and John Kirchenbauer and Micah Goldblum and David Wipf and Furong Huang and Tom Goldstein},
  booktitle = {Workshop on Distribution Shifts: Connecting Methods and Applications (DistShift), Spotlight, NeurIPS 2021},
  year = {2021},
}

@inproceedings{zhu2021adaptive1420,
  title = {Adaptive learning rates with maximum variation averaging},
  author = {Chen Zhu and Yu Cheng and Zhe Gan and Furong Huang and Jingjing Liu and Tom Goldstein},
  booktitle = {European Conference on Machine Learning},
  year = {2021},
}

@inproceedings{schwarzschild2021learnf6e7,
  title = {Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks},
  author = {Avi Schwarzschild and Eitan Borgnia and Arjun Gupta and Furong Huang and Uzi Vishkin and Micah Goldblum and Tom Goldstein},
  booktitle = {Neural Information Processing System (NeurIPS), 2021},
  year = {2021},
  eprint = {2106.04537},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2106.04537},
}

@misc{zeng2021certifieda883,
  title = {Certified defense via latent space randomized smoothing with orthogonal encoders},
  author = {Huimin Zeng and Jiahao Su and Furong Huang},
  howpublished = {arXiv preprint arXiv:2108.00491},
  year = {2021},
  eprint = {2108.00491},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2108.00491},
}

@misc{schwarzschild2021datasetsb2b4,
  title = {Datasets for studying generalization from easy to hard examples},
  author = {Avi Schwarzschild and Eitan Borgnia and Arjun Gupta and Arpit Bansal and Zeyad Emam and Furong Huang and Micah Goldblum and Tom Goldstein},
  howpublished = {arXiv preprint arXiv:2108.06011},
  year = {2021},
  eprint = {2108.06011},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2108.06011},
}

@misc{joo2021guided4e17,
  title = {Guided hyperparameter tuning through visualization and inference},
  author = {Hyekang Joo and Calvin Bao and Ishan Sen and Furong Huang and Leilani Battle},
  howpublished = {arXiv preprint arXiv:2105.11516},
  year = {2021},
  eprint = {2105.11516},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2105.11516},
}

@inproceedings{zhu2021maxva6871,
  title = {MaxVA: Fast Adaptation of Stepsizes by Maximizing Observed Variance of Gradients},
  author = {Chen Zhu and Yu Cheng and Zhe Gan and Furong Huang and Jingjing Liu and Tom Goldstein},
  booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2021},
  year = {2021},
  eprint = {2006.11918},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2006.11918},
}

@inproceedings{rabbani2021practical999f,
  title = {Practical and Fast Momentum-Based Power Methods},
  author = {Tahseen Rabbani and Apollo Jain and Arjun Rajkumar and Furong Huang},
  booktitle = {2nd Annual Conference on Mathematical and Scientific Machine Learning (MSML), Proceedings of Machine Learning Research vol 145:1-36, 2021},
  year = {2021},
  eprint = {2108.09264},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2108.09264},
}

@inproceedings{sun2021temple396e,
  title = {TempLe: Learning Template of Transitions for Sample Efficient Multi-Task RL},
  author = {Yanchao Sun and Xiangyu Yin and Furong Huang},
  booktitle = {35th AAAI conference on Artificial Intelligence (AAAI), 2021},
  year = {2021},
  eprint = {2002.06659},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2002.06659},
}

@inproceedings{zhu2021understandingc5a2,
  title = {Understanding the Generalization Benefit of Model Invariance from a Data Perspective},
  author = {Sicheng Zhu and Bang An and Furong Huang},
  booktitle = {Neural Information Processing System (NeurIPS), 2021},
  year = {2021},
  eprint = {2111.05529},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2111.05529},
}

@inproceedings{ding2021universal726c,
  title = {VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization},
  author = {Mucong Ding and Kezhi Kong and Jingling Li and Chen Zhu and John Dickerson and Furong Huang and Tom Goldstein},
  booktitle = {Neural Information Processing System (NeurIPS), 2021},
  year = {2021},
  eprint = {2110.14363},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2110.14363},
}

@inproceedings{decarolis2020differentially5836,
  title = {An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm},
  author = {Chris Decarolis and Mukul Ram and Seyed Esmaeili and Yu-Xiang Wang and Furong Huang},
  booktitle = {Proceedings of the 37th International Conference on Machine Learning (ICML), 2020},
  year = {2020},
  eprint = {1805.10341},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/1805.10341},
}

@inproceedings{su2020arma15da,
  title = {ARMA Nets: Expanding Receptive Field for Dense Prediction},
  author = {Jiahao Su and Shiqi Wang and Furong Huang},
  booktitle = {Neural Information Processing System (NeurIPS), 2020},
  year = {2020},
  eprint = {2002.11609},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2002.11609},
}

@article{huang2020convolutional485f,
  title = {Convolutional Sparse Coding},
  author = {Furong Huang},
  journal = {Computer Vision: A Reference Guide},
  year = {2020},
}

@inproceedings{su2020convolutional252b,
  title = {Convolutional Tensor-Train LSTM for Spatio-Temporal Learning},
  author = {Jiahao Su and Wonmin Byeon and Jean Kossaifi and Furong Huang and Jan Kautz and Anima Anandkumar},
  booktitle = {Neural Information Processing System (NeurIPS), 2020},
  year = {2020},
  eprint = {2002.09131},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2002.09131},
}

@article{giraud2020dagstuhl39bd,
  title = {Dagstuhl Reports, Vol. 10, Issue 3 ISSN 2192-5283},
  author = {Luc Giraud and Ulrich Rude and Linda Stals and Paolo Bientinesi and David Ham and Furong Huang and Paul HJ Kelly and Christian Lengauer and Saday Sadayappan},
  journal = {(2020)},
  year = {2020},
}

@inproceedings{reustle2020fastb44e,
  title = {Fast GPU Convolution for CP-decomposed Tensorial Neural Networks},
  author = {Alexander Reustle and Tahseen Rabbani and Furong Huang},
  booktitle = {Intelligent Systems Conference (IntelliSys), 2020},
  year = {2020},
  url = {https://link.springer.com/chapter/10.1007/978-3-030-55180-3_35},
}

@inproceedings{yousefzadeh2020interpretable6796,
  title = {Interpretable Insights about Medical Image Datasets: Using Wavelets and Spectral Methods},
  author = {Roozbeh Yousefzadeh and Furong Huang},
  booktitle = {Workshop on Human Interpretability in Machine Learning (WHI), ICML 2020},
  year = {2020},
}

@inproceedings{su2020sampling4fd0,
  title = {Sampling-Free Learning of Bayesian Quantized Neural Networks},
  author = {Jiahao Su and Milan Cvitkovic and Furong Huang},
  booktitle = {The International Conference on Learning Representations (ICLR), 2020},
  year = {2020},
  eprint = {1912.02992},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/1912.02992},
}

@inproceedings{bientinesi2020tensor5339,
  title = {Tensor Computations: Applications and Optimization (Dagstuhl Seminar 20111)},
  author = {Paolo Bientinesi and David Ham and Furong Huang and Paul HJ Kelly and Christian Lengauer and Saday Sadayappan},
  booktitle = {Dagstuhl Reports},
  year = {2020},
}

@inproceedings{li2020understanding94ee,
  title = {Understanding Generalization in Deep Learning via Tensor Methods},
  author = {Jingling Li and Yanchao Sun and Jiahao Su and Taiji Suzuki and Furong Huang},
  booktitle = {The 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 2020},
  year = {2020},
  eprint = {2001.05070},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2001.05070},
}

@article{huang2020understandingfaa9,
  title = {Understanding generalization through visualizations},
  author = {W Ronny Huang and Zeyad Emam and Micah Goldblum and Liam Fowl and Justin K Terry and Furong Huang and Tom Goldstein},
  year = {2020},
}

@misc{yousefzadeh2020usingf103,
  title = {Using Wavelets and Spectral Methods to Study Patterns in Image-Classification Datasets},
  author = {Roozbeh Yousefzadeh and Furong Huang},
  howpublished = {arXiv preprint arXiv:2006.09879},
  year = {2020},
  eprint = {2006.09879},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2006.09879},
}

@inproceedings{huang2019spectrala77d,
  title = {A Spectral Method for Off-Policy Evaluation in Contextual Bandits under Distribution Shift},
  author = {Furong Huang and Yu-Xiang Wang and Xuchen You},
  booktitle = {13th Annual Machine Learning Symposium, 2019},
  year = {2019},
}

@inproceedings{shafahi2019batch4adf,
  title = {Batch-wise Logit-Similarity: Generalizing Logit-Squeezing and Label-Smoothing},
  author = {Ali Shafahi and Amin Ghiasi and Mahyar Najibi and Furong Huang and John P Dickerson and Tom Goldstein},
  booktitle = {BMVC},
  year = {2019},
}

@inproceedings{huang2019guaranteed55ae,
  title = {Guaranteed Scalable Learning of Latent Tree Models},
  author = {Furong Huang and Niranjan Uma Naresh and Ioakeim Perros and Robert Chen and Jimeng Sun and Anima Anandkumar},
  booktitle = {The Conference on Uncertainty in Artificial Intelligence (UAI), 2019},
  year = {2019},
  eprint = {1406.4566},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/1406.4566},
}

@misc{ratner2019mlsysc5d1,
  title = {MLSys: The New Frontier of Machine Learning Systems},
  author = {Alexander Ratner and Dan Alistarh and Gustavo Alonso and David G Andersen and Peter Bailis and Sarah Bird and Nicholas Carlini and Bryan Catanzaro and Jennifer Chayes and Eric Chung},
  howpublished = {arXiv preprint arXiv:1904.03257},
  year = {2019},
  eprint = {1904.03257},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/1904.03257},
}

@inproceedings{curry2019reinforcementd693,
  title = {Reinforcement Learning for Dynamic Set Packing},
  author = {Michael J. Curry and Duncan McElfresh and Xuchen You and Cameron Moy and Furong Huang and Tom Goldstein and John P. Dickerson},
  booktitle = {Conference on Reinforcement Learning and Decision Making (RLDM), 2019},
  year = {2019},
}

@inproceedings{su2019tensorial5757,
  title = {Tensorial Neural Networks: Generalization of Neural Networks and Application to Model Compression},
  author = {Jiahao Su and Jingling Li and Bobby Bhattacharjee and Furong Huang},
  booktitle = {13th Annual Machine Learning Symposium, 2019},
  year = {2019},
}

@misc{huang2018guaranteeda9e3,
  title = {Guaranteed Simultaneous Asymmetric Tensor Decomposition via Orthogonalized Alternating Least Squares},
  author = {Furong Huang and Jialin Li and Xuchen You},
  howpublished = {arXiv preprint arXiv:1805.10348},
  year = {2018},
  eprint = {1805.10348},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/1805.10348},
}

@misc{huang2016discovery8101,
  title = {Discovery of latent factors in high-dimensional data using tensor methods},
  author = {Furong Huang},
  year = {2016},
}

@inproceedings{xu2016negative0ad5,
  title = {Non-negative Factorization of the Occurrence Tensor from Financial Contracts},
  author = {Zheng Xu and Furong Huang and Louiqa Raschid and Tom Goldstein},
  booktitle = {Tensor-Learn Workshop, NIPS 2016},
  year = {2016},
  eprint = {1612.03350},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/1612.03350},
}

@article{huang2016unsupervisedfe7c,
  title = {Unsupervised learning of word-sequence representations from scratch via convolutional tensor decomposition},
  author = {Furong Huang and Animashree Anandkumar},
  year = {2016},
}

@inproceedings{arabshahi2015goingcf8c,
  title = {Are you going to the party: depends, who else is coming? -Learning hidden group dynamics via conditional latent tree models},
  author = {Forough Arabshahi and Furong Huang and Animashree Anandkumar and Carter T. Butts and Sean M. Fitzhugh},
  booktitle = {IEEE International Conference on Data Mining 2015},
  year = {2015},
  eprint = {1411.1132},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/1411.1132},
}

@article{huang2015convolutionald59a,
  title = {Convolutional Dictionary Learning through Tensor Factorization},
  author = {Furong Huang and Animashree Anandkumar},
  journal = {Journal of Machine Learning Research conference and workshop proceedings 2015},
  year = {2015},
  eprint = {1506.03509},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/1506.03509},
}

@article{huang2015online0fe5,
  title = {Online tensor methods for learning latent variable models},
  author = {Furong Huang and UN Niranjan and Mohammad Umar Hakeem and Animashree Anandkumar},
  journal = {Journal of Machine Learning Research},
  year = {2015},
}

@article{arabshahi2015predictivec811,
  title = {Predictive Modeling in Online Learning Environments},
  author = {Forough Arabshahi and Furong Huang and Animashree Anandkumar and Carter T Butts},
  year = {2015},
}

@article{huang2014distributedfa2b,
  title = {Distributed Latent Dirichlet Allocation on Spark via Tensor Decomposition},
  author = {Furong Huang and Anima Anandkumar},
  year = {2014},
}

@inproceedings{huang2014distributedf03d,
  title = {Distributed Latent Dirichlet Allocation via Tensor Factorization},
  author = {Furong Huang and Sergiy Matusevych and Anima Anandkumar and Nikos Karampatziakis and Paul Mineiro},
  booktitle = {Optimization for Machine Learning Workshop, NIPS 2014},
  year = {2014},
  url = {http://www.opt-ml.org/papers/opt2014_submission_15.pdf},
}

@article{huang2014fastc345,
  title = {Fast Detection of Overlapping Communities via Online Tensor Methods/ Online Tensor Methods for Learning Latent Variable Models},
  author = {Furong Huang and U. N. Niranjan and Mohammad Umar Hakeem and Animashree Anandkumar},
  journal = {Journal of Machine Learning Research 2014},
  year = {2014},
  eprint = {1309.0787},
  archivePrefix = {arXiv},
  url = {http://arxiv.org/abs/1309.0787},
}

@inproceedings{huang2013fast7d23,
  title = {FCD: Fast-Concurrent-Distributed Load Balancing under Switching Costs and Imperfect Observations},
  author = {Furong Huang and Anima Anandkumar},
  booktitle = {In Proc. of the 32nd Annual IEEE International Conference on Computer Communications (INFOCOM), Turin, Italy, Apr. 2013},
  year = {2013},
  url = {https://ieeexplore.ieee.org/document/6566989},
}

@article{anandkumar2012highb5ab,
  title = {High-dimensional structure estimation in Ising models: Local separation criterion},
  author = {Animashree Anandkumar and Vincent YF Tan and Furong Huang and Alan S Willsky},
  journal = {The Annals of Statistics},
  year = {2012},
}

@article{anandkumar2012learning63c3,
  title = {Learning mixtures of tree graphical models},
  author = {Anima Anandkumar and Daniel J Hsu and Furong Huang and Sham M Kakade},
  journal = {Advances in Neural Information Processing Systems},
  year = {2012},
}

@inproceedings{huang2010prediction7869,
  title = {Prediction-based spectrum aggregation with hardware limitation in cognitive radio networks},
  author = {Furong Huang and Wei Wang and Haiyan Luo and Guanding Yu and Zhaoyang Zhang},
  booktitle = {2010 IEEE 71st Vehicular Technology Conference},
  year = {2010},
}