Fei Sha

Publication Activity (10 Years)

Years Active: 1992-2024
Publications (10 Years): 133

Top Venues

CoRR

ICML

CVPR

AISTATS

Publications

Yair Schiff, Zhong Yi Wan, Jeffrey B. Parker, Stephan Hoyer, Volodymyr Kuleshov, Fei Sha, Leonardo Zepeda-Núñez
DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems. CoRR (2024)
Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Joshua Ainslie, Sumit Sanghai, Fei Sha, William W. Cohen
Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute. ICML (2023)
Zhong Yi Wan, Ricardo Baptista, Yi-Fan Chen, John Anderson, Anudhyan Boral, Fei Sha, Leonardo Zepeda-Núñez
Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models. CoRR (2023)
Zhong Yi Wan, Leonardo Zepeda-Núñez, Anudhyan Boral, Fei Sha
Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems. ICLR (2023)
Michiel de Jong, Yury Zemlyanskiy, Joshua Ainslie, Nicholas FitzGerald, Sumit Sanghai, Fei Sha, William W. Cohen
FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference. ACL (Findings) (2023)
Thomas Mensink, Jasper R. R. Uijlings, Lluís Castrejon, Arushi Goel, Felipe Cadar, Howard Zhou, Fei Sha, André Araujo, Vittorio Ferrari
Encyclopedic VQA: Visual questions about detailed properties of fine-grained categories. ICCV (2023)
Hexiang Hu, Ozan Sener, Fei Sha, Vladlen Koltun
Drinking From a Firehose: Continual Learning With Web-Scale Natural Language. IEEE Trans. Pattern Anal. Mach. Intell. 45 (5) (2023)
Zhong Yi Wan, Ricardo Baptista, Anudhyan Boral, Yi-Fan Chen, John Anderson, Fei Sha, Leonardo Zepeda-Núñez
Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models. NeurIPS (2023)
Thomas Mensink, Jasper R. R. Uijlings, Lluís Castrejón, Arushi Goel, Felipe Cadar, Howard Zhou, Fei Sha, André Araujo, Vittorio Ferrari
Encyclopedic VQA: Visual questions about detailed properties of fine-grained categories. CoRR (2023)
Lizao Li, Rob Carver, Ignacio Lopez-Gomez, Fei Sha, John Anderson
SEEDS: Emulation of Weather Forecast Ensembles with Diffusion Models. CoRR (2023)
Marc Finzi, Anudhyan Boral, Andrew Gordon Wilson, Fei Sha, Leonardo Zepeda-Núñez
User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems. CoRR (2023)
Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Joshua Ainslie, Sumit Sanghai, Fei Sha, William Cohen
Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute. CoRR (2023)
Marc Anton Finzi, Anudhyan Boral, Andrew Gordon Wilson, Fei Sha, Leonardo Zepeda-Núñez
User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems. ICML (2023)
Tiwalayo Eisape, Mh Tessler, Ishita Dasgupta, Fei Sha, Sjoerd van Steenkiste, Tal Linzen
A Systematic Comparison of Syllogistic Reasoning in Humans and Language Models. CoRR (2023)
Anudhyan Boral, Zhong Yi Wan, Leonardo Zepeda-Núñez, James Lottes, Qing Wang, Yi-Fan Chen, John Anderson, Fei Sha
Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations. NeurIPS (2023)
Stephan Rasp, Stephan Hoyer, Alexander Merose, Ian Langmore, Peter W. Battaglia, Tyler Russell, Alvaro Sanchez-Gonzalez, Vivian Yang, Rob Carver, Shreya Agrawal, Matthew Chantry, Zied Ben Bouallegue, Peter Dueben, Carla Bromberg, Jared Sisk, Luke Barrington, Aaron Bell, Fei Sha
WeatherBench 2: A benchmark for the next generation of data-driven global weather models. CoRR (2023)
Jackson Petty, Sjoerd van Steenkiste, Ishita Dasgupta, Fei Sha, Dan Garrette, Tal Linzen
The Impact of Depth and Width on Transformer Language Model Generalization. CoRR (2023)
Kun Su, Judith Yue Li, Qingqing Huang, Dima Kuzmin, Joonseok Lee, Chris Donahue, Fei Sha, Aren Jansen, Yu Wang, Mauro Verzetti, Timo I. Denk
V2Meow: Meowing to the Visual Beat via Music Generation. CoRR (2023)
Sébastien M. R. Arnold, Fei Sha
Policy-Induced Self-Supervision Improves Representation Finetuning in Visual RL. CoRR (2023)
Anudhyan Boral, Zhong Yi Wan, Leonardo Zepeda-Núñez, James Lottes, Qing Wang, Yi-Fan Chen, John Robert Anderson, Fei Sha
Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations. CoRR (2023)
Zhong Yi Wan, Leonardo Zepeda-Núñez, Anudhyan Boral, Fei Sha
Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems. CoRR (2023)
Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Fei Sha, William W. Cohen
Mention Memory: incorporating textual knowledge into Transformers through entity mention attention. ICLR (2022)
Linlu Qiu, Peter Shaw, Panupong Pasupat, Pawel Krzysztof Nowak, Tal Linzen, Fei Sha, Kristina Toutanova
Improving Compositional Generalization with Latent Structure and Data Augmentation. NAACL-HLT (2022)
Robby Costales, Shariq Iqbal, Fei Sha
Possibility Before Utility: Learning And Using Hierarchical Affordances. CoRR (2022)
Robby Costales, Shariq Iqbal, Fei Sha
Possibility Before Utility: Learning And Using Hierarchical Affordances. ICLR (2022)
Linlu Qiu, Peter Shaw, Panupong Pasupat, Tianze Shi, Jonathan Herzig, Emily Pitler, Fei Sha, Kristina Toutanova
Evaluating the Impact of Model Scale for Compositional Generalization in Semantic Parsing. EMNLP (2022)
Linlu Qiu, Peter Shaw, Panupong Pasupat, Tianze Shi, Jonathan Herzig, Emily Pitler, Fei Sha, Kristina Toutanova
Evaluating the Impact of Model Scale for Compositional Generalization in Semantic Parsing. CoRR (2022)
Shariq Iqbal, Robby Costales, Fei Sha
ALMA: Hierarchical Learning for Composite Multi-Agent Tasks. NeurIPS (2022)
Yury Zemlyanskiy, Michiel de Jong, Joshua Ainslie, Panupong Pasupat, Peter Shaw, Linlu Qiu, Sumit Sanghai, Fei Sha
Generate-and-Retrieve: Use Your Predictions to Improve Retrieval for Semantic Parsing. COLING (2022)
Shariq Iqbal, Robby Costales, Fei Sha
ALMA: Hierarchical Learning for Composite Multi-Agent Tasks. CoRR (2022)
Michiel de Jong, Yury Zemlyanskiy, Joshua Ainslie, Nicholas FitzGerald, Sumit Sanghai, Fei Sha, William Cohen
FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference. CoRR (2022)
Sébastien M. R. Arnold, Pierre L'Ecuyer, Liyu Chen, Yi-Fan Chen, Fei Sha
Policy Learning and Evaluation with Randomized Quasi-Monte Carlo. AISTATS (2022)
Fei Sha, Ruizhi Zhang
Quickest Detection of the Change of Community via Stochastic Block Models. ISIT (2022)
Sébastien M. R. Arnold, Pierre L'Ecuyer, Liyu Chen, Yi-Fan Chen, Fei Sha
Policy Learning and Evaluation with Randomized Quasi-Monte Carlo. CoRR (2022)
Fei Sha, Ruizhi Zhang
Adversarially robust subspace learning in the spiked covariance model. Stat. Anal. Data Min. 15 (4) (2022)
Yury Zemlyanskiy, Michiel de Jong, Joshua Ainslie, Panupong Pasupat, Peter Shaw, Linlu Qiu, Sumit Sanghai, Fei Sha
Generate-and-Retrieve: use your predictions to improve retrieval for semantic parsing. CoRR (2022)
Yury Zemlyanskiy, Joshua Ainslie, Michiel de Jong, Philip Pham, Ilya Eckstein, Fei Sha
ReadTwice: Reading Very Large Documents with Memories. CoRR (2021)
Yury Zemlyanskiy, Joshua Ainslie, Michiel de Jong, Philip Pham, Ilya Eckstein, Fei Sha
ReadTwice: Reading Very Large Documents with Memories. NAACL-HLT (2021)
Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Fei Sha, William Cohen
Mention Memory: incorporating textual knowledge into Transformers through entity mention attention. CoRR (2021)
Linlu Qiu, Hexiang Hu, Bowen Zhang, Peter Shaw, Fei Sha
Systematic Generalization on gSCAN: What is Nearly Solved and What is Next? EMNLP (1) (2021)
Linlu Qiu, Hexiang Hu, Bowen Zhang, Peter Shaw, Fei Sha
Systematic Generalization on gSCAN: What is Nearly Solved and What is Next? CoRR (2021)
Filipe de Avila Belbute-Peres, Yi-Fan Chen, Fei Sha
HyperPINN: Learning parameterized differential equations with physics-informed hypernetworks. CoRR (2021)
Sayali Kulkarni, Sheide Chammas, Wan Zhu, Fei Sha, Eugene Ie
CoMSum and SIBERT: A Dataset and Neural Model for Query-Based Multi-document Summarization. ICDAR (2) (2021)
Yury Zemlyanskiy, Sudeep Gandhe, Ruining He, Bhargav Kanagal, Anirudh Ravula, Juraj Gottweis, Fei Sha, Ilya Eckstein
DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections. EACL (2021)
Bowen Zhang, Hexiang Hu, Linlu Qiu, Peter Shaw, Fei Sha
Visually Grounded Concept Composition. EMNLP (Findings) (2021)
Sébastien M. R. Arnold, Fei Sha
Embedding Adaptation is Still Needed for Few-Shot Learning. CoRR (2021)
Yury Zemlyanskiy, Sudeep Gandhe, Ruining He, Bhargav Kanagal, Anirudh Ravula, Juraj Gottweis, Fei Sha, Ilya Eckstein
DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections. CoRR (2021)
Wang Zhu, Peter Shaw, Tal Linzen, Fei Sha
Learning to Generalize Compositionally by Transferring Across Semantic Parsing Tasks. CoRR (2021)
Shariq Iqbal, Christian A. Schröder de Witt, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha
Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning. ICML (2021)
Linlu Qiu, Peter Shaw, Panupong Pasupat, Pawel Krzysztof Nowak, Tal Linzen, Fei Sha, Kristina Toutanova
Improving Compositional Generalization with Latent Structure and Data Augmentation. CoRR (2021)
Sébastien M. R. Arnold, Shariq Iqbal, Fei Sha
When MAML Can Adapt Fast and How to Assist When It Cannot. AISTATS (2021)
Bowen Zhang, Jiahui Yu, Christopher Fifty, Wei Han, Andrew M. Dai, Ruoming Pang, Fei Sha
Co-training Transformer with Videos and Images Improves Action Recognition. CoRR (2021)
Bowen Zhang, Hexiang Hu, Linlu Qiu, Peter Shaw, Fei Sha
Visually Grounded Concept Composition. CoRR (2021)
Wang Zhu, Hexiang Hu, Jiacheng Chen, Zhiwei Deng, Vihan Jain, Eugene Ie, Fei Sha
BabyWalk: Going Farther in Vision-and-Language Navigation by Taking Baby Steps. CoRR (2020)
Hexiang Hu, Ozan Sener, Fei Sha, Vladlen Koltun
Drinking from a Firehose: Continual Learning with Web-scale Natural Language. CoRR (2020)
Bowen Zhang, Hexiang Hu, Fei Sha
Visual Storytelling via Predicting Anchor Word Embeddings in the Stories. CoRR (2020)
Shariq Iqbal, Christian A. Schröder de Witt, Bei Peng, Wendelin Böhmer, Shimon Whiteson, Fei Sha
AI-QMIX: Attention and Imagination for Dynamic Multi-Agent Reinforcement Learning. CoRR (2020)
Bowen Zhang, Hexiang Hu, Vihan Jain, Eugene Ie, Fei Sha
Learning to Represent Image and Text with Denotation Graph. EMNLP (1) (2020)
Bowen Zhang, Hexiang Hu, Vihan Jain, Eugene Ie, Fei Sha
Learning to Represent Image and Text with Denotation Graph. CoRR (2020)
Wang Zhu, Hexiang Hu, Jiacheng Chen, Zhiwei Deng, Vihan Jain, Eugene Ie, Fei Sha
BabyWalk: Going Farther in Vision-and-Language Navigation by Taking Baby Steps. ACL (2020)
Han-Jia Ye, Hexiang Hu, De-Chuan Zhan, Fei Sha
Few-Shot Learning via Embedding Adaptation With Set-to-Set Functions. CVPR (2020)
Yiming Yan, Melissa Ailem, Fei Sha
Amortized Inference of Variational Bounds for Learning Noisy-OR. AISTATS (2020)
Zhiyun Lu, Eugene Ie, Fei Sha
Uncertainty Estimation with Infinitesimal Jackknife, Its Distribution and Mean-Field Approximation. CoRR (2020)
Sayali Kulkarni, Sheide Chammas, Wan Zhu, Fei Sha, Eugene Ie
AQuaMuSe: Automatically Generating Datasets for Query-Based Multi-Document Summarization. CoRR (2020)
Soravit Changpinyo, Wei-Lun Chao, Boqing Gong, Fei Sha
Classifier and Exemplar Synthesis for Zero-Shot Learning. Int. J. Comput. Vis. 128 (1) (2020)
Bowen Zhang, Hexiang Hu, Joonseok Lee, Ming Zhao, Sheide Chammas, Vihan Jain, Eugene Ie, Fei Sha
A Hierarchical Multi-Modal Encoder for Moment Localization in Video Corpus. CoRR (2020)
Han-Jia Ye, Hexiang Hu, De-Chuan Zhan, Fei Sha
Learning Classifier Synthesis for Generalized Few-Shot Learning. CoRR (2019)
Shariq Iqbal, Fei Sha
Coordinated Exploration via Intrinsic Rewards for Multi-Agent Reinforcement Learning. CoRR (2019)
Jin Joo Lee, Fei Sha, Cynthia Breazeal
A Bayesian Theory of Mind Approach to Nonverbal Communication. HRI (2019)
Melissa Ailem, Bowen Zhang, Fei Sha
Topic Augmented Generator for Abstractive Summarization. CoRR (2019)
Yiming Yan, Melissa Ailem, Fei Sha
Amortized Inference of Variational Bounds for Learning Noisy-OR. CoRR (2019)
Michiel de Jong, Fei Sha
Neural Theorem Provers Do Not Learn Rules Without Exploration. CoRR (2019)
Zhiyun Lu, Liyu Chen, Chao-Kai Chiang, Fei Sha
Hyper-parameter Tuning under a Budget Constraint. IJCAI (2019)
Avner May, Alireza Bagheri Garakani, Zhiyun Lu, Dong Guo, Kuan Liu, Aurélien Bellet, Linxi Fan, Michael Collins, Daniel Hsu, Brian Kingsbury, Michael Picheny, Fei Sha
Kernel Approximation Methods for Speech Recognition. J. Mach. Learn. Res. 20 (2019)
Zhiyun Lu, Chao-Kai Chiang, Fei Sha
Hyper-parameter Tuning under a Budget Constraint. CoRR (2019)
Shariq Iqbal, Fei Sha
Actor-Attention-Critic for Multi-Agent Reinforcement Learning. ICML (2019)
Sébastien M. R. Arnold, Shariq Iqbal, Fei Sha
Decoupling Adaptation from Modeling with Meta-Optimizers for Meta Learning. CoRR (2019)
Hexiang Hu, Liyu Chen, Boqing Gong, Fei Sha
Synthesized Policies for Transfer and Adaptation across Tasks and Environments. CoRR (2019)
Yury Zemlyanskiy, Fei Sha
Aiming to Know You Better Perhaps Makes Me a More Engaging Dialogue Partner. CoNLL (2018)
Wei-Lun Chao, Hexiang Hu, Fei Sha
Cross-Dataset Adaptation for Visual Question Answering. CoRR (2018)
Hexiang Hu, Wei-Lun Chao, Fei Sha
Learning Answer Embeddings for Visual Question Answering. CVPR (2018)
Ke Zhang, Kristen Grauman, Fei Sha
Retrospective Encoders for Video Summarization. ECCV (8) (2018)
Jan Kremer, Fei Sha, Christian Igel
Robust Active Label Correction. AISTATS (2018)
Melissa Ailem, Bowen Zhang, Aurélien Bellet, Pascal Denis, Fei Sha
A Probabilistic Model for Joint Learning of Word Embeddings from Texts and Images. EMNLP (2018)
Wei-Lun Chao, Hexiang Hu, Fei Sha
Being Negative but Constructively: Lessons Learnt from Creating Better Visual Question Answering Datasets. NAACL-HLT (2018)
Tarek F. Abdelzaher, Nora Ayanian, Tamer Basar, Suhas N. Diggavi, Jana Diesner, Deepak Ganesan, Ramesh Govindan, Susmit Jha, Tancrède Lepoint, Benjamin M. Marlin, Klara Nahrstedt, David M. Nicol, Raj Rajkumar, Stephen Russell, Sanjit A. Seshia, Fei Sha, Prashant J. Shenoy, Mani B. Srivastava, Gaurav S. Sukhatme, Ananthram Swami, Paulo Tabuada, Don Towsley, Nitin H. Vaidya, Venugopal V. Veeravalli
Will Distributed Computing Revolutionize Peace? The Emergence of Battlefield IoT. ICDCS (2018)
Hexiang Hu, Wei-Lun Chao, Fei Sha
Learning Answer Embeddings for Visual Question Answering. CoRR (2018)
Soravit Changpinyo, Wei-Lun Chao, Boqing Gong, Fei Sha
Classifier and Exemplar Synthesis for Zero-Shot Learning. CoRR (2018)
Han-Jia Ye, Hexiang Hu, De-Chuan Zhan, Fei Sha
Learning Embedding Adaptation for Few-Shot Learning. CoRR (2018)
Shariq Iqbal, Fei Sha
Actor-Attention-Critic for Multi-Agent Reinforcement Learning. CoRR (2018)
Soravit Changpinyo, Hexiang Hu, Fei Sha
Multi-Task Learning for Sequence Tagging: An Empirical Study. CoRR (2018)
Bowen Zhang, Hexiang Hu, Fei Sha
Cross-Modal and Hierarchical Modeling of Video and Text. ECCV (13) (2018)
Wei-Lun Chao, Hexiang Hu, Fei Sha
Cross-Dataset Adaptation for Visual Question Answering. CVPR (2018)
Yury Zemlyanskiy, Fei Sha
Aiming to Know You Better Perhaps Makes Me a More Engaging Dialogue Partner. CoRR (2018)
Soravit Changpinyo, Hexiang Hu, Fei Sha
Multi-Task Learning for Sequence Tagging: An Empirical Study. COLING (2018)
Tarek F. Abdelzaher, Nora Ayanian, Tamer Basar, Suhas N. Diggavi, Jana Diesner, Deepak Ganesan, Ramesh Govindan, Susmit Jha, Tancrède Lepoint, Benjamin M. Marlin, Klara Nahrstedt, David M. Nicol, Raj Rajkumar, Stephen Russell, Sanjit A. Seshia, Fei Sha, Prashant J. Shenoy, Mani B. Srivastava, Gaurav S. Sukhatme, Ananthram Swami, Paulo Tabuada, Don Towsley, Nitin H. Vaidya, Venugopal V. Veeravalli
Toward an Internet of Battlefield Things: A Resilience Perspective. Computer 51 (11) (2018)
Hexiang Hu, Liyu Chen, Boqing Gong, Fei Sha
Synthesize Policies for Transfer and Adaptation across Tasks and Environments. NeurIPS (2018)
Bowen Zhang, Hexiang Hu, Fei Sha
Cross-Modal and Hierarchical Modeling of Video and Text. CoRR (2018)
Maximilian Alber, Pieter-Jan Kindermans, Kristof Schütt, Klaus-Robert Müller, Fei Sha
An Empirical Study on The Properties of Random Bases for Kernel Methods. NIPS (2017)
Hexiang Hu, Shiyi Lan, Yuning Jiang, Zhimin Cao, Fei Sha
FastMask: Segment Multi-scale Object Candidates in One Shot. CVPR (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Fei Sha