Fei Sha - RankMe

228 papers A* 51A 17B 6C 2Misc 5Journal 102Unranked 43

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Bayesian Teaching Enables Probabilistic Reasoning in Large Language Models. CoRR Linlu Qiu, Fei Sha, Kelsey R. Allen, Yoon Kim, Tal Linzen, Sjoerd van Steenkiste
2025	J	`jnl`	Can LLM feedback enhance review quality? A randomized study of 20K reviews at ICLR 2025. CoRR Nitya Thakkar, Mert Yüksekgönül, Jake Silberg, Animesh Garg, Nanyun Peng, Fei Sha, Rose Yu, Carl Vondrick, James Zou
2025	Misc	`conf`	Diff4Steer: Steerable Diffusion Prior for Generative Music Retrieval with Semantic Guidance. ICASSP Xuchan Bao, Judith Yue Li, Zhong Yi Wan, Kun Su, Timo I. Denk, Joonseok Lee, Dima Kuzmin, Fei Sha
2025	A*	`conf`	Graders Should Cheat: Privileged Information Enables Expert-Level Automated Evaluations. EMNLP Jin Peng Zhou, Sébastien M. R. Arnold, Nan Ding, Kilian Q. Weinberger, Nan Hua, Fei Sha
2025	J	`jnl`	Graders should cheat: privileged information enables expert-level automated evaluations. CoRR Jin Peng Zhou, Sébastien M. R. Arnold, Nan Ding, Kilian Q. Weinberger, Nan Hua, Fei Sha
2024	—	`conf`	A Systematic Comparison of Syllogistic Reasoning in Humans and Language Models. NAACL-HLT Tiwalayo Eisape, Michael Henry Tessler, Ishita Dasgupta, Fei Sha, Sjoerd van Steenkiste, Tal Linzen
2024	J	`jnl`	A probabilistic framework for learning non-intrusive corrections to long-time climate simulations from short-time training data. CoRR Benedikt Barthel Sorensen, Leonardo Zepeda-Núñez, Ignacio Lopez-Gomez, Zhong Yi Wan, Rob Carver, Fei Sha, Themistoklis P. Sapsis
2024	J	`jnl`	Diff4Steer: Steerable Diffusion Prior for Generative Music Retrieval with Semantic Guidance. CoRR Xuchan Bao, Judith Yue Li, Zhong Yi Wan, Kun Su, Timo I. Denk, Joonseok Lee, Dima Kuzmin, Fei Sha
2024	A*	`conf`	DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems. ICML Yair Schiff, Zhong Yi Wan, Jeffrey B. Parker, Stephan Hoyer, Volodymyr Kuleshov, Fei Sha, Leonardo Zepeda-Núñez
2024	J	`jnl`	DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems. CoRR Yair Schiff, Zhong Yi Wan, Jeffrey B. Parker, Stephan Hoyer, Volodymyr Kuleshov, Fei Sha, Leonardo Zepeda-Núñez
2024	J	`jnl`	Dynamical-generative downscaling of climate model ensembles. CoRR Ignacio Lopez-Gomez, Zhong Yi Wan, Leonardo Zepeda-Núñez, Tapio Schneider, John R. Anderson, Fei Sha
2024	J	`jnl`	Generative AI for fast and accurate Statistical Computation of Fluids. CoRR Roberto Molinaro, Samuel Lanthaler, Bogdan Raonic, Tobias Rohner, Victor Armegioiu, Zhong Yi Wan, Fei Sha, Siddhartha Mishra, Leonardo Zepeda-Núñez
2024	J	`jnl`	Rational-WENO: A lightweight, physically-consistent three-point weighted essentially non-oscillatory scheme. CoRR Shantanu Shahane, Sheide Chammas, Deniz A. Bezgin, Aaron B. Buhendwa, Steffen J. Schmidt, Nikolaus A. Adams, Spencer H. Bryngelson, Yi-Fan Chen, Qing Wang, Fei Sha, Leonardo Zepeda-Núñez
2024	J	`jnl`	Statistical Downscaling via High-Dimensional Distribution Matching with Generative Models. CoRR Zhong Yi Wan, Ignacio Lopez-Gomez, Rob Carver, Tapio Schneider, John R. Anderson, Fei Sha, Leonardo Zepeda-Núñez
2024	—	`conf`	The Impact of Depth on Compositional Generalization in Transformer Language Models. NAACL-HLT Jackson Petty, Sjoerd van Steenkiste, Ishita Dasgupta, Fei Sha, Dan Garrette, Tal Linzen
2024	A*	`conf`	V2Meow: Meowing to the Visual Beat via Video-to-Music Generation. AAAI Kun Su, Judith Yue Li, Qingqing Huang, Dima Kuzmin, Joonseok Lee, Chris Donahue, Fei Sha, Aren Jansen, Yu Wang, Mauro Verzetti, Timo I. Denk
2023	J	`jnl`	A Systematic Comparison of Syllogistic Reasoning in Humans and Language Models. CoRR Tiwalayo Eisape, Michael Henry Tessler, Ishita Dasgupta, Fei Sha, Sjoerd van Steenkiste, Tal Linzen
2023	A*	`conf`	Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models. NeurIPS Zhong Yi Wan, Ricardo Baptista, Anudhyan Boral, Yi-Fan Chen, John Anderson, Fei Sha, Leonardo Zepeda-Núñez
2023	J	`jnl`	Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models. CoRR Zhong Yi Wan, Ricardo Baptista, Yi-Fan Chen, John Anderson, Anudhyan Boral, Fei Sha, Leonardo Zepeda-Núñez
2023	J	`jnl`	Drinking From a Firehose: Continual Learning With Web-Scale Natural Language. IEEE Trans. Pattern Anal. Mach. Intell. Hexiang Hu, Ozan Sener, Fei Sha, Vladlen Koltun
2023	A*	`conf`	Encyclopedic VQA: Visual questions about detailed properties of fine-grained categories. ICCV Thomas Mensink, Jasper R. R. Uijlings, Lluís Castrejón, Arushi Goel, Felipe Cadar, Howard Zhou, Fei Sha, André Araújo, Vittorio Ferrari
2023	J	`jnl`	Encyclopedic VQA: Visual questions about detailed properties of fine-grained categories. CoRR Thomas Mensink, Jasper R. R. Uijlings, Lluís Castrejón, Arushi Goel, Felipe Cadar, Howard Zhou, Fei Sha, André Araújo, Vittorio Ferrari
2023	A*	`conf`	Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems. ICLR Zhong Yi Wan, Leonardo Zepeda-Núñez, Anudhyan Boral, Fei Sha
2023	J	`jnl`	Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems. CoRR Zhong Yi Wan, Leonardo Zepeda-Núñez, Anudhyan Boral, Fei Sha
2023	—	`conf`	FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference. ACL (Findings) Michiel de Jong, Yury Zemlyanskiy, Joshua Ainslie, Nicholas FitzGerald, Sumit Sanghai, Fei Sha, William W. Cohen
2023	A*	`conf`	Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations. NeurIPS Anudhyan Boral, Zhong Yi Wan, Leonardo Zepeda-Núñez, James Lottes, Qing Wang, Yi-Fan Chen, John Anderson, Fei Sha
2023	J	`jnl`	Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations. CoRR Anudhyan Boral, Zhong Yi Wan, Leonardo Zepeda-Núñez, James Lottes, Qing Wang, Yi-Fan Chen, John Robert Anderson, Fei Sha
2023	J	`jnl`	Policy-Induced Self-Supervision Improves Representation Finetuning in Visual RL. CoRR Sébastien M. R. Arnold, Fei Sha
2023	A*	`conf`	Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute. ICML Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Joshua Ainslie, Sumit Sanghai, Fei Sha, William W. Cohen
2023	J	`jnl`	Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute. CoRR Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Joshua Ainslie, Sumit Sanghai, Fei Sha, William W. Cohen
2023	J	`jnl`	SEEDS: Emulation of Weather Forecast Ensembles with Diffusion Models. CoRR Lizao Li, Rob Carver, Ignacio Lopez-Gomez, Fei Sha, John Anderson
2023	J	`jnl`	The Impact of Depth and Width on Transformer Language Model Generalization. CoRR Jackson Petty, Sjoerd van Steenkiste, Ishita Dasgupta, Fei Sha, Dan Garrette, Tal Linzen
2023	A*	`conf`	User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems. ICML Marc Anton Finzi, Anudhyan Boral, Andrew Gordon Wilson, Fei Sha, Leonardo Zepeda-Núñez
2023	J	`jnl`	User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems. CoRR Marc Finzi, Anudhyan Boral, Andrew Gordon Wilson, Fei Sha, Leonardo Zepeda-Núñez
2023	J	`jnl`	V2Meow: Meowing to the Visual Beat via Music Generation. CoRR Kun Su, Judith Yue Li, Qingqing Huang, Dima Kuzmin, Joonseok Lee, Chris Donahue, Fei Sha, Aren Jansen, Yu Wang, Mauro Verzetti, Timo I. Denk
2023	J	`jnl`	WeatherBench 2: A benchmark for the next generation of data-driven global weather models. CoRR 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
2022	A*	`conf`	ALMA: Hierarchical Learning for Composite Multi-Agent Tasks. NeurIPS Shariq Iqbal, Robby Costales, Fei Sha
2022	J	`jnl`	ALMA: Hierarchical Learning for Composite Multi-Agent Tasks. CoRR Shariq Iqbal, Robby Costales, Fei Sha
2022	J	`jnl`	Adversarially robust subspace learning in the spiked covariance model. Stat. Anal. Data Min. Fei Sha, Ruizhi Zhang
2022	A*	`conf`	Evaluating the Impact of Model Scale for Compositional Generalization in Semantic Parsing. EMNLP Linlu Qiu, Peter Shaw, Panupong Pasupat, Tianze Shi, Jonathan Herzig, Emily Pitler, Fei Sha, Kristina Toutanova
2022	J	`jnl`	Evaluating the Impact of Model Scale for Compositional Generalization in Semantic Parsing. CoRR Linlu Qiu, Peter Shaw, Panupong Pasupat, Tianze Shi, Jonathan Herzig, Emily Pitler, Fei Sha, Kristina Toutanova
2022	J	`jnl`	FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference. CoRR Michiel de Jong, Yury Zemlyanskiy, Joshua Ainslie, Nicholas FitzGerald, Sumit Sanghai, Fei Sha, William W. Cohen
2022	B	`conf`	Generate-and-Retrieve: Use Your Predictions to Improve Retrieval for Semantic Parsing. COLING Yury Zemlyanskiy, Michiel de Jong, Joshua Ainslie, Panupong Pasupat, Peter Shaw, Linlu Qiu, Sumit Sanghai, Fei Sha
2022	J	`jnl`	Generate-and-Retrieve: use your predictions to improve retrieval for semantic parsing. CoRR Yury Zemlyanskiy, Michiel de Jong, Joshua Ainslie, Panupong Pasupat, Peter Shaw, Linlu Qiu, Sumit Sanghai, Fei Sha
2022	—	`conf`	Improving Compositional Generalization with Latent Structure and Data Augmentation. NAACL-HLT Linlu Qiu, Peter Shaw, Panupong Pasupat, Pawel Krzysztof Nowak, Tal Linzen, Fei Sha, Kristina Toutanova
2022	A*	`conf`	Mention Memory: incorporating textual knowledge into Transformers through entity mention attention. ICLR Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Fei Sha, William W. Cohen
2022	A	`conf`	Policy Learning and Evaluation with Randomized Quasi-Monte Carlo. AISTATS Sébastien M. R. Arnold, Pierre L'Ecuyer, Liyu Chen, Yi-Fan Chen, Fei Sha
2022	J	`jnl`	Policy Learning and Evaluation with Randomized Quasi-Monte Carlo. CoRR Sébastien M. R. Arnold, Pierre L'Ecuyer, Liyu Chen, Yi-Fan Chen, Fei Sha
2022	A*	`conf`	Possibility Before Utility: Learning And Using Hierarchical Affordances. ICLR Robby Costales, Shariq Iqbal, Fei Sha
2022	J	`jnl`	Possibility Before Utility: Learning And Using Hierarchical Affordances. CoRR Robby Costales, Shariq Iqbal, Fei Sha
2022	B	`conf`	Quickest Detection of the Change of Community via Stochastic Block Models. ISIT Fei Sha, Ruizhi Zhang
2021	J	`jnl`	Co-training Transformer with Videos and Images Improves Action Recognition. CoRR Bowen Zhang, Jiahui Yu, Christopher Fifty, Wei Han, Andrew M. Dai, Ruoming Pang, Fei Sha
2021	—	`conf`	CoMSum and SIBERT: A Dataset and Neural Model for Query-Based Multi-document Summarization. ICDAR (2) Sayali Kulkarni, Sheide Chammas, Wan Zhu, Fei Sha, Eugene Ie
2021	A	`conf`	DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections. EACL Yury Zemlyanskiy, Sudeep Gandhe, Ruining He, Bhargav Kanagal, Anirudh Ravula, Juraj Gottweis, Fei Sha, Ilya Eckstein
2021	J	`jnl`	DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections. CoRR Yury Zemlyanskiy, Sudeep Gandhe, Ruining He, Bhargav Kanagal, Anirudh Ravula, Juraj Gottweis, Fei Sha, Ilya Eckstein
2021	J	`jnl`	Embedding Adaptation is Still Needed for Few-Shot Learning. CoRR Sébastien M. R. Arnold, Fei Sha
2021	J	`jnl`	HyperPINN: Learning parameterized differential equations with physics-informed hypernetworks. CoRR Filipe de Avila Belbute-Peres, Yi-Fan Chen, Fei Sha
2021	J	`jnl`	Improving Compositional Generalization with Latent Structure and Data Augmentation. CoRR Linlu Qiu, Peter Shaw, Panupong Pasupat, Pawel Krzysztof Nowak, Tal Linzen, Fei Sha, Kristina Toutanova
2021	J	`jnl`	Learning to Generalize Compositionally by Transferring Across Semantic Parsing Tasks. CoRR Wang Zhu, Peter Shaw, Tal Linzen, Fei Sha
2021	J	`jnl`	Mention Memory: incorporating textual knowledge into Transformers through entity mention attention. CoRR Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Fei Sha, William W. Cohen
2021	A*	`conf`	Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning. ICML Shariq Iqbal, Christian A. Schröder de Witt, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha
2021	—	`conf`	ReadTwice: Reading Very Large Documents with Memories. NAACL-HLT Yury Zemlyanskiy, Joshua Ainslie, Michiel de Jong, Philip Pham, Ilya Eckstein, Fei Sha
2021	J	`jnl`	ReadTwice: Reading Very Large Documents with Memories. CoRR Yury Zemlyanskiy, Joshua Ainslie, Michiel de Jong, Philip Pham, Ilya Eckstein, Fei Sha
2021	—	`conf`	Systematic Generalization on gSCAN: What is Nearly Solved and What is Next? EMNLP (1) Linlu Qiu, Hexiang Hu, Bowen Zhang, Peter Shaw, Fei Sha
2021	J	`jnl`	Systematic Generalization on gSCAN: What is Nearly Solved and What is Next? CoRR Linlu Qiu, Hexiang Hu, Bowen Zhang, Peter Shaw, Fei Sha
2021	—	`conf`	Visually Grounded Concept Composition. EMNLP (Findings) Bowen Zhang, Hexiang Hu, Linlu Qiu, Peter Shaw, Fei Sha
2021	J	`jnl`	Visually Grounded Concept Composition. CoRR Bowen Zhang, Hexiang Hu, Linlu Qiu, Peter Shaw, Fei Sha
2021	A	`conf`	When MAML Can Adapt Fast and How to Assist When It Cannot. AISTATS Sébastien M. R. Arnold, Shariq Iqbal, Fei Sha
2020	J	`jnl`	A Hierarchical Multi-Modal Encoder for Moment Localization in Video Corpus. CoRR Bowen Zhang, Hexiang Hu, Joonseok Lee, Ming Zhao, Sheide Chammas, Vihan Jain, Eugene Ie, Fei Sha
2020	J	`jnl`	AI-QMIX: Attention and Imagination for Dynamic Multi-Agent Reinforcement Learning. CoRR Shariq Iqbal, Christian A. Schröder de Witt, Bei Peng, Wendelin Böhmer, Shimon Whiteson, Fei Sha
2020	J	`jnl`	AQuaMuSe: Automatically Generating Datasets for Query-Based Multi-Document Summarization. CoRR Sayali Kulkarni, Sheide Chammas, Wan Zhu, Fei Sha, Eugene Ie
2020	A	`conf`	Amortized Inference of Variational Bounds for Learning Noisy-OR. AISTATS Yiming Yan, Melissa Ailem, Fei Sha
2020	A*	`conf`	BabyWalk: Going Farther in Vision-and-Language Navigation by Taking Baby Steps. ACL Wang Zhu, Hexiang Hu, Jiacheng Chen, Zhiwei Deng, Vihan Jain, Eugene Ie, Fei Sha
2020	J	`jnl`	BabyWalk: Going Farther in Vision-and-Language Navigation by Taking Baby Steps. CoRR Wang Zhu, Hexiang Hu, Jiacheng Chen, Zhiwei Deng, Vihan Jain, Eugene Ie, Fei Sha
2020	J	`jnl`	Classifier and Exemplar Synthesis for Zero-Shot Learning. Int. J. Comput. Vis. Soravit Changpinyo, Wei-Lun Chao, Boqing Gong, Fei Sha
2020	J	`jnl`	Drinking from a Firehose: Continual Learning with Web-scale Natural Language. CoRR Hexiang Hu, Ozan Sener, Fei Sha, Vladlen Koltun
2020	A*	`conf`	Few-Shot Learning via Embedding Adaptation With Set-to-Set Functions. CVPR Han-Jia Ye, Hexiang Hu, De-Chuan Zhan, Fei Sha
2020	—	`conf`	Learning to Represent Image and Text with Denotation Graph. EMNLP (1) Bowen Zhang, Hexiang Hu, Vihan Jain, Eugene Ie, Fei Sha
2020	J	`jnl`	Learning to Represent Image and Text with Denotation Graph. CoRR Bowen Zhang, Hexiang Hu, Vihan Jain, Eugene Ie, Fei Sha
2020	J	`jnl`	Uncertainty Estimation with Infinitesimal Jackknife, Its Distribution and Mean-Field Approximation. CoRR Zhiyun Lu, Eugene Ie, Fei Sha
2020	J	`jnl`	Visual Storytelling via Predicting Anchor Word Embeddings in the Stories. CoRR Bowen Zhang, Hexiang Hu, Fei Sha
2019	A*	`conf`	A Bayesian Theory of Mind Approach to Nonverbal Communication. HRI Jin Joo Lee, Fei Sha, Cynthia Breazeal
2019	A*	`conf`	Actor-Attention-Critic for Multi-Agent Reinforcement Learning. ICML Shariq Iqbal, Fei Sha
2019	J	`jnl`	Amortized Inference of Variational Bounds for Learning Noisy-OR. CoRR Yiming Yan, Melissa Ailem, Fei Sha
2019	J	`jnl`	Coordinated Exploration via Intrinsic Rewards for Multi-Agent Reinforcement Learning. CoRR Shariq Iqbal, Fei Sha
2019	J	`jnl`	Decoupling Adaptation from Modeling with Meta-Optimizers for Meta Learning. CoRR Sébastien M. R. Arnold, Shariq Iqbal, Fei Sha
2019	A*	`conf`	Hyper-parameter Tuning under a Budget Constraint. IJCAI Zhiyun Lu, Liyu Chen, Chao-Kai Chiang, Fei Sha
2019	J	`jnl`	Hyper-parameter Tuning under a Budget Constraint. CoRR Zhiyun Lu, Chao-Kai Chiang, Fei Sha
2019	J	`jnl`	Kernel Approximation Methods for Speech Recognition. J. Mach. Learn. Res. 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
2019	J	`jnl`	Learning Classifier Synthesis for Generalized Few-Shot Learning. CoRR Han-Jia Ye, Hexiang Hu, De-Chuan Zhan, Fei Sha
2019	J	`jnl`	Neural Theorem Provers Do Not Learn Rules Without Exploration. CoRR Michiel de Jong, Fei Sha
2019	J	`jnl`	Synthesized Policies for Transfer and Adaptation across Tasks and Environments. CoRR Hexiang Hu, Liyu Chen, Boqing Gong, Fei Sha
2019	J	`jnl`	Topic Augmented Generator for Abstractive Summarization. CoRR Melissa Ailem, Bowen Zhang, Fei Sha
2018	A*	`conf`	A Probabilistic Model for Joint Learning of Word Embeddings from Texts and Images. EMNLP Melissa Ailem, Bowen Zhang, Aurélien Bellet, Pascal Denis, Fei Sha
2018	J	`jnl`	Actor-Attention-Critic for Multi-Agent Reinforcement Learning. CoRR Shariq Iqbal, Fei Sha
2018	B	`conf`	Aiming to Know You Better Perhaps Makes Me a More Engaging Dialogue Partner. CoNLL Yury Zemlyanskiy, Fei Sha
2018	J	`jnl`	Aiming to Know You Better Perhaps Makes Me a More Engaging Dialogue Partner. CoRR Yury Zemlyanskiy, Fei Sha
2018	—	`conf`	Being Negative but Constructively: Lessons Learnt from Creating Better Visual Question Answering Datasets. NAACL-HLT Wei-Lun Chao, Hexiang Hu, Fei Sha
2018	J	`jnl`	Classifier and Exemplar Synthesis for Zero-Shot Learning. CoRR Soravit Changpinyo, Wei-Lun Chao, Boqing Gong, Fei Sha
2018	A*	`conf`	Cross-Dataset Adaptation for Visual Question Answering. CVPR Wei-Lun Chao, Hexiang Hu, Fei Sha
2018	J	`jnl`	Cross-Dataset Adaptation for Visual Question Answering. CoRR Wei-Lun Chao, Hexiang Hu, Fei Sha
2018	—	`conf`	Cross-Modal and Hierarchical Modeling of Video and Text. ECCV (13) Bowen Zhang, Hexiang Hu, Fei Sha
2018	J	`jnl`	Cross-Modal and Hierarchical Modeling of Video and Text. CoRR Bowen Zhang, Hexiang Hu, Fei Sha
2018	A*	`conf`	Learning Answer Embeddings for Visual Question Answering. CVPR Hexiang Hu, Wei-Lun Chao, Fei Sha
2018	J	`jnl`	Learning Answer Embeddings for Visual Question Answering. CoRR Hexiang Hu, Wei-Lun Chao, Fei Sha
2018	J	`jnl`	Learning Embedding Adaptation for Few-Shot Learning. CoRR Han-Jia Ye, Hexiang Hu, De-Chuan Zhan, Fei Sha
2018	B	`conf`	Multi-Task Learning for Sequence Tagging: An Empirical Study. COLING Soravit Changpinyo, Hexiang Hu, Fei Sha
2018	J	`jnl`	Multi-Task Learning for Sequence Tagging: An Empirical Study. CoRR Soravit Changpinyo, Hexiang Hu, Fei Sha
2018	—	`conf`	Retrospective Encoders for Video Summarization. ECCV (8) Ke Zhang, Kristen Grauman, Fei Sha
2018	A	`conf`	Robust Active Label Correction. AISTATS Jan Kremer, Fei Sha, Christian Igel
2018	A*	`conf`	Synthesize Policies for Transfer and Adaptation across Tasks and Environments. NeurIPS Hexiang Hu, Liyu Chen, Boqing Gong, Fei Sha
2018	J	`jnl`	Toward an Internet of Battlefield Things: A Resilience Perspective. Computer 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
2018	A	`conf`	Will Distributed Computing Revolutionize Peace? The Emergence of Battlefield IoT. ICDCS 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
2017	J	`jnl`	Aligning Where to See and What to Tell: Image Captioning with Region-Based Attention and Scene-Specific Contexts. IEEE Trans. Pattern Anal. Mach. Intell. Kun Fu, Junqi Jin, Runpeng Cui, Fei Sha, Changshui Zhang
2017	—	`conf`	An Empirical Study on The Properties of Random Bases for Kernel Methods. NIPS Maximilian Alber, Pieter-Jan Kindermans, Kristof Schütt, Klaus-Robert Müller, Fei Sha
2017	A*	`conf`	Attention Correctness in Neural Image Captioning. AAAI Chenxi Liu, Junhua Mao, Fei Sha, Alan L. Yuille
2017	J	`jnl`	Being Negative but Constructively: Lessons Learnt from Creating Better Visual Question Answering Datasets. CoRR Wei-Lun Chao, Hexiang Hu, Fei Sha
2017	A*	`conf`	FastMask: Segment Multi-scale Object Candidates in One Shot. CVPR Hexiang Hu, Shiyi Lan, Yuning Jiang, Zhimin Cao, Fei Sha
2017	—	`ch.`	Geodesic Flow Kernel and Landmarks: Kernel Methods for Unsupervised Domain Adaptation. Domain Adaptation in Computer Vision Applications Boqing Gong, Kristen Grauman, Fei Sha
2017	J	`jnl`	Kernel Approximation Methods for Speech Recognition. CoRR Avner May, Alireza Bagheri Garakani, Zhiyun Lu, Dong Guo, Kuan Liu, Aurélien Bellet, Linxi Fan, Michael Collins, Daniel J. Hsu, Brian Kingsbury, Michael Picheny, Fei Sha
2017	J	`jnl`	LabelBank: Revisiting Global Perspectives for Semantic Segmentation. CoRR Hexiang Hu, Zhiwei Deng, Guang-Tong Zhou, Fei Sha, Greg Mori
2017	A*	`conf`	Predicting Visual Exemplars of Unseen Classes for Zero-Shot Learning. ICCV Soravit Changpinyo, Wei-Lun Chao, Fei Sha
2016	J	`jnl`	A Comparison between Deep Neural Nets and Kernel Acoustic Models for Speech Recognition. CoRR Zhiyun Lu, Dong Guo, Alireza Bagheri Garakani, Kuan Liu, Avner May, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha
2016	Misc	`conf`	A comparison between deep neural nets and kernel acoustic models for speech recognition. ICASSP Zhiyun Lu, Dong Guo, Alireza Bagheri Garakani, Kuan Liu, Avner May, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha
2016	J	`jnl`	Active multi-view object recognition: A unifying view on online feature selection and view planning. Robotics Auton. Syst. Christian Potthast, Andreas Breitenmoser, Fei Sha, Gaurav S. Sukhatme
2016	—	`conf`	An Empirical Study and Analysis of Generalized Zero-Shot Learning for Object Recognition in the Wild. ECCV (2) Wei-Lun Chao, Soravit Changpinyo, Boqing Gong, Fei Sha
2016	J	`jnl`	An Empirical Study and Analysis of Generalized Zero-Shot Learning for Object Recognition in the Wild. CoRR Wei-Lun Chao, Soravit Changpinyo, Boqing Gong, Fei Sha
2016	J	`jnl`	Attention Correctness in Neural Image Captioning. CoRR Chenxi Liu, Junhua Mao, Fei Sha, Alan L. Yuille
2016	J	`jnl`	FastMask: Segment Object Multi-scale Candidates in One Shot. CoRR Hexiang Hu, Shiyi Lan, Yuning Jiang, Zhimin Cao, Fei Sha
2016	A*	`conf`	Metric Learning for Ordinal Data. AAAI Yuan Shi, Wenzhe Li, Fei Sha
2016	J	`jnl`	Predicting Visual Exemplars of Unseen Classes for Zero-Shot Learning. CoRR Soravit Changpinyo, Wei-Lun Chao, Fei Sha
2016	J	`jnl`	Recalling Holistic Information for Semantic Segmentation. CoRR Hexiang Hu, Zhiwei Deng, Guang-Tong Zhou, Fei Sha, Greg Mori
2016	A*	`conf`	Summary Transfer: Exemplar-Based Subset Selection for Video Summarization. CVPR Ke Zhang, Wei-Lun Chao, Fei Sha, Kristen Grauman
2016	J	`jnl`	Summary Transfer: Exemplar-based Subset Selection for Video Summarization. CoRR Ke Zhang, Wei-Lun Chao, Fei Sha, Kristen Grauman
2016	—	`conf`	Supervised Word Mover's Distance. NIPS Gao Huang, Chuan Guo, Matt J. Kusner, Yu Sun, Fei Sha, Kilian Q. Weinberger
2016	A*	`conf`	Synthesized Classifiers for Zero-Shot Learning. CVPR Soravit Changpinyo, Wei-Lun Chao, Boqing Gong, Fei Sha
2016	J	`jnl`	Synthesized Classifiers for Zero-Shot Learning. CoRR Soravit Changpinyo, Wei-Lun Chao, Boqing Gong, Fei Sha
2016	C	`conf`	The improvement of page sorting algorithm for music users in Nutch. ICIS Ying Li, Fei Sha, Shujuan Wang, Tao Hu
2016	J	`jnl`	Understanding Image and Text Simultaneously: a Dual Vision-Language Machine Comprehension Task. CoRR Nan Ding, Sebastian Goodman, Fei Sha, Radu Soricut
2016	—	`conf`	Video Summarization with Long Short-Term Memory. ECCV (7) Ke Zhang, Wei-Lun Chao, Fei Sha, Kristen Grauman
2016	J	`jnl`	Video Summarization with Long Short-term Memory. CoRR Ke Zhang, Wei-Lun Chao, Fei Sha, Kristen Grauman
2015	A	`conf`	A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning. SDM Aurélien Bellet, Yingyu Liang, Alireza Bagheri Garakani, Maria-Florina Balcan, Fei Sha
2015	—	`conf`	Active Multi-view Object Recognition and Online Feature Selection. ISRR (2) Christian Potthast, Andreas Breitenmoser, Fei Sha, Gaurav S. Sukhatme
2015	J	`jnl`	Aligning where to see and what to tell: image caption with region-based attention and scene factorization. CoRR Junqi Jin, Kun Fu, Runpeng Cui, Fei Sha, Changshui Zhang
2015	—	`conf`	Designing a socially assistive robot for personalized number concepts learning in preschool children. ICDL-EPIROB Caitlyn Clabaugh, Gisele Ragusa, Fei Sha, Maja J. Mataric
2015	A*	`conf`	Exponential Integration for Hamiltonian Monte Carlo. ICML Wei-Lun Chao, Justin Solomon, Dominik L. Michels, Fei Sha
2015	A	`conf`	Large-Margin Determinantal Point Processes. UAI Wei-Lun Chao, Boqing Gong, Kristen Grauman, Fei Sha
2015	J	`jnl`	Marginalizing stacked linear denoising autoencoders. J. Mach. Learn. Res. Minmin Chen, Kilian Q. Weinberger, Zhixiang Eddie Xu, Fei Sha
2015	A	`conf`	Similarity Learning for High-Dimensional Sparse Data. AISTATS Kuan Liu, Aurélien Bellet, Fei Sha
2014	A*	`conf`	Decorrelating Semantic Visual Attributes by Resisting the Urge to Share. CVPR Dinesh Jayaraman, Fei Sha, Kristen Grauman
2014	A*	`conf`	Demystifying Information-Theoretic Clustering. ICML Greg Ver Steeg, Aram Galstyan, Fei Sha, Simon DeDeo
2014	Misc	`conf`	Discriminative non-negative matrix factorization for single-channel speech separation. ICASSP Zi Wang, Fei Sha
2014	J	`jnl`	Distributed Frank-Wolfe Algorithm: A Unified Framework for Communication-Efficient Sparse Learning. CoRR Aurélien Bellet, Yingyu Liang, Alireza Bagheri Garakani, Maria-Florina Balcan, Fei Sha
2014	—	`conf`	Diverse Sequential Subset Selection for Supervised Video Summarization. NIPS Boqing Gong, Wei-Lun Chao, Kristen Grauman, Fei Sha
2014	J	`jnl`	How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets. CoRR Zhiyun Lu, Avner May, Kuan Liu, Alireza Bagheri Garakani, Dong Guo, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha
2014	J	`jnl`	Large-Margin Determinantal Point Processes. CoRR Boqing Gong, Wei-Lun Chao, Kristen Grauman, Fei Sha
2014	J	`jnl`	Learning Kernels for Unsupervised Domain Adaptation with Applications to Visual Object Recognition. Int. J. Comput. Vis. Boqing Gong, Kristen Grauman, Fei Sha
2014	A*	`conf`	Marginalized Denoising Auto-encoders for Nonlinear Representations. ICML Minmin Chen, Kilian Q. Weinberger, Fei Sha, Yoshua Bengio
2014	J	`jnl`	Similarity Learning for High-Dimensional Sparse Data. CoRR Kuan Liu, Aurélien Bellet, Fei Sha
2014	A*	`conf`	Sparse Compositional Metric Learning. AAAI Yuan Shi, Aurélien Bellet, Fei Sha
2014	J	`jnl`	Sparse Compositional Metric Learning. CoRR Yuan Shi, Aurélien Bellet, Fei Sha
2014	A*	`conf`	Two-Stage Metric Learning. ICML Jun Wang, Ke Sun, Fei Sha, Stéphane Marchand-Maillet, Alexandros Kalousis
2014	J	`jnl`	Two-Stage Metric Learning. CoRR Jun Wang, Ke Sun, Fei Sha, Stéphane Marchand-Maillet, Alexandros Kalousis
2013	J	`jnl`	An alternative text representation to TF-IDF and Bag-of-Words CoRR Zhixiang Eddie Xu, Minmin Chen, Kilian Q. Weinberger, Fei Sha
2013	—	`conf`	Analogy-preserving Semantic Embedding for Visual Object Categorization. ICML (3) Sung Ju Hwang, Kristen Grauman, Fei Sha
2013	—	`conf`	Connecting the Dots with Landmarks: Discriminatively Learning Domain-Invariant Features for Unsupervised Domain Adaptation. ICML (1) Boqing Gong, Kristen Grauman, Fei Sha
2013	A*	`conf`	Deformable Spatial Pyramid Matching for Fast Dense Correspondences. CVPR Jaechul Kim, Ce Liu, Fei Sha, Kristen Grauman
2013	J	`jnl`	Demystifying Information-Theoretic Clustering. CoRR Greg Ver Steeg, Aram Galstyan, Fei Sha, Simon DeDeo
2013	—	`conf`	Reshaping Visual Datasets for Domain Adaptation. NIPS Boqing Gong, Kristen Grauman, Fei Sha
2013	—	`conf`	Similarity Component Analysis. NIPS Soravit Changpinyo, Kuan Liu, Fei Sha
2012	Misc	`conf`	Cloud-enabled privacy-preserving collaborative learning for mobile sensing. SenSys Bin Liu, Yurong Jiang, Fei Sha, Ramesh Govindan
2012	A	`conf`	From sBoW to dCoT marginalized encoders for text representation. CIKM Zhixiang Eddie Xu, Minmin Chen, Kilian Q. Weinberger, Fei Sha
2012	A*	`conf`	Geodesic flow kernel for unsupervised domain adaptation. CVPR Boqing Gong, Yuan Shi, Fei Sha, Kristen Grauman
2012	A*	`conf`	Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation. ICML Yuan Shi, Fei Sha
2012	A*	`conf`	Learning the Kernel Matrix with Low-Rank Multiplicative Shaping. AAAI Tomer Levinboim, Fei Sha
2012	J	`jnl`	Marginalized Denoising Autoencoders for Domain Adaptation CoRR Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha
2012	A*	`conf`	Marginalized Denoising Autoencoders for Domain Adaptation. ICML Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha
2012	—	`conf`	Non-linear Metric Learning. NIPS Dor Kedem, Stephen Tyree, Kilian Q. Weinberger, Fei Sha, Gert R. G. Lanckriet
2012	A	`conf`	Predicting Likability of Speakers with Gaussian Processes. INTERSPEECH Dingchao Lu, Fei Sha
2012	—	`conf`	Semantic Kernel Forests from Multiple Taxonomies. NIPS Sung Ju Hwang, Kristen Grauman, Fei Sha
2011	B	`conf`	A Study of Web Services Performance Prediction: A Client's Perspective. MASCOTS Leslie Cheung, Leana Golubchik, Fei Sha
2011	—	`conf`	Application of moment invariants in checking the overall dimension of the head cover. EMEIT Xu Li, Fei Sha
2011	A	`conf`	Information Theoretical Clustering via Semidefinite Programming. AISTATS Meihong Wang, Fei Sha
2011	J	`jnl`	Learning Discriminative Metrics via Generative Models and Kernel Learning CoRR Yuan Shi, Yung-Kyun Noh, Fei Sha, Daniel D. Lee
2011	—	`conf`	Learning a Tree of Metrics with Disjoint Visual Features. NIPS Sung Ju Hwang, Kristen Grauman, Fei Sha
2011	A*	`conf`	Learning with Whom to Share in Multi-task Feature Learning. ICML Zhuoliang Kang, Kristen Grauman, Fei Sha
2011	A	`conf`	Metric learning for reinforcement learning agents. AAMAS Matthew E. Taylor, Brian Kulis, Fei Sha
2011	—	`conf`	Online learning of large margin hidden Markov models for automatic speech recognition. MLSLP Lawrence K. Saul, Chih-Chieh Cheng, Fei Sha
2011	J	`jnl`	Predicting Pedestrian Counts in Crowded Scenes With Rich and High-Dimensional Features. IEEE Trans. Intell. Transp. Syst. Junping Zhang, Ben Tan, Fei Sha, Li He
2011	J	`jnl`	Rapid Feature Learning with Stacked Linear Denoisers CoRR Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha
2011	A*	`conf`	Sharing features between objects and their attributes. CVPR Sung Ju Hwang, Fei Sha, Kristen Grauman
2011	Misc	`conf`	Speech recognitionwith segmental conditional random fields: A summary of the JHU CLSP 2010 Summer Workshop. ICASSP Geoffrey Zweig, Patrick Nguyen, Dirk Van Compernolle, Kris Demuynck, Les E. Atlas, Pascal Clark, Gregory Sell, Meihong Wang, Fei Sha, Hynek Hermansky, Damianos G. Karakos, Aren Jansen, Samuel Thomas, Sivaram G. S. V. S., Samuel R. Bowman, Justine T. Kao
2010	J	`jnl`	Active site prediction using evolutionary and structural information. Bioinform. Sriram Sankararaman, Fei Sha, Jack F. Kirsch, Michael I. Jordan, Kimmen Sjölander
2010	J	`jnl`	Convex Optimizations for Distance Metric Learning and Pattern Classification [Applications Corner]. IEEE Signal Process. Mag. Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul
2010	—	`conf`	Invited Talk Abstracts. AAAI Fall Symposium: Manifold Learning and Its Applications Yi Ma, Fei Sha, Lawrence Carin, Gilad Lerman, Neil D. Lawrence
2010	A	`conf`	Locally Linear Denoising on Image Manifolds. AISTATS Dian Gong, Fei Sha, Gérard G. Medioni
2010	J	`jnl`	Online Learning and Acoustic Feature Adaptation in Large-Margin Hidden Markov Models. IEEE J. Sel. Top. Signal Process. Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul
2010	—	`conf`	Unsupervised Kernel Dimension Reduction. NIPS Meihong Wang, Fei Sha, Michael I. Jordan
2009	A	`conf`	A fast online algorithm for large margin training of continuous density hidden Markov models. INTERSPEECH Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul
2009	C	`conf`	Large-margin feature adaptation for automatic speech recognition. ASRU Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul
2009	A*	`conf`	Matrix updates for perceptron training of continuous density hidden Markov models. ICML Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul
2009	—	`conf`	Robust web extraction: an approach based on a probabilistic tree-edit model. SIGMOD Conference Nilesh N. Dalvi, Philip Bohannon, Fei Sha
2008	—	`conf`	DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification. NIPS Simon Lacoste-Julien, Fei Sha, Michael I. Jordan
2007	—	`conf`	Comparison of Large Margin Training to Other Discriminative Methods for Phonetic Recognition by Hidden Markov Models. ICASSP (4) Fei Sha, Lawrence K. Saul
2007	A*	`conf`	Learning Globally-Consistent Local Distance Functions for Shape-Based Image Retrieval and Classification. ICCV Andrea Frome, Yoram Singer, Fei Sha, Jitendra Malik
2007	B	`conf`	Multiplicative Updates for IDA Fei Sha, Y. Albert Park, Lawrence K. Saul
2007	J	`jnl`	Multiplicative Updates for Nonnegative Quadratic Programming. Neural Comput. Fei Sha, Yuanqing Lin, Lawrence K. Saul, Daniel D. Lee
2007	A*	`conf`	Regression on manifolds using kernel dimension reduction. ICML Jens Nilsson, Fei Sha, Michael I. Jordan
2006	—	`conf`	Graph Laplacian Regularization for Large-Scale Semidefinite Programming. NIPS Kilian Q. Weinberger, Fei Sha, Qihui Zhu, Lawrence K. Saul
2006	—	`conf`	Large Margin Gaussian Mixture Modeling for Phonetic Classification and Recognition. ICASSP (1) Fei Sha, Lawrence K. Saul
2006	—	`conf`	Large Margin Hidden Markov Models for Automatic Speech Recognition. NIPS Fei Sha, Lawrence K. Saul
2006	—	`ch.`	Spectral Methods for Dimensionality Reduction. Semi-Supervised Learning Lawrence K. Saul, Kilian Q. Weinberger, Fei Sha, Jihun Ham, Daniel D. Lee
2005	A*	`conf`	Analysis and extension of spectral methods for nonlinear dimensionality reduction. ICML Fei Sha, Lawrence K. Saul
2004	A*	`conf`	Learning a kernel matrix for nonlinear dimensionality reduction. ICML Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul
2004	—	`conf`	Multiband statistical learning for f ICASSP (5) Fei Sha, John Ashley Burgoyne, Lawrence K. Saul
2004	—	`conf`	Real-Time Pitch Determination of One or More Voices by Nonnegative Matrix Factorization. NIPS Fei Sha, Lawrence K. Saul
2003	A*	`conf`	Multiplicative Updates for Large Margin Classifiers. COLT Fei Sha, Lawrence K. Saul, Daniel D. Lee
2003	—	`conf`	Shallow Parsing with Conditional Random Fields. HLT-NAACL Fei Sha, Fernando C. N. Pereira
2003	A	`conf`	Statistical signal processing with nonnegativity constraints. INTERSPEECH Lawrence K. Saul, Fei Sha, Daniel D. Lee
2002	—	`conf`	Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines. NIPS Fei Sha, Lawrence K. Saul, Daniel D. Lee
2000	A*	`conf`	A Semi-Structured Data Cartridge for Relational Databases. ICDE Fei Sha, Georges Gardarin, Laurent Némirovski
1999	—	`conf`	Managing Semistructured Data in Object-Relational DBMS. Proc. 15èmes Journées Bases de Données Avancées, BDA Fei Sha, Georges Gardarin, Laurent Némirovski
1999	A*	`conf`	Miro Web: Integrating Multiple Data Sources through Semistructured Data Types. VLDB Luc Bouganim, Tatiana Chan-Sine-Ying, Tuyet-Tram Dang-Ngoc, Jean-Luc Darroux, Georges Gardarin, Fei Sha
1999	A	`conf`	XML-based Components for Federating Multiple Heterogeneous Data Sources. ER Georges Gardarin, Fei Sha, Tuyet-Tram Dang-Ngoc
1997	—	`conf`	Using Conceptual Modeling and Intelligent Agents to Integrate Semi-structured Documents in Federated Databases. Conceptual Modeling Georges Gardarin, Fei Sha
1996	—	`conf`	Calibrating the Query Optimizer Cost Model of IRO-DB, an Object-Oriented Federated Database System. BDA Georges Gardarin, Fei Sha, Zhao-Hui Tang
1996	A*	`conf`	Calibrating the Query Optimizer Cost Model of IRO-DB, an Object-Oriented Federated Database System. VLDB Georges Gardarin, Fei Sha, Zhao-Hui Tang
1992	J	`jnl`	Performance Analysis of an Access Control Strategy in Integrated Networks. Comput. Networks ISDN Syst. Tülin Atmaca, Guy Pujolle, Fei Sha