Daniel Y. Fu

According to our database, Daniel Y. Fu authored at least 24 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Hydragen: High-Throughput LLM Inference with Shared Prefixes.

Jordan Juravsky, Bradley C. A. Brown, Ryan Saul Ehrlich, Daniel Y. Fu, Christopher Ré, Azalia Mirhoseini

CoRR, 2024

Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT.

Jon Saad-Falcon, Daniel Y. Fu, Simran Arora, Neel Guha, Christopher Ré

Proceedings of the Forty-first International Conference on Machine Learning, 2024

FlashFFTConv: Efficient Convolutions for Long Sequences with Tensor Cores.

Daniel Y. Fu, Hermann Kumbong, Eric Nguyen, Christopher Ré

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

High-throughput Generative Inference of Large Language Models with a Single GPU.

Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Daniel Y. Fu, Zhiqiang Xie, Beidi Chen, Clark W. Barrett, Joseph E. Gonzalez, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang

CoRR, 2023

Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions.

Stefano Massaroli, Michael Poli, Daniel Y. Fu, Hermann Kumbong, Rom N. Parnichkun, David W. Romero, Aman Timalsina, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture.

Daniel Y. Fu, Simran Arora, Jessica Grogan, Isys Johnson, Evan Sabri Eyuboglu, Armin W. Thomas, Benjamin Spector, Michael Poli, Atri Rudra, Christopher Ré

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Hyena Hierarchy: Towards Larger Convolutional Language Models.

Michael Poli, Stefano Massaroli, Eric Nguyen, Daniel Y. Fu, Tri Dao, Stephen Baccus, Yoshua Bengio, Stefano Ermon, Christopher Ré

Proceedings of the International Conference on Machine Learning, 2023

Simple Hardware-Efficient Long Convolutions for Sequence Modeling.

Daniel Y. Fu, Elliot L. Epstein, Eric Nguyen, Armin W. Thomas, Michael Zhang, Tri Dao, Atri Rudra, Christopher Ré

Proceedings of the International Conference on Machine Learning, 2023

Hungry Hungry Hippos: Towards Language Modeling with State Space Models.

Daniel Y. Fu, Tri Dao, Khaled Kamal Saab, Armin W. Thomas, Atri Rudra, Christopher Ré

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Lost in Transmission: On the Impact of Networking Corruptions on Video Machine Learning Models.

Trenton Chang, Daniel Y. Fu

CoRR, 2022

Shoring up the foundations: fusing model embeddings and weak supervision.

Mayee F. Chen, Daniel Y. Fu, Dyah Adila, Michael Zhang, Frederic Sala, Kayvon Fatahalian, Christopher Ré

Proceedings of the Uncertainty in Artificial Intelligence, 2022

FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness.

Tri Dao, Daniel Y. Fu, Stefano Ermon, Atri Rudra, Christopher Ré

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning.

Mayee F. Chen, Daniel Y. Fu, Avanika Narayan, Michael Zhang, Zhao Song, Kayvon Fatahalian, Christopher Ré

Proceedings of the International Conference on Machine Learning, 2022

TABi: Type-Aware Bi-Encoders for Open-Domain Entity Retrieval.

Megan Leszczynski, Daniel Y. Fu, Mayee F. Chen, Christopher Ré

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021

Double Descent Optimization Pattern and Aliasing: Caveats of Noisy Labels.

Florian Dubost, Khaled Kamal Saab, Erin Hong, Daniel Yang Fu, Max Pike, Siddharth Sharma, Siyi Tang, Nandita Bhaskhar, Christopher Lee-Messer, Daniel L. Rubin

CoRR, 2021

Analysis of Faces in a Decade of US Cable TV News.

James Hong, Will Crichton, Haotian Zhang, Daniel Y. Fu, Jacob Ritchie, Jeremy Barenholtz, Ben Hannel, Xinwei Yao, Michaela Murray, Geraldine Moriba, Maneesh Agrawala, Kayvon Fatahalian

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

Let's Hope it Works! Inaccurate Supervision of Neural Networks with Incorrect Labels: Application to Epilepsy.

Florian Dubost, Erin Hong, Daniel Y. Fu, Nandita Bhaskhar, Siyi Tang, Khaled Saab, Daniel L. Rubin, Jared Dunnmon, Christopher Lee-Messer

CoRR, 2020

Analyzing Who and What Appears in a Decade of US Cable TV News.

James Hong, Will Crichton, Haotian Zhang, Daniel Y. Fu, Jacob Ritchie, Jeremy Barenholtz, Ben Hannel, Xinwei Yao, Michaela Murray, Geraldine Moriba, Maneesh Agrawala, Kayvon Fatahalian

CoRR, 2020

Train and You'll Miss It: Interactive Model Iteration with Weak Supervision and Pre-Trained Embeddings.

Mayee F. Chen, Daniel Y. Fu, Frederic Sala, Sen Wu, Ravi Teja Mullapudi, Fait Poms, Kayvon Fatahalian, Christopher Ré

CoRR, 2020

Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods.

Daniel Y. Fu, Mayee F. Chen, Frederic Sala, Sarah M. Hooper, Kayvon Fatahalian, Christopher Ré

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Rekall: Specifying Video Events using Compositions of Spatiotemporal Labels.

Daniel Y. Fu, Will Crichton, James Hong, Xinwei Yao, Haotian Zhang, Anh Truong, Avanika Narayan, Maneesh Agrawala, Christopher Ré, Kayvon Fatahalian

CoRR, 2019

Multi-Resolution Weak Supervision for Sequential Data.

Paroma Varma, Frederic Sala, Shiori Sagawa, Jason Alan Fries, Daniel Y. Fu, Saelig Khattar, Ashwini Ramamoorthy, Ke Xiao, Kayvon Fatahalian, James Priest, Christopher Ré

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Automatic Parallelization of Sequential Programs.

Peter Kraft, Amos Waterland, Daniel Y. Fu, Anitha Gollamudi, Shai Szulanski, Margo I. Seltzer

CoRR, 2018

Influencing Flock Formation in Low-Density Settings.

Daniel Y. Fu, Emily S. Wang, Peter M. Krafft, Barbara J. Grosz

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018