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2020 – today
- 2022
[c19]Tri Dao, Beidi Chen, Nimit Sharad Sohoni, Arjun D. Desai, Michael Poli, Jessica Grogan, Alexander Liu, Aniruddh Rao, Atri Rudra, Christopher Ré:
Monarch: Expressive Structured Matrices for Efficient and Accurate Training. ICML 2022: 4690-4721- [c18]Chenlin Meng, Linqi Zhou, Kristy Choi, Tri Dao, Stefano Ermon:
ButterflyFlow: Building Invertible Layers with Butterfly Matrices. ICML 2022: 15360-15375 - [i18]Tri Dao, Beidi Chen, Nimit Sharad Sohoni, Arjun D. Desai, Michael Poli, Jessica Grogan, Alexander Liu, Aniruddh Rao, Atri Rudra, Christopher Ré:
Monarch: Expressive Structured Matrices for Efficient and Accurate Training. CoRR abs/2204.00595 (2022) - [i17]Tri Dao, Daniel Y. Fu, Stefano Ermon, Atri Rudra, Christopher Ré:
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness. CoRR abs/2205.14135 (2022) - [i16]Binhang Yuan, Yongjun He, Jared Quincy Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Ré, Ce Zhang:
Decentralized Training of Foundation Models in Heterogeneous Environments. CoRR abs/2206.01288 (2022) - [i15]Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Ré, Ce Zhang:
Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees. CoRR abs/2206.01299 (2022) - 2021
- [c17]Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan Lingjie Li, Tri Dao, Zhao Song, Anshumali Shrivastava, Christopher Ré:
MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training. ICLR 2021 - [c16]Tri Dao, Govinda M. Kamath, Vasilis Syrgkanis, Lester Mackey:
Knowledge Distillation as Semiparametric Inference. ICLR 2021 - [c15]Jared Quincy Davis, Albert Gu, Krzysztof Choromanski, Tri Dao, Christopher Ré, Chelsea Finn, Percy Liang:
Catformer: Designing Stable Transformers via Sensitivity Analysis. ICML 2021: 2489-2499 - [c14]Albert Gu, Isys Johnson, Karan Goel, Khaled Saab, Tri Dao, Atri Rudra, Christopher Ré:
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers. NeurIPS 2021: 572-585 - [c13]Nicholas Roberts, Mikhail Khodak, Tri Dao, Liam Li, Christopher Ré, Ameet Talwalkar:
Rethinking Neural Operations for Diverse Tasks. NeurIPS 2021: 15855-15869 - [c12]Beidi Chen, Tri Dao, Eric Winsor, Zhao Song, Atri Rudra, Christopher Ré:
Scatterbrain: Unifying Sparse and Low-rank Attention. NeurIPS 2021: 17413-17426 - [i14]Nicholas Roberts, Mikhail Khodak, Tri Dao, Liam Li, Christopher Ré, Ameet Talwalkar:
Rethinking Neural Operations for Diverse Tasks. CoRR abs/2103.15798 (2021) - [i13]Tri Dao, Govinda M. Kamath, Vasilis Syrgkanis, Lester Mackey:
Knowledge Distillation as Semiparametric Inference. CoRR abs/2104.09732 (2021) - [i12]Albert Gu, Isys Johnson, Karan Goel, Khaled Saab, Tri Dao, Atri Rudra, Christopher Ré:
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layers. CoRR abs/2110.13985 (2021) - [i11]Beidi Chen, Tri Dao, Eric Winsor, Zhao Song, Atri Rudra, Christopher Ré:
Scatterbrain: Unifying Sparse and Low-rank Attention Approximation. CoRR abs/2110.15343 (2021) - [i10]Beidi Chen, Tri Dao, Kaizhao Liang, Jiaming Yang, Zhao Song, Atri Rudra, Christopher Ré:
Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models. CoRR abs/2112.00029 (2021) - 2020
- [c11]Tri Dao, Nimit Sharad Sohoni, Albert Gu, Matthew Eichhorn, Amit Blonder, Megan Leszczynski, Atri Rudra, Christopher Ré:
Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps. ICLR 2020 - [c10]Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, Christopher Ré:
HiPPO: Recurrent Memory with Optimal Polynomial Projections. NeurIPS 2020 - [i9]Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, Christopher Ré:
HiPPO: Recurrent Memory with Optimal Polynomial Projections. CoRR abs/2008.07669 (2020) - [i8]Tri Dao, Nimit Sharad Sohoni, Albert Gu, Matthew Eichhorn, Amit Blonder, Megan Leszczynski, Atri Rudra, Christopher Ré:
Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps. CoRR abs/2012.14966 (2020)
2010 – 2019
- 2019
- [c9]Jian Zhang, Avner May, Tri Dao, Christopher Ré:
Low-Precision Random Fourier Features for Memory-constrained Kernel Approximation. AISTATS 2019: 1264-1274 - [c8]Tri Dao, Albert Gu, Matthew Eichhorn, Atri Rudra, Christopher Ré:
Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations. ICML 2019: 1517-1527 - [c7]Tri Dao, Albert Gu, Alexander Ratner, Virginia Smith, Chris De Sa, Christopher Ré:
A Kernel Theory of Modern Data Augmentation. ICML 2019: 1528-1537 - [c6]Jonathan Kuck, Tri Dao, Hamid Rezatofighi, Ashish Sabharwal, Stefano Ermon:
Approximating the Permanent by Sampling from Adaptive Partitions. NeurIPS 2019: 8858-8869 - [c5]Avner May, Jian Zhang, Tri Dao, Christopher Ré:
On the Downstream Performance of Compressed Word Embeddings. NeurIPS 2019: 11782-11793 - [c4]Jonathan Kuck, Tri Dao, Shenjia Zhao, Burak Bartan, Ashish Sabharwal, Stefano Ermon:
Adaptive Hashing for Model Counting. UAI 2019: 271-280 - [i7]Tri Dao, Albert Gu, Matthew Eichhorn, Atri Rudra, Christopher Ré:
Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations. CoRR abs/1903.05895 (2019) - [i6]Avner May, Jian Zhang, Tri Dao, Christopher Ré:
On the Downstream Performance of Compressed Word Embeddings. CoRR abs/1909.01264 (2019) - [i5]Jonathan Kuck, Tri Dao, Hamid Rezatofighi, Ashish Sabharwal, Stefano Ermon:
Approximating the Permanent by Sampling from Adaptive Partitions. CoRR abs/1911.11856 (2019) - 2018
- [c3]Anna T. Thomas, Albert Gu, Tri Dao, Atri Rudra, Christopher Ré:
Learning Invariance with Compact Transforms. ICLR (Workshop) 2018 - [c2]Anna T. Thomas, Albert Gu, Tri Dao, Atri Rudra, Christopher Ré:
Learning Compressed Transforms with Low Displacement Rank. NeurIPS 2018: 9066-9078 - [i4]Tri Dao, Albert Gu, Alexander J. Ratner, Virginia Smith, Christopher De Sa, Christopher Ré:
A Kernel Theory of Modern Data Augmentation. CoRR abs/1803.06084 (2018) - [i3]Anna T. Thomas, Albert Gu, Tri Dao, Atri Rudra, Christopher Ré:
Learning Compressed Transforms with Low Displacement Rank. CoRR abs/1810.02309 (2018) - [i2]Jian Zhang, Avner May, Tri Dao, Christopher Ré:
Low-Precision Random Fourier Features for Memory-Constrained Kernel Approximation. CoRR abs/1811.00155 (2018) - 2017
- [c1]Tri Dao, Christopher De Sa, Christopher Ré:
Gaussian Quadrature for Kernel Features. NIPS 2017: 6107-6117 - [i1]Tri Dao, Christopher De Sa, Christopher Ré:
Gaussian Quadrature for Kernel Features. CoRR abs/1709.02605 (2017)
Coauthor Index
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