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2020 – today
- 2024
[i11]Zhuoming Chen, Avner May, Ruslan Svirschevski, Yuhsun Huang, Max Ryabinin, Zhihao Jia, Beidi Chen:
Sequoia: Scalable, Robust, and Hardware-aware Speculative Decoding. CoRR abs/2402.12374 (2024)- [i10]Ruslan Svirschevski, Avner May, Zhuoming Chen, Beidi Chen, Zhihao Jia, Max Ryabinin:
SpecExec: Massively Parallel Speculative Decoding for Interactive LLM Inference on Consumer Devices. CoRR abs/2406.02532 (2024) - [i9]Junxiong Wang, Daniele Paliotta, Avner May, Alexander M. Rush, Tri Dao:
The Mamba in the Llama: Distilling and Accelerating Hybrid Models. CoRR abs/2408.15237 (2024) - 2023
- [i8]Avner May, Dmitriy Serdyuk, Ankit Parag Shah, Otavio Braga, Olivier Siohan:
Audio-visual fine-tuning of audio-only ASR models. CoRR abs/2312.09369 (2023) - 2020
- [c7]Simran Arora, Avner May, Jian Zhang, Christopher Ré:
Contextual Embeddings: When Are They Worth It? ACL 2020: 2650-2663 - [c6]Megan Leszczynski, Avner May, Jian Zhang, Sen Wu, Christopher R. Aberger, Christopher Ré:
Understanding the Downstream Instability of Word Embeddings. MLSys 2020 - [i7]Megan Leszczynski, Avner May, Jian Zhang, Sen Wu, Christopher R. Aberger, Christopher Ré:
Understanding the Downstream Instability of Word Embeddings. CoRR abs/2003.04983 (2020) - [i6]Simran Arora, Avner May, Jian Zhang, Christopher Ré:
Contextual Embeddings: When Are They Worth It? CoRR abs/2005.09117 (2020)
2010 – 2019
- 2019
- [j1]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: 59:1-59:36 (2019) - [c5]Jian Zhang, Avner May, Tri Dao, Christopher Ré:
Low-Precision Random Fourier Features for Memory-constrained Kernel Approximation. AISTATS 2019: 1264-1274 - [c4]Avner May, Jian Zhang, Tri Dao, Christopher Ré:
On the Downstream Performance of Compressed Word Embeddings. NeurIPS 2019: 11782-11793 - [i5]Avner May, Jian Zhang, Tri Dao, Christopher Ré:
On the Downstream Performance of Compressed Word Embeddings. CoRR abs/1909.01264 (2019) - 2018
- [b1]Avner May:
Kernel Approximation Methods for Speech Recognition. Columbia University, USA, 2018 - [i4]Jian Zhang, Avner May, Tri Dao, Christopher Ré:
Low-Precision Random Fourier Features for Memory-Constrained Kernel Approximation. CoRR abs/1811.00155 (2018) - 2017
- [i3]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:
Kernel Approximation Methods for Speech Recognition. CoRR abs/1701.03577 (2017) - 2016
- [c3]Avner May, Michael Collins, Daniel J. Hsu, Brian Kingsbury:
Compact kernel models for acoustic modeling via random feature selection. ICASSP 2016: 2424-2428 - [c2]Zhiyun Lu, Dong Guo, Alireza Bagheri Garakani, Kuan Liu, Avner May, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha:
A comparison between deep neural nets and kernel acoustic models for speech recognition. ICASSP 2016: 5070-5074 - [i2]Zhiyun Lu, Dong Guo, Alireza Bagheri Garakani, Kuan Liu, Avner May, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha:
A Comparison between Deep Neural Nets and Kernel Acoustic Models for Speech Recognition. CoRR abs/1603.05800 (2016) - 2014
- [c1]Avner May, Augustin Chaintreau
, Nitish Korula, Silvio Lattanzi:
Filter & follow: how social media foster content curation. SIGMETRICS 2014: 43-55 - [i1]Zhiyun Lu, Avner May, Kuan Liu, Alireza Bagheri Garakani, Dong Guo, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha:
How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets. CoRR abs/1411.4000 (2014)
Coauthor Index
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last updated on 2024-10-01 21:40 CEST by the dblp team
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