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Yeqi Gao
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2020 – today
- 2024
- [c3]Yeqi Gao, Lianke Qin, Zhao Song, Yitan Wang:
A Sublinear Adversarial Training Algorithm. ICLR 2024 - [i13]Yeqi Gao, Zhao Song, Ruizhe Zhang:
Quantum Speedup for Spectral Approximation of Kronecker Products. CoRR abs/2402.07027 (2024) - [i12]Yeqi Gao, Yuzhou Gu, Zhao Song:
Binary Hypothesis Testing for Softmax Models and Leverage Score Models. CoRR abs/2405.06003 (2024) - 2023
- [c2]Yichuan Deng, Yeqi Gao, Zhao Song:
Solving Tensor Low Cycle Rank Approximation. IEEE Big Data 2023: 6-16 - [i11]Yeqi Gao, Sridhar Mahadevan, Zhao Song:
An Over-parameterized Exponential Regression. CoRR abs/2303.16504 (2023) - [i10]Yichuan Deng, Yeqi Gao, Zhao Song:
Solving Tensor Low Cycle Rank Approximation. CoRR abs/2304.06594 (2023) - [i9]Yeqi Gao, Zhao Song, Junze Yin:
An Iterative Algorithm for Rescaled Hyperbolic Functions Regression. CoRR abs/2305.00660 (2023) - [i8]Yeqi Gao, Zhao Song, Xin Yang:
Differentially Private Attention Computation. CoRR abs/2305.04701 (2023) - [i7]Yeqi Gao, Zhao Song, Shenghao Xie:
In-Context Learning for Attention Scheme: from Single Softmax Regression to Multiple Softmax Regression via a Tensor Trick. CoRR abs/2307.02419 (2023) - [i6]Yeqi Gao, Zhao Song, Xin Yang, Ruizhe Zhang:
Fast Quantum Algorithm for Attention Computation. CoRR abs/2307.08045 (2023) - [i5]Yeqi Gao, Zhao Song, Junze Yin:
GradientCoin: A Peer-to-Peer Decentralized Large Language Models. CoRR abs/2308.10502 (2023) - [i4]Yeqi Gao, Zhao Song, Weixin Wang, Junze Yin:
A Fast Optimization View: Reformulating Single Layer Attention in LLM Based on Tensor and SVM Trick, and Solving It in Matrix Multiplication Time. CoRR abs/2309.07418 (2023) - 2022
- [i3]Yeqi Gao, Lianke Qin, Zhao Song, Yitan Wang:
A Sublinear Adversarial Training Algorithm. CoRR abs/2208.05395 (2022) - [i2]Yeqi Gao, Zhao Song, Baocheng Sun:
An O(k log n) Time Fourier Set Query Algorithm. CoRR abs/2208.09634 (2022) - 2021
- [c1]Ao Zhou
, Jianlei Yang, Yeqi Gao, Tong Qiao, Yingjie Qi, Xiaoyi Wang, Yunli Chen, Pengcheng Dai, Weisheng Zhao, Chunming Hu:
Brief Industry Paper: optimizing Memory Efficiency of Graph Neural Networks on Edge Computing Platforms. RTAS 2021: 445-448 - [i1]Ao Zhou, Jianlei Yang, Yeqi Gao, Tong Qiao, Yingjie Qi, Xiaoyi Wang, Yunli Chen, Pengcheng Dai, Weisheng Zhao, Chunming Hu:
Optimizing Memory Efficiency of Graph Neural Networks on Edge Computing Platforms. CoRR abs/2104.03058 (2021)
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