3 citations · 6 across the 6 of their papers we have counts for
6 papers
GenTT: Generate Vectorized Codes for General Tensor Permutation
Yaojian Chen, Tianyu Ma, An Yang +3
Tensor permutation is a fundamental operation widely applied in AI, tensor networks, and related fields. However, it is extremely complex, and different shapes and permutation maps…
A Mamba Foundation Model for Time Series Forecasting
Haoyu Ma, Yushu Chen, Wenlai Zhao +7
Time series foundation models have demonstrated strong performance in zero-shot learning, making them well-suited for predicting rapidly evolving patterns in real-world application…
RecycleGPT: An Autoregressive Language Model with Recyclable Module
Yufan Jiang, Qiaozhi He, Xiaomin Zhuang +4
Existing large language models have to run K times to generate a sequence of K tokens. In this paper, we present RecycleGPT, a generative language model with fast decoding speed by…
A Joint Time-frequency Domain Transformer for Multivariate Time Series Forecasting
Yushu Chen, Shengzhuo Liu, Jinzhe Yang +3
In order to enhance the performance of Transformer models for long-term multivariate forecasting while minimizing computational demands, this paper introduces the Joint Time-Freque…
An Adaptive Remote Stochastic Gradient Method for Training Neural Networks
Yushu Chen, Hao Jing, Wenlai Zhao +5
We present the remote stochastic gradient (RSG) method, which computes the gradients at configurable remote observation points, in order to improve the convergence rate and suppres…
swCaffe: a Parallel Framework for Accelerating Deep Learning Applications on Sunway TaihuLight
Jiarui Fang, Liandeng Li, Haohuan Fu +5
This paper reports our efforts on swCaffe, a highly efficient parallel framework for accelerating deep neural networks (DNNs) training on Sunway TaihuLight, the current fastest sup…