From d7fc90ddcd623640546268deaad4495405036a20 Mon Sep 17 00:00:00 2001 From: lwwang1995 Date: Fri, 27 Nov 2020 23:36:29 +0800 Subject: [PATCH] Update readme. --- examples/benchmarks/ALSTM/README.md | 4 +--- examples/benchmarks/SFM/README.md | 1 - 2 files changed, 1 insertion(+), 4 deletions(-) diff --git a/examples/benchmarks/ALSTM/README.md b/examples/benchmarks/ALSTM/README.md index cd9dd3493..1b749bd80 100644 --- a/examples/benchmarks/ALSTM/README.md +++ b/examples/benchmarks/ALSTM/README.md @@ -2,9 +2,7 @@ - ALSTM contains a temporal attentive aggregation layer based on normal LSTM. -- The code used in Qlib is a pyTorch implementation of Code: https://github.com/fulifeng/Adv-ALSTM - - Paper: A dual-stage attention-based recurrent neural network for time series prediction. - https://www.ijcai.org/Proceedings/2017/0366.pdf + [https://www.ijcai.org/Proceedings/2017/0366.pdf](https://www.ijcai.org/Proceedings/2017/0366.pdf) diff --git a/examples/benchmarks/SFM/README.md b/examples/benchmarks/SFM/README.md index eb1c8b157..5f74c15d2 100644 --- a/examples/benchmarks/SFM/README.md +++ b/examples/benchmarks/SFM/README.md @@ -1,4 +1,3 @@ # State-Frequency-Memory - State Frequency Memory (SFM) is a novel recurrent network that uses Discrete Fourier Transform to decompose the hidden states of memory cells and capture the multi-frequency trading patterns from past market data to make stock price predictions. -- The code used in Qlib is a pyTorch implementation of SFM. - Paper: Stock Price Prediction via Discovering Multi-Frequency Trading Patterns. [https://www.cs.ucf.edu/~gqi/publications/kdd2017_stock.pdf.](https://www.cs.ucf.edu/~gqi/publications/kdd2017_stock.pdf.) \ No newline at end of file