Search Results for author: Shan Zhong

Found 7 papers, 2 papers with code

Differentially Private Low-Rank Adaptation of Large Language Model Using Federated Learning

no code implementations29 Dec 2023 Xiao-Yang Liu, Rongyi Zhu, Daochen Zha, Jiechao Gao, Shan Zhong, Meikang Qiu

The surge in interest and application of large language models (LLMs) has sparked a drive to fine-tune these models to suit specific applications, such as finance and medical science.

Federated Learning Language Modelling +1

Interactive Model Fusion-Based GM-PHD Filter

no code implementations15 Sep 2023 Jiacheng He, Shan Zhong, Bei Peng, Gang Wang, Qizhen Wang

In multi-target tracking (MTT), non-Gaussian measurement noise from sensors can diminish the performance of the Gaussian-assumed Gaussian mixture probability hypothesis density (GM-PHD) filter.

Variational Bayesian Approximations Kalman Filter Based on Threshold Judgment

no code implementations6 Sep 2023 Zuxuan Zhang, Gang Wang, Jiacheng He, Shan Zhong

The estimation of non-Gaussian measurement noise models is a significant challenge across various fields.

Seasonality Based Reranking of E-commerce Autocomplete Using Natural Language Queries

no code implementations3 Aug 2023 Prateek Verma, Shan Zhong, Xiaoyu Liu, Adithya Rajan

Query autocomplete (QAC) also known as typeahead, suggests list of complete queries as user types prefix in the search box.

Natural Language Queries

Minimum Error Entropy Rauch-Tung-Striebel Smoother

no code implementations14 Jan 2023 Jiacheng He, Hongwei Wang, Gang Wang, Shan Zhong, Bei Peng

Outliers and impulsive disturbances often cause heavy-tailed distributions in practical applications, and these will degrade the performance of Gaussian approximation smoothing algorithms.

S&P 500 Stock Price Prediction Using Technical, Fundamental and Text Data

1 code implementation24 Aug 2021 Shan Zhong, David B. Hitchcock

We summarized both common and novel predictive models used for stock price prediction and combined them with technical indices, fundamental characteristics and text-based sentiment data to predict S&P stock prices.

BIG-bench Machine Learning Stock Price Prediction +2

Practical Deep Reinforcement Learning Approach for Stock Trading

9 code implementations19 Nov 2018 Xiao-Yang Liu, Zhuoran Xiong, Shan Zhong, Hongyang Yang, Anwar Walid

We explore the potential of deep reinforcement learning to optimize stock trading strategy and thus maximize investment return.

reinforcement-learning Reinforcement Learning (RL)

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