Search Results for author: Jian Guo

Found 21 papers, 13 papers with code

Dynamic Datasets and Market Environments for Financial Reinforcement Learning

1 code implementation25 Apr 2023 Xiao-Yang Liu, Ziyi Xia, Hongyang Yang, Jiechao Gao, Daochen Zha, Ming Zhu, Christina Dan Wang, Zhaoran Wang, Jian Guo

The financial market is a particularly challenging playground for deep reinforcement learning due to its unique feature of dynamic datasets.


Enhancing Chain-of-Thoughts Prompting with Iterative Bootstrapping in Large Language Models

1 code implementation23 Apr 2023 Jiashuo Sun, Yi Luo, Yeyun Gong, Chen Lin, Yelong Shen, Jian Guo, Nan Duan

By utilizing iterative bootstrapping, our approach enables LLMs to autonomously rectify errors, resulting in more precise and comprehensive reasoning chains.

APOLLO: An Optimized Training Approach for Long-form Numerical Reasoning

1 code implementation14 Dec 2022 Jiashuo Sun, Hang Zhang, Chen Lin, Yeyun Gong, Jian Guo, Nan Duan

For the retriever, we adopt a number-aware negative sampling strategy to enable the retriever to be more discriminative on key numerical facts.

Conversational Question Answering

Quant 4.0: Engineering Quantitative Investment with Automated, Explainable and Knowledge-driven Artificial Intelligence

no code implementations13 Dec 2022 Jian Guo, Saizhuo Wang, Lionel M. Ni, Heung-Yeung Shum

Quant has become one of the mainstream investment methodologies over the past decades, and has experienced three generations: Quant 1. 0, trading by mathematical modeling to discover mis-priced assets in markets; Quant 2. 0, shifting quant research pipeline from small ``strategy workshops'' to large ``alpha factories''; Quant 3. 0, applying deep learning techniques to discover complex nonlinear pricing rules.


FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning

4 code implementations6 Nov 2022 Xiao-Yang Liu, Ziyi Xia, Jingyang Rui, Jiechao Gao, Hongyang Yang, Ming Zhu, Christina Dan Wang, Zhaoran Wang, Jian Guo

However, establishing high-quality market environments and benchmarks for financial reinforcement learning is challenging due to three major factors, namely, low signal-to-noise ratio of financial data, survivorship bias of historical data, and model overfitting in the backtesting stage.

reinforcement-learning Reinforcement Learning (RL)

Sentiment-Aware Word and Sentence Level Pre-training for Sentiment Analysis

1 code implementation18 Oct 2022 Shuai Fan, Chen Lin, Haonan Li, Zhenghao Lin, Jinsong Su, Hang Zhang, Yeyun Gong, Jian Guo, Nan Duan

Most existing pre-trained language representation models (PLMs) are sub-optimal in sentiment analysis tasks, as they capture the sentiment information from word-level while under-considering sentence-level information.

Contrastive Learning Language Modelling +2

Optimistic Curiosity Exploration and Conservative Exploitation with Linear Reward Shaping

1 code implementation15 Sep 2022 Hao Sun, Lei Han, Rui Yang, Xiaoteng Ma, Jian Guo, Bolei Zhou

We validate our insight on a range of RL tasks and show its improvement over baselines: (1) In offline RL, the conservative exploitation leads to improved performance based on off-the-shelf algorithms; (2) In online continuous control, multiple value functions with different shifting constants can be used to tackle the exploration-exploitation dilemma for better sample efficiency; (3) In discrete control tasks, a negative reward shifting yields an improvement over the curiosity-based exploration method.

Continuous Control Offline RL

Finger Multimodal Feature Fusion and Recognition Based on Channel Spatial Attention

no code implementations6 Sep 2022 Jian Guo, Jiaxiang Tu, Hengyi Ren, Chong Han, Lijuan Sun

In this paper, we propose a multimodal biometric fusion recognition algorithm based on fingerprints and finger veins (Fingerprint Finger Veins-Channel Spatial Attention Fusion Module, FPV-CSAFM).

Vision-Language Intelligence: Tasks, Representation Learning, and Large Models

no code implementations3 Mar 2022 Feng Li, Hao Zhang, Yi-Fan Zhang, Shilong Liu, Jian Guo, Lionel M. Ni, Pengchuan Zhang, Lei Zhang

This survey is inspired by the remarkable progress in both computer vision and natural language processing, and recent trends shifting from single modality processing to multiple modality comprehension.

Few-Shot Learning Representation Learning

DN-DETR: Accelerate DETR Training by Introducing Query DeNoising

11 code implementations CVPR 2022 Feng Li, Hao Zhang, Shilong Liu, Jian Guo, Lionel M. Ni, Lei Zhang

Our method is universal and can be easily plugged into any DETR-like methods by adding dozens of lines of code to achieve a remarkable improvement.

Object Detection

ElegantRL-Podracer: Scalable and Elastic Library for Cloud-Native Deep Reinforcement Learning

1 code implementation11 Dec 2021 Xiao-Yang Liu, Zechu Li, Zhuoran Yang, Jiahao Zheng, Zhaoran Wang, Anwar Walid, Jian Guo, Michael I. Jordan

In this paper, we present a scalable and elastic library ElegantRL-podracer for cloud-native deep reinforcement learning, which efficiently supports millions of GPU cores to carry out massively parallel training at multiple levels.

reinforcement-learning Reinforcement Learning (RL) +1

FinRL-Podracer: High Performance and Scalable Deep Reinforcement Learning for Quantitative Finance

no code implementations7 Nov 2021 Zechu Li, Xiao-Yang Liu, Jiahao Zheng, Zhaoran Wang, Anwar Walid, Jian Guo

Unfortunately, the steep learning curve and the difficulty in quick modeling and agile development are impeding finance researchers from using deep reinforcement learning in quantitative trading.

reinforcement-learning Reinforcement Learning (RL) +1

Reward Shifting for Optimistic Exploration and Conservative Exploitation

no code implementations29 Sep 2021 Hao Sun, Lei Han, Jian Guo, Bolei Zhou

We verify our insight on a range of tasks: (1) In offline RL, the conservative exploitation leads to improved learning performance based on off-the-shelf algorithms; (2) In online continuous control, multiple value functions with different shifting constants can be used to trade-off between exploration and exploitation thus improving learning efficiency; (3) In online RL with discrete action space, a negative reward shifting brings an improvement over the previous curiosity-based exploration method.

Continuous Control Offline RL

VisMCA: A Visual Analytics System for Misclassification Correction and Analysis. VAST Challenge 2020, Mini-Challenge 2 Award: Honorable Mention for Detailed Analysis of Patterns of Misclassification

no code implementations22 Jul 2021 Huyen N. Nguyen, Jake Gonzalez, Jian Guo, Ngan V. T. Nguyen, Tommy Dang

This paper presents VisMCA, an interactive visual analytics system that supports deepening understanding in ML results, augmenting users' capabilities in correcting misclassification, and providing an analysis of underlying patterns, in response to the VAST Challenge 2020 Mini-Challenge 2.

object-detection Object Detection

A model-based framework for learning transparent swarm behaviors

1 code implementation9 Mar 2021 Mario Coppola, Jian Guo, Eberhard Gill, Guido C. H. E. de Croon

The framework is based on the automatic extraction of two distinct models: 1) a neural network model trained to estimate the relationship between the robots' sensor readings and the global performance of the swarm, and 2) a probabilistic state transition model that explicitly models the local state transitions (i. e., transitions in observations from the perspective of a single robot in the swarm) given a policy.

GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing

4 code implementations9 Jul 2019 Jian Guo, He He, Tong He, Leonard Lausen, Mu Li, Haibin Lin, Xingjian Shi, Chenguang Wang, Junyuan Xie, Sheng Zha, Aston Zhang, Hang Zhang, Zhi Zhang, Zhongyue Zhang, Shuai Zheng, Yi Zhu

We present GluonCV and GluonNLP, the deep learning toolkits for computer vision and natural language processing based on Apache MXNet (incubating).

Provable Emergent Pattern Formation by a Swarm of Anonymous, Homogeneous, Non-Communicating, Reactive Robots with Limited Relative Sensing and no Global Knowledge or Positioning

no code implementations18 Apr 2018 Mario Coppola, Jian Guo, Eberhard K. A. Gill, Guido C. H. E. de Croon

We then formally show that these local states can only coexist when the global desired pattern is achieved and that, until this occurs, there is always a sequence of actions that will lead from the current pattern to the desired pattern.


Deep CNN Ensemble with Data Augmentation for Object Detection

no code implementations24 Jun 2015 Jian Guo, Stephen Gould

We report on the methods used in our recent DeepEnsembleCoco submission to the PASCAL VOC 2012 challenge, which achieves state-of-the-art performance on the object detection task.

Data Augmentation object-detection +1

Cannot find the paper you are looking for? You can Submit a new open access paper.