Search Results for author: Xiaoxiao Wang

Found 10 papers, 2 papers with code

SPSTracker: Sub-Peak Suppression of Response Map for Robust Object Tracking

1 code implementation2 Dec 2019 Qintao Hu, Lijun Zhou, Xiaoxiao Wang, Yao Mao, Jianlin Zhang, Qixiang Ye

Modern visual trackers usually construct online learning models under the assumption that the feature response has a Gaussian distribution with target-centered peak response.

Object Tracking

AdaLinUCB: Opportunistic Learning for Contextual Bandits

no code implementations20 Feb 2019 Xueying Guo, Xiaoxiao Wang, Xin Liu

In this paper, we propose and study opportunistic contextual bandits - a special case of contextual bandits where the exploration cost varies under different environmental conditions, such as network load or return variation in recommendations.

Multi-Armed Bandits

BWCNN: Blink to Word, a Real-Time Convolutional Neural Network Approach

no code implementations1 Jun 2020 Albara Ah Ramli, Rex Liu, Rahul Krishnamoorthy, Vishal I B, Xiaoxiao Wang, Ilias Tagkopoulos, Xin Liu

The system uses a Convolutional Neural Network (CNN) to find the blinking pattern, which is defined as a series of Open and Closed states.

FINETUNA: Fine-tuning Accelerated Molecular Simulations

no code implementations2 May 2022 Joseph Musielewicz, Xiaoxiao Wang, Tian Tian, Zachary Ulissi

Finally, we demonstrate a technique for leveraging the interactive functionality built in to VASP to efficiently compute single point calculations within our online active learning framework without the significant startup costs.

Active Learning Transfer Learning

Opportunistic Episodic Reinforcement Learning

no code implementations24 Oct 2022 Xiaoxiao Wang, Nader Bouacida, Xueying Guo, Xin Liu

In this paper, we propose and study opportunistic reinforcement learning - a new variant of reinforcement learning problems where the regret of selecting a suboptimal action varies under an external environmental condition known as the variation factor.

reinforcement-learning Reinforcement Learning (RL)

MRGazer: Decoding Eye Gaze Points from Functional Magnetic Resonance Imaging in Individual Space

no code implementations22 Nov 2023 Xiuwen Wu, Rongjie Hu, Jie Liang, Yanming Wang, Bensheng Qiu, Xiaoxiao Wang

Compared to the previous method, the proposed framework skips the fMRI co-registration step, simplifies the processing protocol and achieves end-to-end eye gaze regression.

Gaze Prediction

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