Search Results for author: Jie Zheng

Found 13 papers, 4 papers with code

Credentials in the Occupation Ontology

no code implementations30 Apr 2024 John Beverley, Robin McGill, Sam Smith, Jie Zheng, Giacomo De Colle, Finn Wilson, Matthew Diller, William D. Duncan, William R. Hogan, Yongqun He

The term credential encompasses educational certificates, degrees, certifications, and government-issued licenses.

Large Language Models for Automated Open-domain Scientific Hypotheses Discovery

1 code implementation6 Sep 2023 Zonglin Yang, Xinya Du, Junxian Li, Jie Zheng, Soujanya Poria, Erik Cambria

Hypothetical induction is recognized as the main reasoning type when scientists make observations about the world and try to propose hypotheses to explain those observations.


Weakly supervised learning for pattern classification in serial femtosecond crystallography

no code implementations30 Jul 2023 Jianan Xie, Ji Liu, Chi Zhang, Xihui Chen, Ping Huai, Jie Zheng, Xiaofeng Zhang

Th is heavy dependence on labeled datasets will seriously restrict the application of networks, because it is very costly to annotate a large number of diffraction patterns.

Weakly-supervised Learning

Biological Factor Regulatory Neural Network

1 code implementation11 Apr 2023 Xinnan Dai, Caihua Shan, Jie Zheng, Xiaoxiao Li, Dongsheng Li

BFReg-NN starts from gene expression data and is capable of merging most existing biological knowledge into the model, including the regulatory relations among genes or proteins (e. g., gene regulatory networks (GRN), protein-protein interaction networks (PPI)) and the hierarchical relations among genes, proteins and pathways (e. g., several genes/proteins are contained in a pathway).

Constrained Reinforcement Learning for Short Video Recommendation

no code implementations26 May 2022 Qingpeng Cai, Ruohan Zhan, Chi Zhang, Jie Zheng, Guangwei Ding, Pinghua Gong, Dong Zheng, Peng Jiang

In this paper, we formulate the problem of short video recommendation as a constrained Markov Decision Process (MDP), where platforms want to optimize the main goal of user watch time in long term, with the constraint of accommodating the auxiliary responses of user interactions such as sharing/downloading videos.

Recommendation Systems reinforcement-learning +1

Exploring the Impact of Negative Samples of Contrastive Learning: A Case Study of Sentence Embedding

1 code implementation Findings (ACL) 2022 Rui Cao, Yihao Wang, Yuxin Liang, Ling Gao, Jie Zheng, Jie Ren, Zheng Wang

We define a maximum traceable distance metric, through which we learn to what extent the text contrastive learning benefits from the historical information of negative samples.

Contrastive Learning Sentence +4

ESOD:Edge-based Task Scheduling for Object Detection

no code implementations20 Oct 2021 Yihao Wang, Ling Gao, Jie Ren, Rui Cao, Hai Wang, Jie Zheng, Quanli Gao

In detail, we train a DNN model (termed as pre-model) to predict which object detection model to use for the coming task and offloads to which edge servers by physical characteristics of the image task (e. g., brightness, saturation).

Object object-detection +2

PASTO: Strategic Parameter Optimization in Recommendation Systems -- Probabilistic is Better than Deterministic

no code implementations20 Aug 2021 Weicong Ding, Hanlin Tang, Jingshuo Feng, Lei Yuan, Sen yang, Guangxu Yang, Jie Zheng, Jing Wang, Qiang Su, Dong Zheng, Xuezhong Qiu, Yongqi Liu, Yuxuan Chen, Yang Liu, Chao Song, Dongying Kong, Kai Ren, Peng Jiang, Qiao Lian, Ji Liu

In this setting with multiple and constrained goals, this paper discovers that a probabilistic strategic parameter regime can achieve better value compared to the standard regime of finding a single deterministic parameter.

Recommendation Systems

Learning to Remove: Towards Isotropic Pre-trained BERT Embedding

1 code implementation12 Apr 2021 Yuxin Liang, Rui Cao, Jie Zheng, Jie Ren, Ling Gao

We train the weights on word similarity tasks and show that processed embedding is more isotropic.

Semantic Textual Similarity Word Similarity

To Compress, or Not to Compress: Characterizing Deep Learning Model Compression for Embedded Inference

no code implementations21 Oct 2018 Qing Qin, Jie Ren, Jialong Yu, Ling Gao, Hai Wang, Jie Zheng, Yansong Feng, Jianbin Fang, Zheng Wang

We experimentally show that how two mainstream compression techniques, data quantization and pruning, perform on these network architectures and the implications of compression techniques to the model storage size, inference time, energy consumption and performance metrics.

Image Classification Model Compression +1

SL$^2$MF: Predicting Synthetic Lethality in Human Cancers via Logistic Matrix Factorization

no code implementations20 Oct 2018 Yong Liu, Min Wu, Chenghao Liu, Xiao-Li Li, Jie Zheng

Moreover, we also incorporate biological knowledge about genes from protein-protein interaction (PPI) data and Gene Ontology (GO).

Convolutional neural network based automatic plaque characterization from intracoronary optical coherence tomography images

no code implementations10 Jul 2018 Shenghua He, Jie Zheng, Akiko Maehara, Gary Mintz, Dalin Tang, Mark Anastasio, Hua Li

Traditional machine learning based methods, such as the least squares support vector machine and random forest methods, have been recently employed to automatically characterize plaque regions in OCT images.

Classification feature selection +2

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