Search Results for author: Lei Zheng

Found 19 papers, 10 papers with code

Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer

1 code implementation14 Aug 2021 Ziwei Fan, Zhiwei Liu, Jiawei Zhang, Yun Xiong, Lei Zheng, Philip S. Yu

Therefore, we propose to unify sequential patterns and temporal collaborative signals to improve the quality of recommendation, which is rather challenging.

Modeling Sequences as Distributions with Uncertainty for Sequential Recommendation

1 code implementation11 Jun 2021 Ziwei Fan, Zhiwei Liu, Lei Zheng, Shen Wang, Philip S. Yu

We use Elliptical Gaussian distributions to describe items and sequences with uncertainty.

Safe Learning-based Gradient-free Model Predictive Control Based on Cross-entropy Method

no code implementations24 Feb 2021 Lei Zheng, Rui Yang, Zhixuan Wu, Jiesen Panb, Hui Cheng

In this paper, a safe and learning-based control framework for model predictive control (MPC) is proposed to optimize nonlinear systems with a gradient-free objective function under uncertain environmental disturbances.

Gaussian Processes Robotics

JSCN: Joint Spectral Convolutional Network for Cross Domain Recommendation

1 code implementation18 Oct 2019 Zhiwei Liu, Lei Zheng, Jiawei Zhang, Jiayu Han, Philip S. Yu

JSCN will simultaneously operate multi-layer spectral convolutions on different graphs, and jointly learn a domain-invariant user representation with a domain adaptive user mapping module.

Recommendation Systems

Deep Landscape Forecasting for Real-time Bidding Advertising

2 code implementations7 May 2019 Kan Ren, Jiarui Qin, Lei Zheng, Zhengyu Yang, Wei-Nan Zhang, Yong Yu

The problem is formulated as to forecast the probability distribution of market price for each ad auction.

Survival Analysis

Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction

1 code implementation2 May 2019 Kan Ren, Jiarui Qin, Yuchen Fang, Wei-Nan Zhang, Lei Zheng, Weijie Bian, Guorui Zhou, Jian Xu, Yong Yu, Xiaoqiang Zhu, Kun Gai

In order to tackle these challenges, in this paper, we propose a Hierarchical Periodic Memory Network for lifelong sequential modeling with personalized memorization of sequential patterns for each user.

Automated Multiscale 3D Feature Learning for Vessels Segmentation in Thorax CT Images

no code implementations6 Jan 2019 Tomasz Konopczyński, Thorben Kröger, Lei Zheng, Christoph S. Garbe, Jürgen Hesser

Following their idea of feature learning instead of hand-crafted filters, we have extended the method to learn 3D features.

Dictionary Learning

Instance Segmentation of Fibers from Low Resolution CT Scans via 3D Deep Embedding Learning

no code implementations4 Jan 2019 Tomasz Konopczyński, Thorben Kröger, Lei Zheng, Jürgen Hesser

We propose a novel approach for automatic extraction (instance segmentation) of fibers from low resolution 3D X-ray computed tomography scans of short glass fiber reinforced polymers.

3D Instance Segmentation Semantic Segmentation

Fully Convolutional Deep Network Architectures for Automatic Short Glass Fiber Semantic Segmentation from CT scans

no code implementations4 Jan 2019 Tomasz Konopczyński, Danish Rathore, Jitendra Rathore, Thorben Kröger, Lei Zheng, Christoph S. Garbe, Simone Carmignato, Jürgen Hesser

We present the first attempt to perform short glass fiber semantic segmentation from X-ray computed tomography volumetric datasets at medium (3. 9 {\mu}m isotropic) and low (8. 3 {\mu}m isotropic) resolution using deep learning architectures.

Semantic Segmentation

Semi-supervised Deep Representation Learning for Multi-View Problems

no code implementations11 Nov 2018 Vahid Noroozi, Sara Bahaadini, Lei Zheng, Sihong Xie, Weixiang Shao, Philip S. Yu

While neural networks for learning representation of multi-view data have been previously proposed as one of the state-of-the-art multi-view dimension reduction techniques, how to make the representation discriminative with only a small amount of labeled data is not well-studied.

Dimensionality Reduction Learning Representation Of Multi-View Data

Deep Recurrent Survival Analysis

1 code implementation7 Sep 2018 Kan Ren, Jiarui Qin, Lei Zheng, Zhengyu Yang, Wei-Nan Zhang, Lin Qiu, Yong Yu

By capturing the time dependency through modeling the conditional probability of the event for each sample, our method predicts the likelihood of the true event occurrence and estimates the survival rate over time, i. e., the probability of the non-occurrence of the event, for the censored data.

Survival Analysis

Spectral Collaborative Filtering

1 code implementation30 Aug 2018 Lei Zheng, Chun-Ta Lu, Fei Jiang, Jiawei Zhang, Philip S. Yu

Benefiting from the rich information of connectivity existing in the \textit{spectral domain}, SpectralCF is capable of discovering deep connections between users and items and therefore, alleviates the \textit{cold-start} problem for CF.

Recommendation Systems

TI-CNN: Convolutional Neural Networks for Fake News Detection

2 code implementations3 Jun 2018 Yang Yang, Lei Zheng, Jiawei Zhang, Qingcai Cui, Zhoujun Li, Philip S. Yu

By projecting the explicit and latent features into a unified feature space, TI-CNN is trained with both the text and image information simultaneously.

Fact Checking Fake News Detection

DeepMood: Modeling Mobile Phone Typing Dynamics for Mood Detection

no code implementations23 Mar 2018 Bokai Cao, Lei Zheng, Chenwei Zhang, Philip S. Yu, Andrea Piscitello, John Zulueta, Olu Ajilore, Kelly Ryan, Alex D. Leow

The increasing use of electronic forms of communication presents new opportunities in the study of mental health, including the ability to investigate the manifestations of psychiatric diseases unobtrusively and in the setting of patients' daily lives.

Texygen: A Benchmarking Platform for Text Generation Models

1 code implementation6 Feb 2018 Yaoming Zhu, Sidi Lu, Lei Zheng, Jiaxian Guo, Wei-Nan Zhang, Jun Wang, Yong Yu

We introduce Texygen, a benchmarking platform to support research on open-domain text generation models.

Text Generation

Joint Deep Modeling of Users and Items Using Reviews for Recommendation

5 code implementations17 Jan 2017 Lei Zheng, Vahid Noroozi, Philip S. Yu

One of the networks focuses on learning user behaviors exploiting reviews written by the user, and the other one learns item properties from the reviews written for the item.

Recommendation Systems

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