Search Results for author: Liang Du

Found 20 papers, 3 papers with code

DELTA: Direct Embedding Enhancement and Leverage Truncated Conscious Attention for Recommendation System

no code implementations3 May 2023 Chen Zhu, Liang Du, Xin Wang, Wenwu Zhu

Click-Through Rate (CTR) prediction is the most critical task in product and content recommendation, and learning effective feature interaction is the key challenge to exploiting user preferences for products.

Click-Through Rate Prediction

MathPrompter: Mathematical Reasoning using Large Language Models

no code implementations4 Mar 2023 Shima Imani, Liang Du, Harsh Shrivastava

Large Language Models (LLMs) have limited performance when solving arithmetic reasoning tasks and often provide incorrect answers.

Arithmetic Reasoning Mathematical Reasoning +1

Rethinking Precision of Pseudo Label: Test-Time Adaptation via Complementary Learning

no code implementations15 Jan 2023 Jiayi Han, Longbin Zeng, Liang Du, Weiyang Ding, Jianfeng Feng

In this work, we propose a novel complementary learning approach to enhance test-time adaptation (TTA), which has been proven to exhibit good performance on testing data with distribution shifts such as corruptions.

Pseudo Label

Repainting and Imitating Learning for Lane Detection

no code implementations11 Oct 2022 Yue He, Minyue Jiang, Xiaoqing Ye, Liang Du, Zhikang Zou, Wei zhang, Xiao Tan, Errui Ding

In this paper, we target at finding an enhanced feature space where the lane features are distinctive while maintaining a similar distribution of lanes in the wild.

Lane Detection

SGM3D: Stereo Guided Monocular 3D Object Detection

1 code implementation3 Dec 2021 Zheyuan Zhou, Liang Du, Xiaoqing Ye, Zhikang Zou, Xiao Tan, Li Zhang, xiangyang xue, Jianfeng Feng

Monocular 3D object detection aims to predict the object location, dimension and orientation in 3D space alongside the object category given only a monocular image.

Autonomous Driving Depth Estimation +3

A Data-Driven Democratized Control Architecture for Regional Transmission Operators

no code implementations20 Sep 2021 Xiaoyuan Fan, Daniel Moscovitz, Liang Du, Walid Saad

As probably the most complicated and critical infrastructure system, U. S. power grids become increasingly vulnerable to extreme events such as cyber-attacks and severe weather, as well as higher DER penetrations and growing information mismatch among system operators, utilities (transmission or generation owners), and end-users.

Manifold Adaptive Multiple Kernel K-Means for Clustering

no code implementations30 Sep 2020 Liang Du, Haiying Zhang, Xin Ren, Xiaolin Lv

Multiple kernel methods based on k-means aims to integrate a group of kernels to improve the performance of kernel k-means clustering.

3DCFS: Fast and Robust Joint 3D Semantic-Instance Segmentation via Coupled Feature Selection

no code implementations1 Mar 2020 Liang Du, Jingang Tan, xiangyang xue, Lili Chen, Hongkai Wen, Jianfeng Feng, Jiamao Li, Xiaolin Zhang

We propose a novel fast and robust 3D point clouds segmentation framework via coupled feature selection, named 3DCFS, that jointly performs semantic and instance segmentation.

3D Semantic Instance Segmentation Semantic Segmentation

Visualization of Multi-Objective Switched Reluctance Machine Optimization at Multiple Operating Conditions with t-SNE

no code implementations4 Nov 2019 Shen Zhang, Shibo Zhang, Sufei Li, Liang Du, Thomas G. Habetler

However, the number of objectives that would need to be optimized would significantly increase with the number of operating points considered in the optimization, thus posting a potential problem in regards to the visualization techniques currently in use, such as in the scatter plots of Pareto fronts, the parallel coordinates, and in the principal component analysis (PCA), inhibiting their ability to provide machine designers with intuitive and informative visualizations of all of the design candidates and their ability to pick a few for further fine-tuning with performance verification.

SSF-DAN: Separated Semantic Feature Based Domain Adaptation Network for Semantic Segmentation

no code implementations ICCV 2019 Liang Du, Jingang Tan, Hongye Yang, Jianfeng Feng, Xiangyang Xue, Qibao Zheng, Xiaoqing Ye, Xiaolin Zhang

Despite the great success achieved by supervised fully convolutional models in semantic segmentation, training the models requires a large amount of labor-intensive work to generate pixel-level annotations.

Domain Adaptation Semantic Segmentation

Cross-Age Face Verification by Coordinating With Cross-Face Age Verification

no code implementations CVPR 2015 Liang Du, Haibin Ling

As shown in our experiments, the algorithm effectively balances feature sharing and feature exclusion between the two tasks; and, for face verification, the algorithm effectively removes distracting features used in age verification.

Face Verification MORPH

Unsupervised Feature Selection with Adaptive Structure Learning

1 code implementation3 Apr 2015 Liang Du, Yi-Dong Shen

Traditional unsupervised methods select the features which can faithfully preserve the intrinsic structures of data, where the intrinsic structures are estimated using all the input features of data.

Heterogeneous Metric Learning with Content-based Regularization for Software Artifact Retrieval

no code implementations25 Sep 2014 Liang Wu, Hui Xiong, Liang Du, Bo Liu, Guandong Xu, Yong Ge, Yanjie Fu, Yuanchun Zhou, Jianhui Li

Specifically, this method can capture both the inherent information in the source codes and the semantic information hidden in the comments, descriptions, and identifiers of the source codes.

Information Retrieval Metric Learning +1

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