Search Results for author: Chong Liu

Found 20 papers, 9 papers with code

Learning from All Sides: Diversified Positive Augmentation via Self-distillation in Recommendation

no code implementations15 Aug 2023 Chong Liu, Xiaoyang Liu, Ruobing Xie, Lixin Zhang, Feng Xia, Leyu Lin

A powerful positive item augmentation is beneficial to address the sparsity issue, while few works could jointly consider both the accuracy and diversity of these augmented training labels.

Recommendation Systems Retrieval

Graph Convolution Based Efficient Re-Ranking for Visual Retrieval

1 code implementation15 Jun 2023 Yuqi Zhang, Qi Qian, Hongsong Wang, Chong Liu, Weihua Chen, Fan Wang

In particular, the plain GCR is extended for cross-camera retrieval and an improved feature propagation formulation is presented to leverage affinity relationships across different cameras.

Distributed Computing Image Retrieval +3

Efficient Token-Guided Image-Text Retrieval with Consistent Multimodal Contrastive Training

1 code implementation15 Jun 2023 Chong Liu, Yuqi Zhang, Hongsong Wang, Weihua Chen, Fan Wang, Yan Huang, Yi-Dong Shen, Liang Wang

Most previous works either simply learn coarse-grained representations of the overall image and text, or elaborately establish the correspondence between image regions or pixels and text words.

Representation Learning Retrieval +1

An Approximation Theory for Metric Space-Valued Functions With A View Towards Deep Learning

no code implementations24 Apr 2023 Anastasis Kratsios, Chong Liu, Matti Lassas, Maarten V. de Hoop, Ivan Dokmanić

Motivated by the developing mathematics of deep learning, we build universal functions approximators of continuous maps between arbitrary Polish metric spaces $\mathcal{X}$ and $\mathcal{Y}$ using elementary functions between Euclidean spaces as building blocks.

No-Regret Linear Bandits beyond Realizability

no code implementations26 Feb 2023 Chong Liu, Ming Yin, Yu-Xiang Wang

It achieves a near-optimal $\sqrt{T}$ regret for problems that the best-known regret is almost linear in time horizon $T$.

Dialogue State Distillation Network with Inter-slot Contrastive Learning for Dialogue State Tracking

no code implementations16 Feb 2023 Jing Xu, Dandan song, Chong Liu, Siu Cheung Hui, Fei Li, Qiang Ju, Xiaonan He, Jian Xie

In this paper, we propose a Dialogue State Distillation Network (DSDN) to utilize relevant information of previous dialogue states and migrate the gap of utilization between training and testing.

Contrastive Learning Dialogue State Tracking +1

Summative Student Course Review Tool Based on Machine Learning Sentiment Analysis to Enhance Life Science Feedback Efficacy

no code implementations15 Jan 2023 Ben Hoar, Roshini Ramachandran, Marc Levis, Erin Sparck, Ke wu, Chong Liu

Often, student opinions are gathered with a general comment section that solicits their feelings towards their courses without polling specifics about course contents.

Sentiment Analysis

Global Optimization with Parametric Function Approximation

no code implementations16 Nov 2022 Chong Liu, Yu-Xiang Wang

We consider the problem of global optimization with noisy zeroth order oracles - a well-motivated problem useful for various applications ranging from hyper-parameter tuning for deep learning to new material design.

Bayesian Optimization Gaussian Processes

UFNRec: Utilizing False Negative Samples for Sequential Recommendation

1 code implementation8 Aug 2022 Xiaoyang Liu, Chong Liu, Pinzheng Wang, Rongqin Zheng, Lixin Zhang, Leyu Lin, Zhijun Chen, Liangliang Fu

To this end, we propose a novel method that can Utilize False Negative samples for sequential Recommendation (UFNRec) to improve model performance.

Sequential Recommendation

CT4Rec: Simple yet Effective Consistency Training for Sequential Recommendation

2 code implementations13 Dec 2021 Chong Liu, Xiaoyang Liu, Rongqin Zheng, Lixin Zhang, Xiaobo Liang, Juntao Li, Lijun Wu, Min Zhang, Leyu Lin

State-of-the-art sequential recommendation models proposed very recently combine contrastive learning techniques for obtaining high-quality user representations.

Click-Through Rate Prediction Contrastive Learning +2

Graph Convolution for Re-ranking in Person Re-identification

1 code implementation5 Jul 2021 Yuqi Zhang, Qian Qi, Chong Liu, Weihua Chen, Fan Wang, Hao Li, Rong Jin

In this work, we propose a graph-based re-ranking method to improve learned features while still keeping Euclidean distance as the similarity metric.

Person Re-Identification Re-Ranking +1

An Empirical Study of Vehicle Re-Identification on the AI City Challenge

1 code implementation20 May 2021 Hao Luo, Weihua Chen, Xianzhe Xu, Jianyang Gu, Yuqi Zhang, Chong Liu, Yiqi Jiang, Shuting He, Fan Wang, Hao Li

We mainly focus on four points, i. e. training data, unsupervised domain-adaptive (UDA) training, post-processing, model ensembling in this challenge.

Re-Ranking Retrieval +1

City-Scale Multi-Camera Vehicle Tracking Guided by Crossroad Zones

1 code implementation14 May 2021 Chong Liu, Yuqi Zhang, Hao Luo, Jiasheng Tang, Weihua Chen, Xianzhe Xu, Fan Wang, Hao Li, Yi-Dong Shen

Multi-Target Multi-Camera Tracking has a wide range of applications and is the basis for many advanced inferences and predictions.

Clustering Vehicle Re-Identification

Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning

no code implementations6 Nov 2020 Chong Liu, Yuqing Zhu, Kamalika Chaudhuri, Yu-Xiang Wang

The Private Aggregation of Teacher Ensembles (PATE) framework is one of the most promising recent approaches in differentially private learning.

Active Learning Majority Voting Classifier

Reconstruction Regularized Deep Metric Learning for Multi-label Image Classification

no code implementations27 Jul 2020 Changsheng Li, Chong Liu, Lixin Duan, Peng Gao, Kai Zheng

In this paper, we present a novel deep metric learning method to tackle the multi-label image classification problem.

General Classification Metric Learning +1

Unity Style Transfer for Person Re-Identification

no code implementations CVPR 2020 Chong Liu, Xiaojun Chang, Yi-Dong Shen

To solve this problem, we propose a UnityStyle adaption method, which can smooth the style disparities within the same camera and across different cameras.

Person Re-Identification Style Transfer +1

Supermartingale deflators in the absence of a numéraire

no code implementations16 Jan 2020 Philipp Harms, Chong Liu, Ariel Neufeld

In this paper we study arbitrage theory of financial markets in the absence of a num\'eraire both in discrete and continuous time.

Doubly Robust Crowdsourcing

no code implementations8 Jun 2019 Chong Liu, Yu-Xiang Wang

Large-scale labeled dataset is the indispensable fuel that ignites the AI revolution as we see today.

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