Search Results for author: Qi Qi

Found 42 papers, 18 papers with code

Modeling Aspect Correlation for Aspect-based Sentiment Analysis via Recurrent Inverse Learning Guidance

no code implementations COLING 2022 Longfeng Li, Haifeng Sun, Qi Qi, Jingyu Wang, Jing Wang, Jianxin Liao

Second, we propose Inverse Learning Guidance to improve the selection of aspect feature by considering aspect correlation, which provides more useful information to determine polarity.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1

OutlierTune: Efficient Channel-Wise Quantization for Large Language Models

no code implementations27 Jun 2024 Jinguang Wang, Yuexi Yin, Haifeng Sun, Qi Qi, Jingyu Wang, Zirui Zhuang, Tingting Yang, Jianxin Liao

The pre-execution of dequantization updates the model weights by the activation scaling factors, avoiding the internal scaling and costly additional computational overheads brought by the per-channel activation quantization.

Quantization

Provable Optimization for Adversarial Fair Self-supervised Contrastive Learning

no code implementations9 Jun 2024 Qi Qi, Quanqi Hu, Qihang Lin, Tianbao Yang

Adversarial fair representation learning is well suited for this scenario by minimizing a contrastive loss over unlabeled data while maximizing an adversarial loss of predicting the sensitive attribute over the data with sensitive attribute.

Attribute Contrastive Learning +3

Single-loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions

no code implementations28 May 2024 Quanqi Hu, Qi Qi, Zhaosong Lu, Tianbao Yang

In this paper, we study a class of non-smooth non-convex problems in the form of $\min_{x}[\max_{y\in Y}\phi(x, y) - \max_{z\in Z}\psi(x, z)]$, where both $\Phi(x) = \max_{y\in Y}\phi(x, y)$ and $\Psi(x)=\max_{z\in Z}\psi(x, z)$ are weakly convex functions, and $\phi(x, y), \psi(x, z)$ are strongly concave functions in terms of $y$ and $z$, respectively.

Fairness

Underwater Image Enhancement by Diffusion Model with Customized CLIP-Classifier

1 code implementation25 May 2024 Shuaixin Liu, Kunqian Li, Yilin Ding, Qi Qi

Unlike other image enhancement tasks, underwater images suffer from the unavailability of real reference images.

Image Generation UIE

QCRD: Quality-guided Contrastive Rationale Distillation for Large Language Models

no code implementations14 May 2024 Wei Wang, Zhaowei Li, Qi Xu, Yiqing Cai, Hang Song, Qi Qi, Ran Zhou, Zhida Huang, Tao Wang, Li Xiao

For the learning of positive knowledge, we collect positive rationales through self-consistency to denoise the LLM rationales generated by temperature sampling.

Contrastive Learning Knowledge Distillation +1

FairSync: Ensuring Amortized Group Exposure in Distributed Recommendation Retrieval

1 code implementation16 Feb 2024 Chen Xu, Jun Xu, Yiming Ding, Xiao Zhang, Qi Qi

Specifically, FairSync resolves the issue by moving it to the dual space, where a central node aggregates historical fairness data into a vector and distributes it to all servers.

Distributed Optimization Fairness +2

Understanding and Guiding Weakly Supervised Entity Alignment with Potential Isomorphism Propagation

1 code implementation5 Feb 2024 Yuanyi Wang, Wei Tang, Haifeng Sun, Zirui Zhuang, Xiaoyuan Fu, Jingyu Wang, Qi Qi, Jianxin Liao

In this paper, we present a propagation perspective to analyze weakly supervised EA and explain the existing aggregation-based EA models.

Entity Alignment Knowledge Graphs

Towards Semantic Consistency: Dirichlet Energy Driven Robust Multi-Modal Entity Alignment

1 code implementation31 Jan 2024 Yuanyi Wang, Haifeng Sun, Jiabo Wang, Jingyu Wang, Wei Tang, Qi Qi, Shaoling Sun, Jianxin Liao

This study introduces a novel approach, DESAlign, which addresses these issues by applying a theoretical framework based on Dirichlet energy to ensure semantic consistency.

Attribute Graph Learning +3

Gradient Flow of Energy: A General and Efficient Approach for Entity Alignment Decoding

1 code implementation23 Jan 2024 Yuanyi Wang, Haifeng Sun, Jingyu Wang, Qi Qi, Shaoling Sun, Jianxin Liao

However, the decoding process in EA - essential for effective operation and alignment accuracy - has received limited attention and remains tailored to specific datasets and model architectures, necessitating both entity and additional explicit relation embeddings.

Entity Alignment Entity Embeddings +4

GroundingGPT:Language Enhanced Multi-modal Grounding Model

2 code implementations11 Jan 2024 Zhaowei Li, Qi Xu, Dong Zhang, Hang Song, Yiqing Cai, Qi Qi, Ran Zhou, Junting Pan, Zefeng Li, Van Tu Vu, Zhida Huang, Tao Wang

Beyond capturing global information like other multi-modal models, our proposed model excels at tasks demanding a detailed understanding of local information within the input.

Language Modelling Large Language Model

Multi-Scale Video Anomaly Detection by Multi-Grained Spatio-Temporal Representation Learning

no code implementations CVPR 2024 Menghao Zhang, Jingyu Wang, Qi Qi, Haifeng Sun, Zirui Zhuang, Pengfei Ren, Ruilong Ma, Jianxin Liao

ecent progress in video anomaly detection suggests that the features of appearance and motion play crucial roles in distinguishing abnormal patterns from normal ones.

Anomaly Detection Contrastive Learning +2

Adaptive DNN Surgery for Selfish Inference Acceleration with On-demand Edge Resource

no code implementations21 Jun 2023 Xiang Yang, Dezhi Chen, Qi Qi, Jingyu Wang, Haifeng Sun, Jianxin Liao, Song Guo

Deep Neural Networks (DNNs) have significantly improved the accuracy of intelligent applications on mobile devices.

Edge-computing

Improving Identity-Robustness for Face Models

no code implementations7 Apr 2023 Qi Qi, Shervin Ardeshir

When it comes to models directly trained on human faces, a sensitive confounder is that of human identities.

Face Recognition

Decoupled Iterative Refinement Framework for Interacting Hands Reconstruction from a Single RGB Image

1 code implementation ICCV 2023 Pengfei Ren, Chao Wen, Xiaozheng Zheng, Zhou Xue, Haifeng Sun, Qi Qi, Jingyu Wang, Jianxin Liao

On the other hand, there are complex spatial relationship between interacting hands, which significantly increases the solution space of hand poses and increases the difficulty of network learning.

3D Hand Pose Estimation 3D Interacting Hand Pose Estimation

Fairness via Adversarial Attribute Neighbourhood Robust Learning

no code implementations12 Oct 2022 Qi Qi, Shervin Ardeshir, Yi Xu, Tianbao Yang

Improving fairness between privileged and less-privileged sensitive attribute groups (e. g, {race, gender}) has attracted lots of attention.

Attribute Fairness

Stochastic Constrained DRO with a Complexity Independent of Sample Size

no code implementations11 Oct 2022 Qi Qi, Jiameng Lyu, Kung sik Chan, Er Wei Bai, Tianbao Yang

Distributionally Robust Optimization (DRO), as a popular method to train robust models against distribution shift between training and test sets, has received tremendous attention in recent years.

Can Shuffling Video Benefit Temporal Bias Problem: A Novel Training Framework for Temporal Grounding

1 code implementation29 Jul 2022 Jiachang Hao, Haifeng Sun, Pengfei Ren, Jingyu Wang, Qi Qi, Jianxin Liao

Our framework introduces two auxiliary tasks, cross-modal matching and temporal order discrimination, to promote the grounding model training.

Language-Based Temporal Localization Sentence

SGUIE-Net: Semantic Attention Guided Underwater Image Enhancement with Multi-Scale Perception

no code implementations8 Jan 2022 Qi Qi, Kunqian Li, Haiyong Zheng, Xiang Gao, Guojia Hou, Kun Sun

In this paper, we propose a novel underwater image enhancement network, called SGUIE-Net, in which we introduce semantic information as high-level guidance across different images that share common semantic regions.

Image Enhancement

Mining Multi-View Information: A Strong Self-Supervised Framework for Depth-Based 3D Hand Pose and Mesh Estimation

1 code implementation CVPR 2022 Pengfei Ren, Haifeng Sun, Jiachang Hao, Jingyu Wang, Qi Qi, Jianxin Liao

However, these methods ignore the rich semantic information in each view and ignore the complex dependencies between different regions of different views.

3D Hand Pose Estimation

A Variational U-Net for Weather Forecasting

1 code implementation5 Nov 2021 Pak Hay Kwok, Qi Qi

Not only can discovering patterns and insights from atmospheric data enable more accurate weather predictions, but it may also provide valuable information to help tackle climate change.

Weather Forecasting

Attentional-Biased Stochastic Gradient Descent

1 code implementation13 Dec 2020 Qi Qi, Yi Xu, Rong Jin, Wotao Yin, Tianbao Yang

In this paper, we present a simple yet effective provable method (named ABSGD) for addressing the data imbalance or label noise problem in deep learning.

Classification General Classification +2

Traffic4cast 2020 -- Graph Ensemble Net and the Importance of Feature And Loss Function Design for Traffic Prediction

no code implementations3 Dec 2020 Qi Qi, Pak Hay Kwok

We also explored the use of Graph Neural Networks and introduced a novel ensemble GNN architecture which outperformed the GNN solution from last year.

Traffic Prediction

Advanced Graph and Sequence Neural Networks for Molecular Property Prediction and Drug Discovery

1 code implementation2 Dec 2020 Zhengyang Wang, Meng Liu, Youzhi Luo, Zhao Xu, Yaochen Xie, Limei Wang, Lei Cai, Qi Qi, Zhuoning Yuan, Tianbao Yang, Shuiwang Ji

Here we develop a suite of comprehensive machine learning methods and tools spanning different computational models, molecular representations, and loss functions for molecular property prediction and drug discovery.

BIG-bench Machine Learning Drug Discovery +2

Robust Unsupervised Video Anomaly Detection by Multi-Path Frame Prediction

no code implementations5 Nov 2020 Xuanzhao Wang, Zhengping Che, Bo Jiang, Ning Xiao, Ke Yang, Jian Tang, Jieping Ye, Jingyu Wang, Qi Qi

In this paper, we propose a novel and robust unsupervised video anomaly detection method by frame prediction with proper design which is more in line with the characteristics of surveillance videos.

Anomaly Detection Video Anomaly Detection

A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous Sampling

no code implementations NeurIPS 2020 Xiaotie Deng, Ron Lavi, Tao Lin, Qi Qi, Wenwei Wang, Xiang Yan

The Empirical Revenue Maximization (ERM) is one of the most important price learning algorithms in auction design: as the literature shows it can learn approximately optimal reserve prices for revenue-maximizing auctioneers in both repeated auctions and uniform-price auctions.

Variance-Reduced Off-Policy Memory-Efficient Policy Search

no code implementations14 Sep 2020 Daoming Lyu, Qi Qi, Mohammad Ghavamzadeh, Hengshuai Yao, Tianbao Yang, Bo Liu

To achieve variance-reduced off-policy-stable policy optimization, we propose an algorithm family that is memory-efficient, stochastically variance-reduced, and capable of learning from off-policy samples.

Reinforcement Learning (RL) Stochastic Optimization

AWR: Adaptive Weighting Regression for 3D Hand Pose Estimation

1 code implementation19 Jul 2020 Weiting Huang, Pengfei Ren, Jingyu Wang, Qi Qi, Haifeng Sun

In this paper, we propose an adaptive weighting regression (AWR) method to leverage the advantages of both detection-based and regression-based methods.

3D Hand Pose Estimation regression

Adversarial and Domain-Aware BERT for Cross-Domain Sentiment Analysis

no code implementations ACL 2020 Chunning Du, Haifeng Sun, Jingyu Wang, Qi Qi, Jianxin Liao

To tackle these problems, we design a post-training procedure, which contains the target domain masked language model task and a novel domain-distinguish pre-training task.

Language Modelling Sentiment Analysis +2

An Online Method for A Class of Distributionally Robust Optimization with Non-Convex Objectives

1 code implementation NeurIPS 2021 Qi Qi, Zhishuai Guo, Yi Xu, Rong Jin, Tianbao Yang

In this paper, we propose a practical online method for solving a class of distributionally robust optimization (DRO) with non-convex objectives, which has important applications in machine learning for improving the robustness of neural networks.

A Simple and Effective Framework for Pairwise Deep Metric Learning

1 code implementation ECCV 2020 Qi Qi, Yan Yan, Xiaoyu Wang, Tianbao Yang

To tackle this issue, we propose a simple and effective framework to sample pairs in a batch of data for updating the model.

Binary Classification Metric Learning

Capsule Network with Interactive Attention for Aspect-Level Sentiment Classification

no code implementations IJCNLP 2019 Chunning Du, Haifeng Sun, Jingyu Wang, Qi Qi, Jianxin Liao, Tong Xu, Ming Liu

Aspect-level sentiment classification is a crucial task for sentiment analysis, which aims to identify the sentiment polarities of specific targets in their context.

Classification General Classification +3

Investigating Capsule Network and Semantic Feature on Hyperplanes for Text Classification

no code implementations IJCNLP 2019 Chunning Du, Haifeng Sun, Jingyu Wang, Qi Qi, Jianxin Liao, Chun Wang, Bing Ma

It has been demonstrated that multiple senses of a word actually reside in linear superposition within the word embedding so that specific senses can be extracted from the original word embedding.

General Classification text-classification +1

OICSR: Out-In-Channel Sparsity Regularization for Compact Deep Neural Networks

1 code implementation CVPR 2019 Jiashi Li, Qi Qi, Jingyu Wang, Ce Ge, Yujian Li, Zhangzhang Yue, Haifeng Sun

Many channel pruning works utilize structured sparsity regularization to zero out all the weights in some channels and automatically obtain structure-sparse network in training stage.

Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence

no code implementations28 Nov 2018 Yi Xu, Qi Qi, Qihang Lin, Rong Jin, Tianbao Yang

In this paper, we propose new stochastic optimization algorithms and study their first-order convergence theories for solving a broad family of DC functions.

Stochastic Optimization

A Deep Tree-Structured Fusion Model for Single Image Deraining

no code implementations21 Nov 2018 Xueyang Fu, Qi Qi, Yue Huang, Xinghao Ding, Feng Wu, John Paisley

We propose a simple yet effective deep tree-structured fusion model based on feature aggregation for the deraining problem.

Single Image Deraining

Fewer is More: Image Segmentation Based Weakly Supervised Object Detection with Partial Aggregation

no code implementations BMVC 2018 Ce Ge, Jingyu Wang, Qi Qi, Haifeng Sun, Jianxin Liao

As most weakly supervised object detection methods are based on pre-generated proposals, they often show two false detections: (i) group multiple object instances with one bounding box, and (ii) focus on only parts rather than the whole objects.

Image Segmentation Object +3

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