Search Results for author: Hongfu Liu

Found 34 papers, 11 papers with code

Advancing Test-Time Adaptation for Acoustic Foundation Models in Open-World Shifts

no code implementations14 Oct 2023 Hongfu Liu, Hengguan Huang, Ye Wang

However, while acoustic models face similar challenges due to distribution shifts in test-time speech, TTA techniques specifically designed for acoustic modeling in the context of open-world data shifts remain scarce.


Towards Informative Few-Shot Prompt with Maximum Information Gain for In-Context Learning

no code implementations13 Oct 2023 Hongfu Liu, Ye Wang

Large Language models (LLMs) possess the capability to engage In-context Learning (ICL) by leveraging a few demonstrations pertaining to a new downstream task as conditions.

Dual Node and Edge Fairness-Aware Graph Partition

no code implementations16 Jun 2023 TingWei Liu, Peizhao Li, Hongfu Liu

To address this gap, we propose a notion edge balance to measure the proportion of edges connecting different demographic groups in clusters.

Fairness Link Prediction +1

Visualizing Transferred Knowledge: An Interpretive Model of Unsupervised Domain Adaptation

1 code implementation4 Mar 2023 Wenxiao Xiao, Zhengming Ding, Hongfu Liu

Many research efforts have been committed to unsupervised domain adaptation (DA) problems that transfer knowledge learned from a labeled source domain to an unlabeled target domain.

Unsupervised Domain Adaptation

Zero-Knowledge Zero-Shot Learning for Novel Visual Category Discovery

no code implementations9 Feb 2023 Zhaonan Li, Hongfu Liu

Generalized Zero-Shot Learning (GZSL) and Open-Set Recognition (OSR) are two mainstream settings that greatly extend conventional visual object recognition.

Generalized Zero-Shot Learning Object Recognition +1

Learning Antidote Data to Individual Unfairness

no code implementations29 Nov 2022 Peizhao Li, Ethan Xia, Hongfu Liu

Fairness is essential for machine learning systems deployed in high-stake applications.


Characterizing the Influence of Graph Elements

no code implementations14 Oct 2022 Zizhang Chen, Peizhao Li, Hongfu Liu, Pengyu Hong

To fill this gap, we started with the simple graph convolution (SGC) model that operates on an attributed graph and formulated an influence function to approximate the changes in model parameters when a node or an edge is removed from an attributed graph.

Robust Fair Clustering: A Novel Fairness Attack and Defense Framework

1 code implementation4 Oct 2022 Anshuman Chhabra, Peizhao Li, Prasant Mohapatra, Hongfu Liu

Experimentally, we observe that CFC is highly robust to the proposed attack and is thus a truly robust fair clustering alternative.

Adversarial Attack Clustering +2

Contrastive Graph Few-Shot Learning

no code implementations30 Sep 2022 Chunhui Zhang, Hongfu Liu, Jundong Li, Yanfang Ye, Chuxu Zhang

Later, the trained encoder is frozen as a teacher model to distill a student model with a contrastive loss.

Contrastive Learning Few-Shot Learning +2

Multi-task Envisioning Transformer-based Autoencoder for Corporate Credit Rating Migration Early Prediction

no code implementations10 Jul 2022 Han Yue, Steve Xia, Hongfu Liu

META consists of Positional Encoding, Transformer-based Autoencoder, and Multi-task Prediction to learn effective representations for both migration prediction and rating prediction.

Decision Making

Learnable Visual Words for Interpretable Image Recognition

1 code implementation22 May 2022 Wenxiao Xiao, Zhengming Ding, Hongfu Liu

In this paper, we revisit the concept of visual words and propose the Learnable Visual Words (LVW) to interpret the model prediction behaviors with two novel modules: semantic visual words learning and dual fidelity preservation.

Label-invariant Augmentation for Semi-Supervised Graph Classification

no code implementations19 May 2022 Han Yue, Chunhui Zhang, Chuxu Zhang, Hongfu Liu

Recently, contrastiveness-based augmentation surges a new climax in the computer vision domain, where some operations, including rotation, crop, and flip, combined with dedicated algorithms, dramatically increase the model generalization and robustness.

Contrastive Learning Graph Classification

Achieving Fairness at No Utility Cost via Data Reweighing with Influence

1 code implementation1 Feb 2022 Peizhao Li, Hongfu Liu

With the fast development of algorithmic governance, fairness has become a compulsory property for machine learning models to suppress unintentional discrimination.

BIG-bench Machine Learning Fairness

Implicit Semantic Response Alignment for Partial Domain Adaptation

1 code implementation NeurIPS 2021 Wenxiao Xiao, Zhengming Ding, Hongfu Liu

Partial Domain Adaptation (PDA) addresses the unsupervised domain adaptation problem where the target label space is a subset of the source label space.

Partial Domain Adaptation Unsupervised Domain Adaptation

Code Editing from Few Exemplars by Adaptive Multi-Extent Composition

no code implementations29 Sep 2021 Peizhao Li, Xuchao Zhang, Ziyu Yao, Wei Cheng, Haifeng Chen, Hongfu Liu

To achieve this, we propose a machine learning approach to adapt the editorial style derived from few exemplars to a query code snippet.

Second-Order Unsupervised Feature Selection via Knowledge Contrastive Distillation

no code implementations29 Sep 2021 Han Yue, Jundong Li, Hongfu Liu

Unsupervised feature selection aims to select a subset from the original features that are most useful for the downstream tasks without external guidance information.

feature selection

IPOF: An Extremely and Excitingly Simple Outlier Detection Booster via Infinite Propagation

no code implementations1 Aug 2021 Sibo Zhu, Handong Zhao, Hongfu Liu

By employing score-based outlier detectors for initialization, iPOF updates each data point's outlier score by averaging the outlier factors of its nearest common neighbors.

Outlier Detection

Economic Recession Prediction Using Deep Neural Network

no code implementations21 Jul 2021 ZiHao Wang, Kun Li, Steve Q. Xia, Hongfu Liu

We investigate the effectiveness of different machine learning methodologies in predicting economic cycles.

BIG-bench Machine Learning

STRODE: Stochastic Boundary Ordinary Differential Equation

1 code implementation17 Jul 2021 Hengguan Huang, Hongfu Liu, Hao Wang, Chang Xiao, Ye Wang

In this paper, we present a probabilistic ordinary differential equation (ODE), called STochastic boundaRy ODE (STRODE), that learns both the timings and the dynamics of time series data without requiring any timing annotations during training.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +4

Deep Clustering based Fair Outlier Detection

1 code implementation9 Jun 2021 Hanyu Song, Peizhao Li, Hongfu Liu

In this paper, we focus on the fairness issues regarding unsupervised outlier detection.

Clustering Deep Clustering +3

SelfDoc: Self-Supervised Document Representation Learning

no code implementations CVPR 2021 Peizhao Li, Jiuxiang Gu, Jason Kuen, Vlad I. Morariu, Handong Zhao, Rajiv Jain, Varun Manjunatha, Hongfu Liu

For downstream usage, we propose a novel modality-adaptive attention mechanism for multimodal feature fusion by adaptively emphasizing language and vision signals.

Representation Learning

Fairness-Aware Unsupervised Feature Selection

no code implementations4 Jun 2021 Xiaoying Xing, Hongfu Liu, Chen Chen, Jundong Li

Feature selection is a prevalent data preprocessing paradigm for various learning tasks.

Fairness feature selection

Towards Novel Target Discovery Through Open-Set Domain Adaptation

1 code implementation ICCV 2021 Taotao Jing, Hongfu Liu, Zhengming Ding

In this paper, we propose a novel framework to accurately identify the seen categories in target domain, and effectively recover the semantic attributes for unseen categories.

Domain Adaptation Open Set Learning

Graph-Graph Similarity Network

no code implementations1 Jan 2021 Han Yue, Pengyu Hong, Hongfu Liu

In this paper, we propose a Graph-Graph Similarity Network to tackle the graph classification problem by constructing a SuperGraph through learning the relationships among graphs.

General Classification Graph Classification +2

Mining Label Distribution Drift in Unsupervised Domain Adaptation

no code implementations16 Jun 2020 Peizhao Li, Zhengming Ding, Hongfu Liu

Unsupervised domain adaptation targets to transfer task-related knowledge from labeled source domain to unlabeled target domain.

Unsupervised Domain Adaptation

Learnable Subspace Clustering

1 code implementation9 Apr 2020 Jun Li, Hongfu Liu, Zhiqiang Tao, Handong Zhao, Yun Fu

This paper studies the large-scale subspace clustering (LSSC) problem with million data points.


Consensus Clustering: An Embedding Perspective, Extension and Beyond

no code implementations31 May 2019 Hongfu Liu, Zhiqiang Tao, Zhengming Ding

Consensus clustering fuses diverse basic partitions (i. e., clustering results obtained from conventional clustering methods) into an integrated one, which has attracted increasing attention in both academic and industrial areas due to its robust and effective performance.

Constrained Clustering Domain Adaptation +3

Predictive Local Smoothness for Stochastic Gradient Methods

no code implementations ICLR 2019 Jun Li, Hongfu Liu, Bineng Zhong, Yue Wu, Yun Fu

To address this problem, we propose a simple yet effective method for improving stochastic gradient methods named predictive local smoothness (PLS).

Clustering with Outlier Removal

no code implementations5 Jan 2018 Hongfu Liu, Jun Li, Yue Wu, Yun Fu

Then an objective function based Holoentropy is designed to enhance the compactness of each cluster with a few outliers removed.

Clustering Outlier Detection

Cannot find the paper you are looking for? You can Submit a new open access paper.