b'Ivor W. Tsang'

research

∙ 07/29/2022

A Survey of Learning on Small Data

Learning on big data brings success for artificial intelligence (AI), bu...

Xiaofeng Cao, et al. ∙

research

∙ 06/30/2022

When an Active Learner Meets a Black-box Teacher

Active learning maximizes the hypothesis updates to find those desired u...

Xiaofeng Cao, et al. ∙

research

∙ 06/30/2022

Data-Efficient Learning via Minimizing Hyperspherical Energy

Deep learning on large-scale data is dominant nowadays. The unprecedente...

Xiaofeng Cao, et al. ∙

research

∙ 06/08/2022

Latent Boundary-guided Adversarial Training

Deep Neural Networks (DNNs) have recently achieved great success in many...

Xiaowei Zhou, et al. ∙

research

∙ 05/23/2022

Neural Subgraph Explorer: Reducing Noisy Information via Target-Oriented Syntax Graph Pruning

Recent years have witnessed the emerging success of leveraging syntax gr...

Bowen Xing, et al. ∙

research

∙ 04/01/2022

Diverse Preference Augmentation with Multiple Domains for Cold-start Recommendations

Cold-start issues have been more and more challenging for providing accu...

Yan Zhang, et al. ∙

research

∙ 03/08/2022

DARER: Dual-task Temporal Relational Recurrent Reasoning Network for Joint Dialog Sentiment Classification and Act Recognition

The task of joint dialog sentiment classification (DSC) and act recognit...

Bowen Xing, et al. ∙

research

∙ 12/15/2021

Taming Overconfident Prediction on Unlabeled Data from Hindsight

Minimizing prediction uncertainty on unlabeled data is a key factor to a...

Jing Li, et al. ∙

research

∙ 11/26/2021

TRIP: Refining Image-to-Image Translation via Rival Preferences

Relative attribute (RA), referring to the preference over two images on ...

Yinghua Yao, et al. ∙

research

∙ 09/24/2021

Edge but not Least: Cross-View Graph Pooling

Graph neural networks have emerged as a powerful model for graph represe...

Xiaowei Zhou, et al. ∙

research

∙ 09/02/2021

A Multi-view Multi-task Learning Framework for Multi-variate Time Series Forecasting

Multi-variate time series (MTS) data is a ubiquitous class of data abstr...

Jinliang Deng, et al. ∙

research

∙ 08/05/2021

Understand me, if you refer to Aspect Knowledge: Knowledge-aware Gated Recurrent Memory Network

Aspect-level sentiment classification (ASC) aims to predict the fine-gra...

Bowen Xing, et al. ∙

research

∙ 07/14/2021

Differential-Critic GAN: Generating What You Want by a Cue of Preferences

This paper proposes Differential-Critic Generative Adversarial Network (...

Yinghua Yao, et al. ∙

research

∙ 07/02/2021

Online Multi-Agent Forecasting with Interpretable Collaborative Graph Neural Network

This paper considers predicting future statuses of multiple agents in an...

Maosen Li, et al. ∙

research

∙ 06/21/2021

Out of Context: A New Clue for Context Modeling of Aspect-based Sentiment Analysis

Aspect-based sentiment analysis (ABSA) aims to predict the sentiment exp...

Bowen Xing, et al. ∙

research

∙ 05/06/2021

Bayesian Active Learning by Disagreements: A Geometric Perspective

We present geometric Bayesian active learning by disagreements (GBALD), ...

Xiaofeng Cao, et al. ∙

research

∙ 11/23/2020

The Emerging Trends of Multi-Label Learning

Exabytes of data are generated daily by humans, leading to the growing n...

Weiwei Liu, et al. ∙

research

∙ 11/09/2020

A Survey of Label-noise Representation Learning: Past, Present and Future

Classical machine learning implicitly assumes that labels of the trainin...

Bo Han, et al. ∙

research

∙ 11/03/2020

Learning on Attribute-Missing Graphs

Graphs with complete node attributes have been widely explored recently....

Xu Chen, et al. ∙

research

∙ 11/02/2020

Collaborative Generative Hashing for Marketing and Fast Cold-start Recommendation

Cold-start has being a critical issue in recommender systems with the ex...

Yan Zhang, et al. ∙

research

∙ 11/02/2020

Deep Pairwise Hashing for Cold-start Recommendation

Recommendation efficiency and data sparsity problems have been regarded ...

Yan Zhang, et al. ∙

research

∙ 10/05/2020

Graph Cross Networks with Vertex Infomax Pooling

We propose a novel graph cross network (GXN) to achieve comprehensive fe...

Maosen Li, et al. ∙

research

∙ 06/26/2020

Intrinsic Reward Driven Imitation Learning via Generative Model

Imitation learning in a high-dimensional environment is challenging. Mos...

Xingrui Yu, et al. ∙

research

∙ 05/24/2020

Multi-view Alignment and Generation in CCA via Consistent Latent Encoding

Multi-view alignment, achieving one-to-one correspondence of multi-view ...

Yaxin Shi, et al. ∙

research

∙ 03/30/2020

Secure Metric Learning via Differential Pairwise Privacy

Distance Metric Learning (DML) has drawn much attention over the last tw...

Jing Li, et al. ∙

research

∙ 02/09/2020

Face Hallucination with Finishing Touches

Obtaining a high-quality frontal face image from a low-resolution (LR) n...

Yang Zhang, et al. ∙

research

∙ 02/01/2020

Towards Sharper First-Order Adversary with Quantized Gradients

Despite the huge success of Deep Neural Networks (DNNs) in a wide spectr...

Zhuanghua Liu, et al. ∙

research

∙ 10/09/2019

Stochastic Implicit Natural Gradient for Black-box Optimization

Black-box optimization is primarily important for many compute-intensive...

Yueming Lyu, et al. ∙

research

∙ 07/26/2019

Improving Generalization via Attribute Selection on Out-of-the-box Data

Zero-shot learning (ZSL) aims to recognize unseen objects (test classes)...

Xiaofeng Xu, et al. ∙

research

∙ 07/23/2019

Node Attribute Generation on Graphs

Graph structured data provide two-fold information: graph structures and...

Xu Chen, et al. ∙

research

∙ 07/16/2019

Latent Adversarial Defence with Boundary-guided Generation

Deep Neural Networks (DNNs) have recently achieved great success in many...

Xiaowei Zhou, et al. ∙

research

∙ 05/29/2019

Fast and Robust Rank Aggregation against Model Misspecification

In rank aggregation, preferences from different users are summarized int...

Yuangang Pan, et al. ∙

research

∙ 05/24/2019

Curriculum Loss: Robust Learning and Generalization against Label Corruption

Generalization is vital important for many deep network models. It becom...

Yueming Lyu, et al. ∙

research

∙ 05/24/2019

Efficient Batch Black-box Optimization with Deterministic Regret Bounds

In this work, we investigate black-box optimization from the perspective...

Yueming Lyu, et al. ∙

research

∙ 05/21/2019

Marginalized Average Attentional Network for Weakly-Supervised Learning

In weakly-supervised temporal action localization, previous works have f...

Yuan Yuan, et al. ∙

research

∙ 05/20/2019

Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation

As a kind of semantic representation of visual object descriptions, attr...

Xiaofeng Xu, et al. ∙

research

∙ 03/06/2019

Safeguarded Dynamic Label Regression for Generalized Noisy Supervision

Learning with noisy labels, which aims to reduce expensive labors on acc...

Jiangchao Yao, et al. ∙

research

∙ 01/14/2019

How Does Disagreement Benefit Co-teaching?

Learning with noisy labels is one of the most important question in weak...

Xingrui Yu, et al. ∙

research

∙ 01/02/2019

A Survey on Multi-output Learning

Multi-output learning aims to simultaneously predict multiple outputs gi...

Donna Xu, et al. ∙

research

∙ 09/30/2018

Privacy-preserving Stochastic Gradual Learning

It is challenging for stochastic optimizations to handle large-scale sen...

Bo Han, et al. ∙

research

∙ 09/28/2018

Target-Independent Active Learning via Distribution-Splitting

To reduce the label complexity in Agnostic Active Learning (A^2 algorith...

Xiaofeng Cao, et al. ∙

research

∙ 07/24/2018

A Structured Perspective of Volumes on Active Learning

Active Learning (AL) is a learning task that requires learners interacti...

Xiaofeng Cao, et al. ∙

research

∙ 07/10/2018

Understanding VAEs in Fisher-Shannon Plane

In information theory, Fisher information and Shannon information (entro...

Huangjie Zheng, et al. ∙

research

∙ 05/31/2018

Geometric Active Learning via Enclosing Ball Boundary

Active Learning (AL) requires learners to retrain the classifier with th...

Xiaofeng Cao, et al. ∙

research

∙ 05/23/2018

Matrix Co-completion for Multi-label Classification with Missing Features and Labels

We consider a challenging multi-label classification problem where both ...

Miao Xu, et al. ∙

research

∙ 05/03/2018

Multi-Context Label Embedding

Label embedding plays an important role in zero-shot learning. Side info...

Yaxin Shi, et al. ∙

research

∙ 04/17/2018

Zero-shot Learning with Complementary Attributes

Zero-shot learning (ZSL) aims to recognize unseen objects using disjoint...

Xiaofeng Xu, et al. ∙

research

∙ 02/26/2018

VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning

In this paper, we propose a simple variant of the original SVRG, called ...

Fanhua Shang, et al. ∙

research

∙ 02/26/2018

Millionaire: A Hint-guided Approach for Crowdsourcing

Modern machine learning is migrating to the era of complex models, which...

Bo Han, et al. ∙

research

∙ 02/19/2018

Degeneration in VAE: in the Light of Fisher Information Loss

Variational Autoencoder (VAE) is one of the most popular generative mode...

Huangjie Zheng, et al. ∙

Ivor W. Tsang

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