b'Kun Zhang'

research

∙ 06/08/2022

What-Is and How-To for Fairness in Machine Learning: A Survey, Reflection, and Perspective

Algorithmic fairness has attracted increasing attention in the machine l...

Zeyu Tang, et al. ∙

research

∙ 06/03/2022

Offline Reinforcement Learning with Causal Structured World Models

Model-based methods have recently shown promising for offline reinforcem...

Zheng-Mao Zhu, et al. ∙

research

∙ 05/27/2022

Counterfactual Fairness with Partially Known Causal Graph

Fair machine learning aims to avoid treating individuals or sub-populati...

Aoqi Zuo, et al. ∙

research

∙ 05/27/2022

MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models

State-of-the-art causal discovery methods usually assume that the observ...

Erdun Gao, et al. ∙

research

∙ 05/19/2022

Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems

Calibration is defined as the ratio of the average predicted click rate ...

Yewen Fan, et al. ∙

research

∙ 05/18/2022

Graph Adaptive Semantic Transfer for Cross-domain Sentiment Classification

Cross-domain sentiment classification (CDSC) aims to use the transferabl...

Kai Zhang, et al. ∙

research

∙ 04/26/2022

A Review-aware Graph Contrastive Learning Framework for Recommendation

Most modern recommender systems predict users preferences with two compo...

Jie Shuai, et al. ∙

research

∙ 03/30/2022

Factored Adaptation for Non-Stationary Reinforcement Learning

Dealing with non-stationarity in environments (i.e., transition dynamics...

Fan Feng, et al. ∙

research

∙ 03/30/2022

Incorporating Dynamic Semantics into Pre-Trained Language Model for Aspect-based Sentiment Analysis

Aspect-based sentiment analysis (ABSA) predicts sentiment polarity towar...

Kai Zhang, et al. ∙

research

∙ 03/29/2022

Sample Recycling for Nested Simulation with Application in Portfolio Risk Measurement

Nested simulation is a natural approach to tackle nested estimation prob...

Kun Zhang, et al. ∙

research

∙ 02/24/2022

Attainability and Optimality: The Equalized Odds Fairness Revisited

Fairness of machine learning algorithms has been of increasing interest....

Zeyu Tang, et al. ∙

research

∙ 02/11/2022

Conditional Contrastive Learning with Kernel

Conditional contrastive learning frameworks consider the conditional sam...

Yao-Hung Hubert Tsai, et al. ∙

research

∙ 02/10/2022

Learning Latent Causal Dynamics

One critical challenge of time-series modeling is how to learn and quick...

Weiran Yao, et al. ∙

research

∙ 01/14/2022

Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions

Many of the causal discovery methods rely on the faithfulness assumption...

Ignavier Ng, et al. ∙

research

∙ 12/26/2021

Perlin Noise Improve Adversarial Robustness

Adversarial examples are some special input that can perturb the output ...

Chengjun Tang, et al. ∙

research

∙ 12/13/2021

GLaM: Efficient Scaling of Language Models with Mixture-of-Experts

Scaling language models with more data, compute and parameters has drive...

Nan Du, et al. ∙

research

∙ 11/05/2021

Transferable Time-Series Forecasting under Causal Conditional Shift

This paper focuses on the problem of semi-supervised domain adaptation f...

Zijian Li, et al. ∙

research

∙ 10/18/2021

Towards Federated Bayesian Network Structure Learning with Continuous Optimization

Traditionally, Bayesian network structure learning is often carried out ...

Ignavier Ng, et al. ∙

research

∙ 10/12/2021

Action-Sufficient State Representation Learning for Control with Structural Constraints

Perceived signals in real-world scenarios are usually high-dimensional a...

Biwei Huang, et al. ∙

research

∙ 10/11/2021

Learning Temporally Causal Latent Processes from General Temporal Data

Our goal is to recover time-delayed latent causal variables and identify...

Weiran Yao, et al. ∙

research

∙ 09/24/2021

Unaligned Image-to-Image Translation by Learning to Reweight

Unsupervised image-to-image translation aims at learning the mapping fro...

Shaoan Xie, et al. ∙

research

∙ 09/10/2021

A Fast PC Algorithm with Reversed-order Pruning and A Parallelization Strategy

The PC algorithm is the state-of-the-art algorithm for causal structure ...

Kai Zhang, et al. ∙

research

∙ 09/07/2021

Instance-dependent Label-noise Learning under a Structural Causal Model

Label noise will degenerate the performance of deep learning algorithms ...

Yu Yao, et al. ∙

research

∙ 08/27/2021

DAE-GAN: Dynamic Aspect-aware GAN for Text-to-Image Synthesis

Text-to-image synthesis refers to generating an image from a given text ...

Shulan Ruan, et al. ∙

research

∙ 08/24/2021

Outdoor Position Recovery from HeterogeneousTelco Cellular Data

Recent years have witnessed unprecedented amounts of data generated by t...

Yige Zhang, et al. ∙

research

∙ 08/06/2021

LadRa-Net: Locally-Aware Dynamic Re-read Attention Net for Sentence Semantic Matching

Sentence semantic matching requires an agent to determine the semantic r...

Kun Zhang, et al. ∙

research

∙ 07/15/2021

Multi-Channel Auto-Encoders and a Novel Dataset for Learning Domain Invariant Representations of Histopathology Images

Domain shift is a problem commonly encountered when developing automated...

Andrew Moyes, et al. ∙

research

∙ 07/06/2021

AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning

Most approaches in reinforcement learning (RL) are data-hungry and speci...

Biwei Huang, et al. ∙

research

∙ 06/23/2021

Region-Aware Network: Model Human's Top-Down Visual Perception Mechanism for Crowd Counting

Background noise and scale variation are common problems that have been ...

Yuehai Chen, et al. ∙

research

∙ 06/14/2021

Graph Domain Adaptation: A Generative View

Recent years have witnessed tremendous interest in deep learning on grap...

Ruichu Cai, et al. ∙

research

∙ 06/11/2021

Adversarial Robustness through the Lens of Causality

The adversarial vulnerability of deep neural networks has attracted sign...

Yonggang Zhang, et al. ∙

research

∙ 06/09/2021

DGA-Net Dynamic Gaussian Attention Network for Sentence Semantic Matching

Sentence semantic matching requires an agent to determine the semantic r...

Kun Zhang, et al. ∙

research

∙ 06/05/2021

Conditional Contrastive Learning: Removing Undesirable Information in Self-Supervised Representations

Self-supervised learning is a form of unsupervised learning that leverag...

Yao-Hung Hubert Tsai, et al. ∙

research

∙ 06/01/2021

Graph-based Exercise- and Knowledge-Aware Learning Network for Student Performance Prediction

Predicting student performance is a fundamental task in Intelligent Tuto...

Mengfan Liu, et al. ∙

research

∙ 05/31/2021

Privileged Graph Distillation for Cold Start Recommendation

The cold start problem in recommender systems is a long-standing challen...

Shuai Wang, et al. ∙

research

∙ 05/19/2021

Learning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate Prediction

Click-through rate (CTR) prediction is one of the most central tasks in ...

Wentao Ouyang, et al. ∙

research

∙ 05/16/2021

Set2setRank: Collaborative Set to Set Ranking for Implicit Feedback based Recommendation

As users often express their preferences with binary behavior data (impl...

Lei Chen, et al. ∙

research

∙ 04/27/2021

A Survey on Neural Recommendation: From Collaborative Filtering to Content and Context Enriched Recommendation

Influenced by the stunning success of deep learning in computer vision a...

Le Wu, et al. ∙

research

∙ 03/26/2021

FRITL: A Hybrid Method for Causal Discovery in the Presence of Latent Confounders

We consider the problem of estimating a particular type of linear non-Ga...

Wei Chen, et al. ∙

research

∙ 02/28/2021

RIS-Aided Wireless Communications: Prototyping, Adaptive Beamforming, and Indoor/Outdoor Field Trials

The prospects of using a Reconfigurable Intelligent Surface (RIS) to aid...

Xilong Pei, et al. ∙

research

∙ 01/20/2021

Ensemble manifold based regularized multi-modal graph convolutional network for cognitive ability prediction

Objective: Multi-modal functional magnetic resonance imaging (fMRI) can ...

Gang Qu, et al. ∙

research

∙ 12/22/2020

Learning Disentangled Semantic Representation for Domain Adaptation

Domain adaptation is an important but challenging task. Most of the exis...

Ruichu Cai, et al. ∙

research

∙ 12/16/2020

Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation

Reinforcement learning (RL) algorithms usually require a substantial amo...

Chaochao Lu, et al. ∙

research

∙ 12/16/2020

R^2-Net: Relation of Relation Learning Network for Sentence Semantic Matching

Sentence semantic matching is one of the fundamental tasks in natural la...

Kun Zhang, et al. ∙

research

∙ 12/13/2020

Learning Heatmap-Style Jigsaw Puzzles Provides Good Pretraining for 2D Human Pose Estimation

The target of 2D human pose estimation is to locate the keypoints of bod...

Kun Zhang, et al. ∙

research

∙ 10/21/2020

How Do Fair Decisions Fare in Long-term Qualification?

Although many fairness criteria have been proposed for decision making, ...

Xueru Zhang, et al. ∙

research

∙ 10/10/2020

Generalized Independent Noise Condition for Estimating Linear Non-Gaussian Latent Variable Graphs

Causal discovery aims to recover causal structures or models underlying ...

Feng Xie, et al. ∙

research

∙ 08/16/2020

Attack on Multi-Node Attention for Object Detection

This paper focuses on high-transferable adversarial attacks on detection...

Sizhe Chen, et al. ∙

research

∙ 07/17/2020

Adaptive Task Sampling for Meta-Learning

Meta-learning methods have been extensively studied and applied in compu...

Chenghao Liu, et al. ∙

research

∙ 06/17/2020

On the Role of Sparsity and DAG Constraints for Learning Linear DAGs

Learning graphical structure based on Directed Acyclic Graphs (DAGs) is ...

Ignavier Ng, et al. ∙

Kun Zhang

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