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08/27/2023
Topological Augmentation for Class-Imbalanced Node Classification
Class imbalance is prevalent in real-world node classification tasks and...
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08/21/2023
Graph Neural Bandits
Contextual bandits algorithms aim to choose the optimal arm with the hig...
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07/10/2023
Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey
In graph machine learning, data collection, sharing, and analysis often ...
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06/10/2023
Optimizing the Collaboration Structure in Cross-Silo Federated Learning
In federated learning (FL), multiple clients collaborate to train machin...
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05/05/2023
Neural Exploitation and Exploration of Contextual Bandits
In this paper, we study utilizing neural networks for the exploitation a...
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02/11/2023
Fairness-aware Multi-view Clustering
In the era of big data, we are often facing the challenge of data hetero...
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12/15/2022
Non-IID Transfer Learning on Graphs
Transfer learning refers to the transfer of knowledge or information fro...
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10/07/2022
Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative
This paper targets at improving the generalizability of hypergraph neura...
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10/02/2022
Improved Algorithms for Neural Active Learning
We improve the theoretical and empirical performance of neural-network(N...
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08/27/2022
BOBA: Byzantine-Robust Federated Learning with Label Skewness
In federated learning, most existing techniques for robust aggregation a...
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08/21/2022
MentorGNN: Deriving Curriculum for Pre-Training GNNs
Graph pre-training strategies have been attracting a surge of attention ...
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07/05/2022
A Unified Meta-Learning Framework for Dynamic Transfer Learning
Transfer learning refers to the transfer of knowledge or information fro...
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06/30/2022
Privacy-preserving Graph Analytics: Secure Generation and Federated Learning
Directly motivated by security-related applications from the Homeland Se...
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06/19/2022
Fairness-aware Model-agnostic Positive and Unlabeled Learning
With the increasing application of machine learning in high-stake decisi...
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06/09/2022
Comprehensive Fair Meta-learned Recommender System
In recommender systems, one common challenge is the cold-start problem, ...
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06/08/2022
Neural Bandit with Arm Group Graph
Contextual bandits aim to identify among a set of arms the optimal one w...
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03/09/2022
DISCO: Comprehensive and Explainable Disinformation Detection
Disinformation refers to false information deliberately spread to influe...
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01/31/2022
Neural Collaborative Filtering Bandits via Meta Learning
Contextual multi-armed bandits provide powerful tools to solve the explo...
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01/15/2022
Training Fair Deep Neural Networks by Balancing Influence
Most fair machine learning methods either highly rely on the sensitive i...
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01/14/2022
Adaptive Transfer Learning for Plant Phenotyping
Plant phenotyping (Guo et al. 2021; Pieruschka et al. 2019) focuses on s...
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10/28/2021
From Intrinsic to Counterfactual: On the Explainability of Contextualized Recommender Systems
With the prevalence of deep learning based embedding approaches, recomme...
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10/26/2021
Tackling Oversmoothing of GNNs with Contrastive Learning
Graph neural networks (GNNs) integrate the comprehensive relation of gra...
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10/16/2021
Deep Active Learning by Leveraging Training Dynamics
Active learning theories and methods have been extensively studied in cl...
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10/07/2021
EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits
Contextual multi-armed bandits have been studied for decades and adapted...
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07/05/2021
DPPIN: A Biological Dataset of Dynamic Protein-Protein Interaction Networks
Nowadays, many network representation learning algorithms and downstream...
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06/06/2021
Multi-facet Contextual Bandits: A Neural Network Perspective
Contextual multi-armed bandit has shown to be an effective tool in recom...
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05/31/2021
Controllable Gradient Item Retrieval
In this paper, we identify and study an important problem of gradient it...
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05/19/2021
Heterogeneous Contrastive Learning
With the advent of big data across multiple high-impact applications, we...
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12/12/2020
GAN-based Recommendation with Positive-Unlabeled Sampling
Recommender systems are popular tools for information retrieval tasks on...
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09/18/2020
Robust Decentralized Learning for Neural Networks
In decentralized learning, data is distributed among local clients which...
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09/15/2020
A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning Processes
Many statistical learning models hold an assumption that the training da...
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07/14/2020
Generic Outlier Detection in Multi-Armed Bandit
In this paper, we study the problem of outlier arm detection in multi-ar...
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06/05/2020
Continuous Transfer Learning with Label-informed Distribution Alignment
Transfer learning has been successfully applied across many high-impact ...
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08/22/2019
Coalesced TLB to Exploit Diverse Contiguity of Memory Mapping
The miss rate of TLB is crucial to the performance of address translatio...
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06/05/2019
DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification
Graph data widely exist in many high-impact applications. Inspired by th...
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05/14/2019
Visual Analytics of Anomalous User Behaviors: A Survey
The increasing accessibility of data provides substantial opportunities ...
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01/25/2019
Deep Multimodality Model for Multi-task Multi-view Learning
Many real-world problems exhibit the coexistence of multiple types of he...
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06/23/2018
Optimizing the Wisdom of the Crowd: Inference, Learning, and Teaching
The unprecedented demand for large amount of data has catalyzed the tren...
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04/17/2018