research
∙
04/26/2023
Bayesian Federated Learning: A Survey
Federated learning (FL) demonstrates its advantages in integrating distr...
share
research
∙
03/23/2023
ClinicLens: Visual Analytics for Exploring and Optimizing the Testing Capacity of Clinics given Uncertainty
Clinic testing plays a critical role in containing infectious diseases s...
research
∙
01/27/2023
Learning Informative Representation for Fairness-aware Multivariate Time-series Forecasting: A Group-based Perspective
Multivariate time series (MTS) forecasting has penetrated and benefited ...
research
∙
01/01/2023
eVAE: Evolutionary Variational Autoencoder
The surrogate loss of variational autoencoders (VAEs) poses various chal...
research
∙
10/06/2022
Edge-Varying Fourier Graph Networks for Multivariate Time Series Forecasting
The key problem in multivariate time series (MTS) analysis and forecasti...
research
∙
06/29/2022
Supervised Deep Hashing for High-dimensional and Heterogeneous Case-based Reasoning
Case-based Reasoning (CBR) on high-dimensional and heterogeneous data is...
research
∙
06/19/2022
Label and Distribution-discriminative Dual Representation Learning for Out-of-Distribution Detection
To classify in-distribution samples, deep neural networks learn label-di...
research
∙
06/19/2022
Out-of-distribution Detection by Cross-class Vicinity Distribution of In-distribution Data
Deep neural networks only learn to map in-distribution inputs to their c...
research
∙
06/19/2022
Supervision Adaptation Balances In-Distribution Generalization and Out-of-Distribution Detection
When there is a discrepancy between in-distribution (ID) samples and out...
research
∙
06/19/2022
Gray Learning from Non-IID Data with Out-of-distribution Samples
The quality of the training data annotated by experts cannot be guarante...
research
∙
04/04/2022
Explicit and Implicit Pattern Relation Analysis for Discovering Actionable Negative Sequences
Real-life events, behaviors and interactions produce sequential data. An...
research
∙
02/12/2022
Coupling Online-Offline Learning for Multi-distributional Data Streams
The distributions of real-life data streams are usually nonstationary, w...
research
∙
12/03/2021
Table2Vec: Automated Universal Representation Learning to Encode All-round Data DNA for Benchmarkable and Explainable Enterprise Data Science
Enterprise data typically involves multiple heterogeneous data sources a...
research
∙
08/23/2021
Modeling COVID-19 uncertainties evolving over time and density-dependent social reinforcement and asymptomatic infections
The novel coronavirus disease 2019 (COVID-19) presents unique and unknow...
research
∙
08/23/2021
Revealing Distributional Vulnerability of Explicit Discriminators by Implicit Generators
An explicit discriminator trained on observable in-distribution (ID) sam...
research
∙
08/19/2021
Personalized next-best action recommendation with multi-party interaction learning for automated decision-making
Automated next-best action recommendation for each customer in a sequent...
research
∙
08/18/2021
DeepExpress: Heterogeneous and Coupled Sequence Modeling for Express Delivery Prediction
The prediction of express delivery sequence, i.e., modeling and estimati...
research
∙
07/20/2021
AI in Finance: Challenges, Techniques and Opportunities
AI in finance broadly refers to the applications of AI techniques in fin...
research
∙
06/23/2021
Recurrent Coupled Topic Modeling over Sequential Documents
The abundant sequential documents such as online archival, social media ...
research
∙
05/13/2021
Graph Learning based Recommender Systems: A Review
Recent years have witnessed the fast development of the emerging topic o...
research
∙
04/16/2021
COVID-19 Modeling: A Review
To tackle the COVID-19 pandemic, massive efforts have been made in model...
research
∙
03/21/2021
Homophily Outlier Detection in Non-IID Categorical Data
Most of existing outlier detection methods assume that the outlier facto...
research
∙
09/15/2020
Deep Reinforcement Learning for Unknown Anomaly Detection
We address a critical yet largely unsolved anomaly detection problem, in...
research
∙
08/09/2020
Scientific Article Recommendation: Exploiting Common Author Relations and Historical Preferences
Scientific article recommender systems are playing an increasingly impor...
research
∙
07/21/2020
Unsupervised Heterogeneous Coupling Learning for Categorical Representation
Complex categorical data is often hierarchically coupled with heterogene...
research
∙
07/10/2020
AI in FinTech: A Research Agenda
Smart FinTech has emerged as a new area that synthesizes and transforms ...
research
∙
07/06/2020
Deep Learning for Anomaly Detection: A Review
Anomaly detection, a.k.a. outlier detection, has been a lasting yet acti...
research
∙
07/01/2020
Non-IID Recommender Systems: A Review and Framework of Recommendation Paradigm Shifting
While recommendation plays an increasingly critical role in our living, ...
research
∙
07/01/2020
Coupling Learning of Complex Interactions
Complex applications such as big data analytics involve different forms ...
research
∙
07/01/2020
Data Science: A Comprehensive Overview
The twenty-first century has ushered in the age of big data and data eco...
research
∙
06/28/2020
Data Science: Nature and Pitfalls
Data science is creating very exciting trends as well as significant con...
research
∙
06/28/2020
Data Science: Challenges and Directions
While data science has emerged as a contentious new scientific field, en...
research
∙
05/30/2020
Jointly Modeling Intra- and Inter-transaction Dependencies with Hierarchical Attentive Transaction Embeddings for Next-item Recommendation
A transaction-based recommender system (TBRS) aims to predict the next i...
research
∙
04/22/2020
Graph Learning Approaches to Recommender Systems: A Review
Recent years have witnessed the fast development of the emerging topic o...
research
∙
12/28/2019
Sequential Recommender Systems: Challenges, Progress and Prospects
The emerging topic of sequential recommender systems has attracted incre...
research
∙
07/01/2019
FiDi-RL: Incorporating Deep Reinforcement Learning with Finite-Difference Policy Search for Efficient Learning of Continuous Control
In recent years significant progress has been made in dealing with chall...
research
∙
05/25/2019
Multi-view Information-theoretic Co-clustering for Co-occurrence Data
Multi-view clustering has received much attention recently. Most of the ...
research
∙
05/17/2019
TBQ(σ): Improving Efficiency of Trace Utilization for Off-Policy Reinforcement Learning
Off-policy reinforcement learning with eligibility traces is challenging...
research
∙
02/13/2019
A Survey on Session-based Recommender Systems
Session-based recommender systems (SBRS) are an emerging topic in the re...
research
∙
06/13/2018
Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection
Learning expressive low-dimensional representations of ultrahigh-dimensi...
research
∙
10/06/2013
Learning Hidden Structures with Relational Models by Adequately Involving Rich Information in A Network
Effectively modelling hidden structures in a network is very practical b...
research
∙
06/13/2013
Non-parametric Power-law Data Clustering
It has always been a great challenge for clustering algorithms to automa...
research
∙
06/13/2013
A Convergence Theorem for the Graph Shift-type Algorithms
Graph Shift (GS) algorithms are recently focused as a promising approach...
research
∙
06/13/2013
Dynamic Infinite Mixed-Membership Stochastic Blockmodel
Directional and pairwise measurements are often used to model inter-rela...
research
∙
06/12/2013
Copula Mixed-Membership Stochastic Blockmodel for Intra-Subgroup Correlations
The Mixed-Membership Stochastic Blockmodel (MMSB) is a popular framework...
research
∙
05/24/2013