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09/15/2023
To Predict or to Reject: Causal Effect Estimation with Uncertainty on Networked Data
Due to the imbalanced nature of networked observational data, the causal...
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07/29/2023
Graph Condensation for Inductive Node Representation Learning
Graph neural networks (GNNs) encounter significant computational challen...
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06/18/2023
Personalized Elastic Embedding Learning for On-Device Recommendation
To address privacy concerns and reduce network latency, there has been a...
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04/26/2023
Self-Supervised Multi-Modal Sequential Recommendation
With the increasing development of e-commerce and online services, perso...
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04/24/2023
WizardLM: Empowering Large Language Models to Follow Complex Instructions
Training large language models (LLM) with open-domain instruction follow...
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04/12/2023
Optimal Testing of Generalized Reed-Muller Codes in Fewer Queries
A local tester for an error correcting code C⊆Σ^n is a tester that makes...
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04/08/2023
Model-Agnostic Decentralized Collaborative Learning for On-Device POI Recommendation
As an indispensable personalized service in Location-based Social Networ...
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04/07/2023
Continuous Input Embedding Size Search For Recommender Systems
Latent factor models are the most popular backbones for today's recommen...
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12/20/2022
A Pattern Discovery Approach to Multivariate Time Series Forecasting
Multivariate time series forecasting constitutes important functionality...
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12/06/2022
Trajectory Flow Map: Graph-based Approach to Analysing Temporal Evolution of Aggregated Traffic Flows in Large-scale Urban Networks
This paper proposes a graph-based approach to representing spatio-tempor...
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11/17/2022
Approaching the Soundness Barrier: A Near Optimal Analysis of the Cube versus Cube Test
The Cube versus Cube test is a variant of the well-known Plane versus Pl...
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09/10/2022
A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis
The continued digitization of societal processes translates into a proli...
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08/11/2022
Uncertainty Quantification for Traffic Forecasting: A Unified Approach
Uncertainty is an essential consideration for time series forecasting ta...
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07/28/2022
ReFRS: Resource-efficient Federated Recommender System for Dynamic and Diversified User Preferences
Owing to its nature of scalability and privacy by design, federated lear...
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06/20/2022
Bandwidth-Efficient Multi-video Prefetching for Short Video Streaming
Applications that allow sharing of user-created short videos exploded in...
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05/30/2022
Cache-Augmented Inbatch Importance Resampling for Training Recommender Retriever
Recommender retrievers aim to rapidly retrieve a fraction of items from ...
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04/07/2022
Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection—Extended Version
Time series data occurs widely, and outlier detection is a fundamental p...
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01/08/2022
DeHIN: A Decentralized Framework for Embedding Large-scale Heterogeneous Information Networks
Modeling heterogeneity by extraction and exploitation of high-order info...
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11/22/2021
Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles – Extended Version
With the sweeping digitalization of societal, medical, industrial, and s...
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10/16/2021
Multimodal Dialogue Response Generation
Responsing with image has been recognized as an important capability for...
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09/13/2021
Fast Variational AutoEncoder with Inverted Multi-Index for Collaborative Filtering
Variational AutoEncoder (VAE) has been extended as a representative nonl...
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06/11/2021
HIFI: Anomaly Detection for Multivariate Time Series with High-order Feature Interactions
Monitoring complex systems results in massive multivariate time series d...
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05/11/2021
Learning to Ask Appropriate Questions in Conversational Recommendation
Conversational recommender systems (CRSs) have revolutionized the conven...
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03/30/2021
Historical Inertia: An Ignored but Powerful Baseline for Long Sequence Time-series Forecasting
Long sequence time-series forecasting (LSTF) has become increasingly pop...
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03/24/2021
Hierarchical Hyperedge Embedding-based Representation Learning for Group Recommendation
In this work, we study group recommendation in a particular scenario, na...
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03/02/2021
Efficient Optimal Selection for Composited Advertising Creatives with Tree Structure
Ad creatives are one of the prominent mediums for online e-commerce adve...
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02/28/2021
Automated Creative Optimization for E-Commerce Advertising
Advertising creatives are ubiquitous in E-commerce advertisements and ae...
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11/10/2020
MP-ResNet: Multi-path Residual Network for the Semantic segmentation of High-Resolution PolSAR Images
There are limited studies on the semantic segmentation of high-resolutio...
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10/02/2020
Overcoming Data Sparsity in Group Recommendation
It has been an important task for recommender systems to suggest satisfy...
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09/24/2020
SOUP: Spatial-Temporal Demand Forecasting and Competitive Supply
We consider a setting with an evolving set of requests for transportatio...
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07/27/2020
Reconstruction Regularized Deep Metric Learning for Multi-label Image Classification
In this paper, we present a novel deep metric learning method to tackle ...
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06/01/2020
(Locally) Differentially Private Combinatorial Semi-Bandits
In this paper, we study Combinatorial Semi-Bandits (CSB) that is an exte...
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06/01/2020
Locally Differentially Private (Contextual) Bandits Learning
We study locally differentially private (LDP) bandits learning in this p...
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02/12/2020
On Layer Normalization in the Transformer Architecture
The Transformer is widely used in natural language processing tasks. To ...
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02/10/2020
Combinatorial Semi-Bandit in the Non-Stationary Environment
In this paper, we investigate the non-stationary combinatorial semi-band...
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02/10/2020
Bilinear Graph Neural Network with Node Interactions
Graph Neural Network (GNN) is a powerful model to learn representations ...
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02/10/2020
Bilinear Graph Neural Network with Neighbor Interactions
Graph Neural Network (GNN) is a powerful model to learn representations ...
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05/30/2019
Equipping Experts/Bandits with Long-term Memory
We propose the first reduction-based approach to obtaining long-term mem...
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02/20/2019
Learning Transferable Self-attentive Representations for Action Recognition in Untrimmed Videos with Weak Supervision
Action recognition in videos has attracted a lot of attention in the pas...
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05/18/2018
Efficient Online Portfolio with Logarithmic Regret
We study the decades-old problem of online portfolio management and prop...
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02/21/2018
PABO: A Link-Layer Congestion Mitigation Mechanism Based on Packet Bounce
In today's data center, a diverse mix of throughput-sensitive long flows...
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09/20/2017
ProbeSim: Scalable Single-Source and Top-k SimRank Computations on Dynamic Graphs
Single-source and top-k SimRank queries are two important types of simil...
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08/30/2017
End-to-end Learning for Short Text Expansion
Effectively making sense of short texts is a critical task for many real...
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07/19/2017
Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints
Algorithm-dependent generalization error bounds are central to statistic...
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03/29/2017