research
∙
08/13/2023
CDR: Conservative Doubly Robust Learning for Debiased Recommendation
In recommendation systems (RS), user behavior data is observational rath...
share
research
∙
08/10/2023
Effect of eHMI on pedestrian road crossing behavior in shared space with Automated Vehicles-A Virtual Reality study
A shared space area is a low-speed urban area in which pedestrians, cycl...
research
∙
08/07/2023
A data-driven approach to predict decision point choice during normal and evacuation wayfinding in multi-story buildings
Understanding pedestrian route choice behavior in complex buildings is i...
research
∙
06/17/2023
OpenGSL: A Comprehensive Benchmark for Graph Structure Learning
Graph Neural Networks (GNNs) have emerged as the de facto standard for r...
research
∙
04/20/2023
Pedestrian wayfinding behavior in a multi-story building: a comprehensive modeling study featuring route choice, wayfinding performance, and observation behavior
This paper proposes a comprehensive approach for modeling pedestrian way...
research
∙
12/28/2022
Robust Sequence Networked Submodular Maximization
In this paper, we study the Robust optimization for sequence Networked s...
research
∙
11/30/2022
Statistical treatment of convolutional neural network super-resolution of inland surface wind for subgrid-scale variability quantification
Machine learning models are frequently employed to perform either purely...
research
∙
11/22/2022
Accelerating Diffusion Sampling with Classifier-based Feature Distillation
Although diffusion model has shown great potential for generating higher...
research
∙
06/21/2022
sqSGD: Locally Private and Communication Efficient Federated Learning
Federated learning (FL) is a technique that trains machine learning mode...
research
∙
06/07/2022
Improving Knowledge Graph Embedding via Iterative Self-Semantic Knowledge Distillation
Knowledge graph embedding (KGE) has been intensively investigated for li...
research
∙
03/26/2022
Knowledge Distillation with the Reused Teacher Classifier
Knowledge distillation aims to compress a powerful yet cumbersome teache...
research
∙
12/28/2021
Online Adversarial Distillation for Graph Neural Networks
Knowledge distillation has recently become a popular technique to improv...
research
∙
10/19/2021
Spectral Variability Augmented Sparse Unmixing of Hyperspectral Images
Spectral unmixing (SU) expresses the mixed pixels existed in hyperspectr...
research
∙
09/14/2021
Exploring the Connection between Knowledge Distillation and Logits Matching
Knowledge distillation is a generalized logits matching technique for mo...
research
∙
03/02/2021
Development of a VR tool to study pedestrian route and exit choice behaviour in a multi-story building
Although route and exit choice in complex buildings are important aspect...
research
∙
11/16/2020
CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation
Sampling strategies have been widely applied in many recommendation syst...
research
∙
11/16/2020
SamWalker++: recommendation with informative sampling strategy
Recommendation from implicit feedback is a highly challenging task due t...
research
∙
06/15/2020
Efficient Black-Box Adversarial Attack Guided by the Distribution of Adversarial Perturbations
This work studied the score-based black-box adversarial attack problem, ...
research
∙
03/16/2020
Toward Adversarial Robustness via Semi-supervised Robust Training
Adversarial examples have been shown to be the severe threat to deep neu...
research
∙
03/04/2020
Fast Adaptively Weighted Matrix Factorization for Recommendation with Implicit Feedback
Recommendation from implicit feedback is a highly challenging task due t...
research
∙
02/23/2020
Practical and Bilateral Privacy-preserving Federated Learning
Federated learning, as an emerging distributed training model of neural ...
research
∙
12/01/2019
