Name
Affiliation
Papers
HWANJO YU
POSTECH (Pohang University of Science and Technology), Pohang, South Korea
148
Collaborators
Citations 
PageRank 
176
1715
114.02
Referers 
Referees 
References 
4456
2786
1642
Search Limit
1001000
Title
Citations
PageRank
Year
Beyond Learning from Next Item: Sequential Recommendation via Personalized Interest Sustainability00.342022
Personalized Knowledge Distillation for Recommender System00.342022
TaxoCom: Topic Taxonomy Completion with Hierarchical Discovery of Novel Topic Clusters00.342022
Topology Distillation for Recommender System10.382021
Learnable Dynamic Temporal Pooling For Time Series Classification00.342021
Bootstrapping User and Item Representations for One-Class Collaborative Filtering00.342021
Bidirectional Distillation for Top-K Recommender System10.372021
Weakly Supervised Temporal Anomaly Segmentation with Dynamic Time Warping.00.342021
Learnable Structural Semantic Readout for Graph Classification00.342021
Out-of-Category Document Identification Using Target-Category Names as Weak Supervision00.342021
Learning Heterogeneous Temporal Patterns of User Preference for Timely Recommendation20.392021
Learning to utilize auxiliary reviews for recommendation00.342021
Item-side ranking regularized distillation for recommender system00.342021
Unsupervised Attributed Multiplex Network Embedding20.362020
Convolutional Neural Networks with Compression Complexity Pooling for Out-of-Distribution Image Detection00.342020
Multi-class Data Description for Out-of-distribution Detection10.392020
PUMAD:PU Metric Learning for Anomaly Detection10.362020
Scalable disk-based topic modeling for memory limited devices.00.342020
Deep Rating Elicitation for New Users in Collaborative Filtering00.342020
Unsupervised Differentiable Multi-aspect Network Embedding10.352020
Fast and memory-efficient algorithms for high-order Tucker decomposition00.342020
Click-aware Purchase Prediction with Push at the Top30.412020
Interest Sustainability-Aware Recommender System00.342020
Action Space Learning for Heterogeneous User Behavior Prediction.00.342019
Semi-Supervised Learning for Cross-Domain Recommendation to Cold-Start Users120.612019
Target-aware convolutional neural network for target-level sentiment analysis.00.342019
An encoder-decoder switch network for purchase prediction.10.342019
Adversarial Approach to Domain Adaptation for Reinforcement Learning on Dialog Systems00.342019
Sequential and Diverse Recommendation with Long Tail.00.342019
DILOF: Effective and Memory Efficient Local Outlier Detection in Data Streams.40.422018
Sentiment Classification with Convolutional Neural Network using Multiple Word Representations00.342018
Collaborative Translational Metric Learning30.372018
Neural sentence embedding using only in-domain sentences for out-of-domain sentence detection in dialog systems.00.342018
DualSentiNet: Dual Prediction of Word and Document Sentiments Using Shared Word Embedding00.342018
Disk-based Matrix Completion for Memory Limited Devices.00.342018
Do "Also-Viewed" Products Help User Rating Prediction?100.492017
Federated Tensor Factorization for Computational Phenotyping.90.482017
Deep hybrid recommender systems via exploiting document context and statistics of items.180.582017
Influence maximization based on reachability sketches in dynamic graphs.50.402017
Two-stage approach to named entity recognition using Wikipedia and DBpedia.00.342017
RecTime: Real-Time recommender system for online broadcasting.50.402017
DiagTree: Diagnostic Tree for Differential Diagnosis.00.342017
Tensor-Factorization-Based Phenotyping using Group Information: Case Study on the Efficacy of Statins00.342017
Your Click Knows It: Predicting User Purchase through Improved User-Item Pairwise Relationship.00.342017
Answer ranking based on named entity types for question answering.00.342017
Convolutional Matrix Factorization for Document Context-Aware Recommendation.991.912016
TRecSo: Enhancing Top-k Recommendation With Social Information.70.442016
Automatic Open Knowledge Acquisition via Long Short-Term Memory Networks with Feedback Negative Sampling.00.342016
Mathematical Model for Processing Multi-user Requests on POMDP Hybrid Dialog Management00.342016
Improving top-K recommendation with truster and trustee relationship in user trust network.80.492016
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