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03/02/2023
Distillation from Heterogeneous Models for Top-K Recommendation
Recent recommender systems have shown remarkable performance by using an...
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02/27/2023
Learning Topology-Specific Experts for Molecular Property Prediction
Recently, graph neural networks (GNNs) have been successfully applied to...
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01/28/2023
Dynamic Multi-Behavior Sequence Modeling for Next Item Recommendation
Sequential Recommender Systems (SRSs) aim to predict the next item that ...
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12/21/2022
Generating Multiple-Length Summaries via Reinforcement Learning for Unsupervised Sentence Summarization
Sentence summarization shortens given texts while maintaining core conte...
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09/14/2022
Beyond Learning from Next Item: Sequential Recommendation via Personalized Interest Sustainability
Sequential recommender systems have shown effective suggestions by captu...
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02/26/2022
Toward Interpretable Semantic Textual Similarity via Optimal Transport-based Contrastive Sentence Learning
Recently, finetuning a pretrained language model to capture the similari...
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02/26/2022
Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering
Over the past decades, for One-Class Collaborative Filtering (OCCF), man...
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12/09/2021
Obtaining Calibrated Probabilities with Personalized Ranking Models
For personalized ranking models, the well-calibrated probability of an i...
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11/24/2021
Out-of-Category Document Identification Using Target-Category Names as Weak Supervision
Identifying outlier documents, whose content is different from the major...
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11/22/2021
Learnable Structural Semantic Readout for Graph Classification
With the great success of deep learning in various domains, graph neural...
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08/15/2021
Weakly Supervised Temporal Anomaly Segmentation with Dynamic Time Warping
Most recent studies on detecting and localizing temporal anomalies have ...
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07/08/2021
Unsupervised Proxy Selection for Session-based Recommender Systems
Session-based Recommender Systems (SRSs) have been actively developed to...
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06/16/2021
Topology Distillation for Recommender System
Recommender Systems (RS) have employed knowledge distillation which is a...
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06/05/2021
Bidirectional Distillation for Top-K Recommender System
Recommender systems (RS) have started to employ knowledge distillation, ...
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05/14/2021
Out-of-Manifold Regularization in Contextual Embedding Space for Text Classification
Recent studies on neural networks with pre-trained weights (i.e., BERT) ...
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05/13/2021
Bootstrapping User and Item Representations for One-Class Collaborative Filtering
The goal of one-class collaborative filtering (OCCF) is to identify the ...
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04/29/2021
Learning Heterogeneous Temporal Patterns of User Preference for Timely Recommendation
Recommender systems have achieved great success in modeling user's prefe...
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04/02/2021
Learnable Dynamic Temporal Pooling for Time Series Classification
With the increase of available time series data, predicting their class ...
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04/02/2021
Multi-Class Data Description for Out-of-distribution Detection
The capability of reliably detecting out-of-distribution samples is one ...
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12/08/2020
DE-RRD: A Knowledge Distillation Framework for Recommender System
Recent recommender systems have started to employ knowledge distillation...
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09/07/2020
Sparse Network Inversion for Key Instance Detection in Multiple Instance Learning
Multiple Instance Learning (MIL) involves predicting a single label for ...
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06/07/2020
Unsupervised Differentiable Multi-aspect Network Embedding
Network embedding is an influential graph mining technique for represent...
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11/26/2019
BHIN2vec: Balancing the Type of Relation in Heterogeneous Information Network
The goal of network embedding is to transform nodes in a network to a lo...
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11/15/2019
Unsupervised Attributed Multiplex Network Embedding
Nodes in a multiplex network are connected by multiple types of relation...
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06/04/2019
Collaborative Translational Metric Learning
Recently, matrix factorization-based recommendation methods have been cr...
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06/04/2019
Task-Guided Pair Embedding in Heterogeneous Network
Many real-world tasks solved by heterogeneous network embedding methods ...
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07/27/2018
Neural Sentence Embedding using Only In-domain Sentences for Out-of-domain Sentence Detection in Dialog Systems
To ensure satisfactory user experience, dialog systems must be able to d...
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04/11/2017
Federated Tensor Factorization for Computational Phenotyping
Tensor factorization models offer an effective approach to convert massi...
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05/25/2016