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09/06/2023
Enhancing Event Sequence Modeling with Contrastive Relational Inference
Neural temporal point processes(TPPs) have shown promise for modeling co...
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08/21/2023
Leveraging Large Language Models for Pre-trained Recommender Systems
Recent advancements in recommendation systems have shifted towards more ...
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08/21/2023
Enhancing Recommender Systems with Large Language Model Reasoning Graphs
Recommendation systems aim to provide users with relevant suggestions, b...
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07/29/2023
Continual Learning in Predictive Autoscaling
Predictive Autoscaling is used to forecast the workloads of servers and ...
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06/16/2023
Automatic Deduction Path Learning via Reinforcement Learning with Environmental Correction
Automatic bill payment is an important part of business operations in fi...
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11/21/2022
A Graph Regularized Point Process Model For Event Propagation Sequence
Point process is the dominant paradigm for modeling event sequences occu...
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10/04/2022
HYPRO: A Hybridly Normalized Probabilistic Model for Long-Horizon Prediction of Event Sequences
In this paper, we tackle the important yet under-investigated problem of...
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07/11/2022
Learning Large-scale Universal User Representation with Sparse Mixture of Experts
Learning user sequence behaviour embedding is very sophisticated and cha...
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05/31/2022
A Meta Reinforcement Learning Approach for Predictive Autoscaling in the Cloud
Predictive autoscaling (autoscaling with workload forecasting) is an imp...
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01/29/2022