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09/14/2023
Distributed formation control of end-effector of mixed planar fully- and under-actuated manipulators
This paper addresses the problem of end-effector formation control for a...
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08/27/2023
Confucius: Iterative Tool Learning from Introspection Feedback by Easy-to-Difficult Curriculum
Augmenting large language models (LLMs) with external tools has emerged ...
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08/27/2023
Label Denoising through Cross-Model Agreement
Learning from corrupted labels is very common in real-world machine-lear...
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07/19/2023
Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community
The research field of Information Retrieval (IR) has evolved significant...
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05/24/2023
How Graph Convolutions Amplify Popularity Bias for Recommendation?
Graph convolutional networks (GCNs) have become prevalent in recommender...
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05/18/2023
Contrastive State Augmentations for Reinforcement Learning-Based Recommender Systems
Learning reinforcement learning (RL)-based recommenders from historical ...
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05/09/2023
Improving Implicit Feedback-Based Recommendation through Multi-Behavior Alignment
Recommender systems that learn from implicit feedback often use large vo...
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03/04/2023
A Self-Correcting Sequential Recommender
Sequential recommendations aim to capture users' preferences from their ...
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12/22/2022
Variational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendation
Conversational recommender systems (CRSs) often utilize external knowled...
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10/16/2022
On the User Behavior Leakage from Recommender System Exposure
Modern recommender systems are trained to predict users potential future...
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09/27/2022
Robust Fused Lasso Penalized Huber Regression with Nonasymptotic Property and Implementation Studies
For some special data in reality, such as the genetic data, adjacent gen...
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06/15/2022
Rethinking Reinforcement Learning for Recommendation: A Prompt Perspective
Modern recommender systems aim to improve user experience. As reinforcem...
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05/20/2022
GDSRec: Graph-Based Decentralized Collaborative Filtering for Social Recommendation
Generating recommendations based on user-item interactions and user-user...
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11/05/2021
Supervised Advantage Actor-Critic for Recommender Systems
Casting session-based or sequential recommendation as reinforcement lear...
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10/28/2021
Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning
Since the inception of Recommender Systems (RS), the accuracy of the rec...
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09/28/2021
Extracting Attentive Social Temporal Excitation for Sequential Recommendation
In collaborative filtering, it is an important way to make full use of s...
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09/27/2021
ICMT: Item Cluster-Wise Multi-Objective Training for Long-Tail Recommendation
Item recommendation based on historical user-item interactions is of vit...
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05/20/2021
Probabilistic and Variational Recommendation Denoising
Learning from implicit feedback is one of the most common cases in the a...
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05/10/2021
AutoDebias: Learning to Debias for Recommendation
Recommender systems rely on user behavior data like ratings and clicks t...
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03/05/2021
Graph Convolutional Embeddings for Recommender Systems
Modern recommender systems (RS) work by processing a number of signals t...
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06/10/2020
Self-Supervised Reinforcement Learning forRecommender Systems
In session-based or sequential recommendation, it is important to consid...
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06/10/2020
Self-Supervised Reinforcement Learning for Recommender Systems
In session-based or sequential recommendation, it is important to consid...
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04/09/2020
Graph Highway Networks
Graph Convolution Networks (GCN) are widely used in learning graph repre...
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02/16/2020
Generalized Embedding Machines for Recommender Systems
Factorization machine (FM) is an effective model for feature-based recom...
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04/29/2019
Relational Collaborative Filtering:Modeling Multiple Item Relations for Recommendation
Existing item-based collaborative filtering (ICF) methods leverage only ...
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11/27/2017