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Found 5 papers, 1 papers with code
DynLLM: When Large Language Models Meet Dynamic Graph Recommendation
To bridge this gap, in this paper, we propose a novel framework, called DynLLM, to deal with the dynamic graph recommendation task with LLMs.
Practical Parallel Algorithms for Non-Monotone Submodular Maximization
Submodular maximization has found extensive applications in various domains within the field of artificial intelligence, including but not limited to machine learning, computer vision, and natural language processing.
A Smart Recycling Bin Using Waste Image Classification At The Edge
The model reached an accuracy of 95. 98% on Jetson Nano and 96. 64% on K210.
BCORLE($\lambda$): An Offline Reinforcement Learning and Evaluation Framework for Coupons Allocation in E-commerce Market
Further, a novel offline reinforcement learning method and an off-policy evaluation algorithm are proposed for policy learning and policy evaluation, respectively.
Interpretable performance analysis towards offline reinforcement learning: A dataset perspective
We make it open-source for fair and comprehensive competitions between offline RL algorithms with complete datasets and checkpoints being provided.
