Search Results for author:
Found 5 papers, 2 papers with code
Denoising Time Cycle Modeling for Recommendation
We define the subset of user behaviors that are irrelevant to the target item as noises, which limits the performance of target-related time cycle modeling and affect the recommendation performance.
Discerning and Enhancing the Weighted Sum-Rate Maximization Algorithms in Communications
By probing the theoretical underpinnings linking the BCA and MM algorithmic frameworks, we reveal the direct correlations between the equivalent transformation techniques, essential to the development of WMMSE and WSR-FP, and the surrogate functions pivotal to WSR-MM.
An Unified Search and Recommendation Foundation Model for Cold-Start Scenario
With the development of large language models, LLM can extract global domain-invariant text features that serve both search and recommendation tasks.
Crossword: A Semantic Approach to Data Compression via Masking
The traditional methods for data compression are typically based on the symbol-level statistics, with the information source modeled as a long sequence of i. i. d.
Spatial Deep Learning for Wireless Scheduling
The optimal scheduling of interfering links in a dense wireless network with full frequency reuse is a challenging task.
