5 papers
Scalable Algorithm for Dynamic Quasi-clique Detection
Jingbang Chen, Weinuo Li, Yingli Zhou +4
Identifying dense subgraphs known as quasi-cliques is pivotal in numerous graph mining tasks across domains such as social networks, biology, and e-commerce. While prior work has d…
From Static Inference to Dynamic Interaction: A Survey of Streaming Large Language Models
Junlong Tong, Zilong Wang, YuJie Ren +4
Standard Large Language Models (LLMs) are predominantly designed for static inference with pre-defined inputs, which limits their applicability in dynamic, real-time scenarios. To…
Fast and Optimal Differentially Private Frequent-Substring Mining
Peaker Guo, Rayne Holland, Hao Wu
Given a dataset of user-contributed strings, each of length at most , a key problem is how to identify all frequent substrings while preserving each user's privacy. Recen…
Improved Approximations for Hard Graph Problems using Predictions
Anders Aamand, Justin Y. Chen, Siddharth Gollapudi +2
We design improved approximation algorithms for NP-hard graph problems by incorporating predictions (e.g., learned from past data). Our prediction model builds upon and extends the…
Learning-Augmented Frequent Directions
Anders Aamand, Justin Y. Chen, Siddharth Gollapudi +2
An influential paper of Hsu et al. (ICLR'19) introduced the study of learning-augmented streaming algorithms in the context of frequency estimation. A fundamental problem in the st…