Across many domains (e.g., observability, networking, security), data processing pipelines face what we refer to as the CSP problem: achieving low Cost at large Scale, while maintaining high Performance. In response, we see several efforts to tackle CSP in various stages of the Collect-Transmit-Store-Analyze data lifec...
Milind Srivastava, Zeying Zhu, Yajie Zhou et al.· 0 citations
Asynchronous Federated Learning (AFL) enhances the efficiency of edge collaborative learning systems by asynchronously aggregating client updates to prevent slowdowns from slow clients. However, in non-IID scenarios, such operations magnify uneven learning among various local data, degrading global model generalization...
Xiaoyi Pang, Yajie Zhou, Zhibo Wang et al.· IEEE Transactions on Mobile...· 0 citations
Results show that privacy-sensitive visual and textual information can be recovered even from deep-layer LVLM hidden states, exposing the privacy risks of collaborative inference.
Shuaifan Jin, Zhibo Wang, Qiyuan Wang et al.· 0 citations
DeePCAP introduces a query-driven fidelity framework spanning packet- and flow-level queries to tackle the fidelity disconnection, and proposes a novel dimensionality reduction approach using frequency domain encoding to improve cost-fidelity trade-off.
Fenghao Dong, Yucheng Yin, Yajie Zhou et al.· Conference on Applications,...· 0 citations
This position paper outlines a common abstraction layer that can substantially lower the effort for designing agents with constrained creativity, and demonstrates early promise of this paradigm for two SysOps use cases: Root Cause Analysis and Network Configuration Generation.
SayanSinha, Vipul Harsh, Yajie Zhou et al.· 1 citation
TabQueryBench is a query-centric benchmark that uses SQL-shaped analytical queries as structural assessors for synthetic data fidelity, and provides an extensible foundation for query-centric synthetic-data evaluation.
