33 citations · 85 across the 18 of their papers we have counts for
10 papers · 1 filter
Halo: Domain-Aware Query Optimization for Long-Context Question Answering
Pramod Chunduri, Francisco Romero, Ali Payani +2
Long-context question answering (QA) over lengthy documents is critical for applications such as financial analysis, legal review, and scientific research. Current approaches, such…
HONEYBEE: Efficient Role-based Access Control for Vector Databases via Dynamic Partitioning[Technical Report]
Hongbin Zhong, Matthew Lentz, Nina Narodytska +2
Enterprise deployments of vector databases require access control policies to protect sensitive data. These systems often implement access control through hybrid vector queries tha…
SketchQL Demonstration: Zero-shot Video Moment Querying with Sketches
Renzhi Wu, Pramod Chunduri, Dristi J Shah +5
In this paper, we will present SketchQL, a video database management system (VDBMS) for retrieving video moments with a sketch-based query interface. This novel interface allows us…
Dynamic Data Layout Optimization with Worst-case Guarantees
Kexin Rong, Paul Liu, Sarah Ashok Sonje +1
Many data analytics systems store and process large datasets in partitions containing millions of rows. By mapping rows to partitions in an optimized way, it is possible to improve…
DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data
Peng Li, Zhiyi Chen, Xu Chu +1
Data preprocessing is a crucial step in the machine learning process that transforms raw data into a more usable format for downstream ML models. However, it can be costly and time…
Rethinking Similarity Search: Embracing Smarter Mechanisms over Smarter Data
Renzhi Wu, Jingfan Meng, Jie Jeff Xu +2
In this vision paper, we propose a shift in perspective for improving the effectiveness of similarity search. Rather than focusing solely on enhancing the data quality, particularl…
Approximate Partition Selection for Big-Data Workloads using Summary Statistics
Kexin Rong, Yao Lu, Peter Bailis +2
Many big-data clusters store data in large partitions that support access at a coarse, partition-level granularity. As a result, approximate query processing via row-level sampling…
Locality-Sensitive Hashing for Earthquake Detection: A Case Study of Scaling Data-Driven Science
Kexin Rong, Clara E. Yoon, Karianne J. Bergen +4
In this work, we report on a novel application of Locality Sensitive Hashing (LSH) to seismic data at scale. Based on the high waveform similarity between reoccurring earthquakes,…
ASAP: Prioritizing Attention via Time Series Smoothing
Kexin Rong, Peter Bailis
Time series visualization of streaming telemetry (i.e., charting of key metrics such as server load over time) is increasingly prevalent in modern data platforms and applications.…
MacroBase: Prioritizing Attention in Fast Data
Peter Bailis, Edward Gan, Samuel Madden +3
As data volumes continue to rise, manual inspection is becoming increasingly untenable. In response, we present MacroBase, a data analytics engine that prioritizes end-user attenti…