|
Publications and Preprints
|
-
Honeybee: Efficient Role-based Access Control for Vector Databases via Dynamic Partitioning
Hongbin Zhong, Matthew Lentz, Nina Narodytska, Adriana Szekeres, Kexin Rong
To appear at SIGMOD 2026.
-
VCR: Interpretable and Interactive Debugging of Object Detection Models with Visual Concepts
Jie Jeff Xu, Saahir Dhanani, Jorge Piazentin Ono, Wenbin He, Liu Ren, Kexin Rong
Information Systems 2025.
-
SketchQL: Video Moment Querying with a Visual Query Interface
Renzhi Wu*, Pramod Chunduri*, Ali Payani, Xu Chu, Joy Arulraj, Kexin Rong
SIGMOD 2025.
-
Inshrinkerator: Compressing Deep Learning Training Checkpoints via Dynamic Quantization
Amey Agrawal, Sameer Reddy, Satwik Bhattamishra, Venkata Prabhakara Sarath Nookala, Vidushi Vashishth, Kexin Rong, Alexey Tumanov
SoCC 2024.
-
Lotus: Characterization of Machine Learning Preprocessing Pipelines via Framework and Hardware Profiling
Rajveer Bachkaniwala, Harshith Lanka, Kexin Rong, Ada Gavrilovska
IISWC 2024. (Best Paper Finalist)
[code]
-
SketchQL Demonstration: Zero-shot Video Moment Querying with Sketches.
Renzhi Wu, Pramod Chunduri, Dristi Shah, Ashmitha Julius Aravind, Ali Payani, Xu Chu, Joy Arulraj, Kexin Rong.
VLDB 2024 Demo.
-
Demonstration of VCR: A Tabular Data Slicing Approach to Understanding Object Detection Model Performance.
Jie Jeff Xu, Saahir Dhanani, Jorge Piazentin Ono, Wenbin He, Liu Ren, Kexin Rong
VLDB 2024 Demo.
-
FALCON: Fair Active Learning using Multi-armed Bandits
Ki Hyun Tae, Hantian Zhang, Jaeyoung Park, Kexin Rong, Steven Euijong Whang
VLDB 2024.
[code]
-
Dynamic Data Layout Optimization with Worst-case Guarantees
Kexin Rong, Paul Liu, Sarah Ashok Sonje, Moses Charikar
ICDE 2024.
[slides][code]
-
Scaling a Declarative Cluster Manager Architecture with Query Optimization Techniques
Kexin Rong, Mihai Budiu, Athinagoras Skiadopoulos, Lalith Suresh, Amy Tai
VLDB 2023.
[slides] [code]
-
DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data
Peng Li, Zhiyi Chen, Xu Chu, Kexin Rong
SIGMOD 2023.
[slides] [code]
-
Interactive Demonstration of EVA
Gaurav Tarlok Kakkar, Aryan Rajoria, Myna Prasanna Kalluraya, Ashmita Raju, Jiashen Cao, Kexin Rong, Joy Arulraj
VLDB 2023 Demo.
[code]
-
Improving Computational and Human Efficiency in Large-Scale Data Analytics
Kexin Rong
PhD Thesis 2021. (SIGMOD Doctoral Dissertation Award Honorable Mention)
-
Approximate Partition Selection for Big-Data Workloads using Summary Statistics
Kexin Rong, Yao Lu, Peter Bailis, Srikanth Kandula, Philip Levis
VLDB 2020.
[talk]
-
Rehashing Kernel Evaluation in High Dimensions
Paris Siminelakis*, Kexin Rong*, Peter Bailis, Moses Charikar, Philip Levis.
ICML 2019. (Long talk)
[blog] [code] [supplementary]
-
CrossTrainer: Practical Domain Adaptation with Loss Reweighting
Justin Chen, Edward Gan, Kexin Rong, Sahaana Suri, Peter Bailis.
SIGMOD DEEM Workshop 2019.
-
Locality-Sensitive Hashing for Earthquake Detection: A Case Study of Scaling Data-Driven Science
Kexin Rong, Clara Yoon, Karianne Bergen, Hashem Elezabi, Peter Bailis, Philip Levis, Gregory Beroza.
VLDB 2018.
[blog] [video] [code] [seismology paper]
-
MacroBase: Prioritizing Attention in Fast Data
Firas Abuzaid, Peter Bailis, Jialin Ding, Edward Gan, Samuel Madden, Deepak Narayanan, Kexin Rong, Sahaana Suri.
ACM TODS 2018. "Best of SIGMOD 2017" Special Issue.
-
ASAP: Prioritizing Attention via Time Series Smoothing
Kexin Rong, Peter Bailis.
VLDB 2017.
[Datadog blog] [Timescale blog] [blog] [demo] [talk] [slides] [code]
-
Prioritizing Attention in Fast Data: Principles and Promise
Peter Bailis, Edward Gan, Kexin Rong, Sahaana Suri.
CIDR 2017.
-
MacroBase: Prioritizing Attention in Fast Data
Peter Bailis, Edward Gan, Samuel Madden, Deepak Narayanan, Kexin Rong, Sahaana Suri.
SIGMOD 2017 (Invited to ACM TODS "Best of SIGMOD 2017" Special Issue.)
[website] [code]
-
Demonstration: MacroBase, A Fast Data Analysis Engine
Peter Bailis, Edward Gan, Kexin Rong, Sahaana Suri.
SIGMOD 2017 Demo.
|
