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ORCIDKexin Rong 0001
Person information
- affiliation: Georgia Institute of Technology, GA, USA
- affiliation (Ph.D.): Stanford University, CA, USA
Other persons with the same name
- Kexin Rong 0002 — Zhejiang Normal University, Jinhua, China
- Kexin Rong 0003 — Harbin Institute of Technology, Harbin, China
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2020 – today
- 2024
[j11]Renzhi Wu
, Pramod Chunduri, Ali Payani, Xu Chu, Joy Arulraj, Kexin Rong:
SketchQL: Video Moment Querying with a Visual Query Interface. Proc. ACM Manag. Data 2(4): 204:1-204:27 (2024)- [j10]Ki Hyun Tae, Hantian Zhang, Jaeyoung Park, Kexin Rong, Steven Euijong Whang:
Falcon: Fair Active Learning using Multi-armed Bandits. Proc. VLDB Endow. 17(5): 952-965 (2024) - [j9]Renzhi Wu, Pramod Chunduri, Dristi J. Shah, Ashmitha Julius Aravind, Ali Payani, Xu Chu, Joy Arulraj, Kexin Rong:
SketchQL Demonstration: Zero-shot Video Moment Querying with Sketches. Proc. VLDB Endow. 17(12): 4429-4432 (2024) - [j8]Jie Jeff Xu, Saahir Dhanani, Jorge Henrique Piazentin Ono, Wenbin He, Liu Ren, Kexin Rong:
Demonstration of VCR: A Tabular Data Slicing Approach to Understanding Object Detection Model Performance. Proc. VLDB Endow. 17(12): 4453-4456 (2024) - [c8]Amey Agrawal, Sameer Reddy, Satwik Bhattamishra, Venkata Prabhakara Sarath Nookala, Vidushi Vashishth, Kexin Rong, Alexey Tumanov:
Inshrinkerator: Compressing Deep Learning Training Checkpoints via Dynamic Quantization. SoCC 2024: 1012-1031 - [c7]Kexin Rong, Paul Liu, Sarah Ashok Sonje, Moses Charikar:
Dynamic Data Layout Optimization with Worst-Case Guarantees. ICDE 2024: 4288-4301 - [c6]Jean-Daniel Fekete, Kexin Rong, Behrooz Omidvar-Tehrani, Roee Shraga:
Eighth Workshop on Human-In-the-Loop Data Analytics (HILDA). SIGMOD Conference Companion 2024: 657-658 - [e1]Jean-Daniel Fekete, Behrooz Omidvar-Tehrani, Kexin Rong, Roee Shraga:
Proceedings of the 2024 Workshop on Human-In-the-Loop Data Analytics, HILDA 24, Santiago, Chile, 14 June 2024. ACM 2024 [contents] - [i11]Yao Lu, Song Bian, Lequn Chen, Yongjun He, Yulong Hui, Matthew Lentz, Beibin Li, Fei Liu, Jialin Li, Qi Liu, Rui Liu, Xiaoxuan Liu, Lin Ma, Kexin Rong, Jianguo Wang, Yingjun Wu, Yongji Wu, Huanchen Zhang, Minjia Zhang, Qizhen Zhang, Tianyi Zhou, Danyang Zhuo:
Computing in the Era of Large Generative Models: From Cloud-Native to AI-Native. CoRR abs/2401.12230 (2024) - [i10]Ki Hyun Tae, Hantian Zhang, Jaeyoung Park, Kexin Rong, Steven Euijong Whang:
Falcon: Fair Active Learning using Multi-armed Bandits. CoRR abs/2401.12722 (2024) - [i9]Kexin Rong, Paul Liu, Sarah Ashok Sonje, Moses Charikar:
Dynamic Data Layout Optimization with Worst-case Guarantees. CoRR abs/2405.04984 (2024) - [i8]Renzhi Wu, Pramod Chunduri, Dristi J. Shah, Ashmitha Julius Aravind, Ali Payani, Xu Chu, Joy Arulraj, Kexin Rong:
SketchQL Demonstration: Zero-shot Video Moment Querying with Sketches. CoRR abs/2405.18334 (2024) - 2023
- [j7]Peng Li, Zhiyi Chen, Xu Chu, Kexin Rong:
DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data. Proc. ACM Manag. Data 1(2): 183:1-183:26 (2023) - [j6]Kexin Rong, Mihai Budiu, Athinagoras Skiadopoulos, Lalith Suresh, Amy Tai:
Scaling a Declarative Cluster Manager Architecture with Query Optimization Techniques. Proc. VLDB Endow. 16(10): 2618-2631 (2023) - [j5]Gaurav Tarlok Kakkar, Aryan Rajoria, Myna Prasanna Kalluraya, Ashmita Raju, Jiashen Cao, Kexin Rong, Joy Arulraj:
Interactive Demonstration of EVA. Proc. VLDB Endow. 16(12): 4082-4085 (2023) - [i7]Amey Agrawal, Sameer Reddy, Satwik Bhattamishra, Venkata Prabhakara Sarath Nookala, Vidushi Vashishth, Kexin Rong, Alexey Tumanov:
DynaQuant: Compressing Deep Learning Training Checkpoints via Dynamic Quantization. CoRR abs/2306.11800 (2023) - [i6]Renzhi Wu, Jingfan Meng, Jie Jeff Xu, Huayi Wang, Kexin Rong:
Rethinking Similarity Search: Embracing Smarter Mechanisms over Smarter Data. CoRR abs/2308.00909 (2023) - [i5]Peng Li, Zhiyi Chen, Xu Chu, Kexin Rong:
DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data. CoRR abs/2308.10915 (2023) - 2021
- [b1]Kexin Rong:
Improving computational and human efficiency in large-scale data analytics. Stanford University, USA, 2021 - 2020
- [j4]Kexin Rong, Yao Lu, Peter Bailis, Srikanth Kandula, Philip Alexander Levis:
Approximate Partition Selection for Big-Data Workloads using Summary Statistics. Proc. VLDB Endow. 13(11): 2606-2619 (2020) - [i4]Kexin Rong, Yao Lu, Peter Bailis, Srikanth Kandula, Philip Alexander Levis:
Approximate Partition Selection for Big-Data Workloads using Summary Statistics. CoRR abs/2008.10569 (2020)
2010 – 2019
- 2019
- [c5]Paris Siminelakis, Kexin Rong, Peter Bailis, Moses Charikar, Philip Alexander Levis:
Rehashing Kernel Evaluation in High Dimensions. ICML 2019: 5789-5798 - [c4]Justin Chen, Edward Gan, Kexin Rong, Sahaana Suri, Peter Bailis:
CrossTrainer: Practical Domain Adaptation with Loss Reweighting. DEEM@SIGMOD 2019: 2:1-2:10 - [i3]Justin Chen, Edward Gan, Kexin Rong, Sahaana Suri, Peter Bailis:
CrossTrainer: Practical Domain Adaptation with Loss Reweighting. CoRR abs/1905.02304 (2019) - 2018
- [j3]Kexin Rong, Clara E. Yoon, Karianne J. Bergen, Hashem Elezabi, Peter Bailis, Philip Alexander Levis, Gregory C. Beroza:
Locality-Sensitive Hashing for Earthquake Detection: A Case Study Scaling Data-Driven Science. Proc. VLDB Endow. 11(11): 1674-1687 (2018) - [j2]Firas Abuzaid, Peter Bailis, Jialin Ding, Edward Gan, Samuel Madden, Deepak Narayanan, Kexin Rong, Sahaana Suri:
MacroBase: Prioritizing Attention in Fast Data. ACM Trans. Database Syst. 43(4): 15:1-15:45 (2018) - [i2]Kexin Rong, Clara E. Yoon, Karianne J. Bergen, Hashem Elezabi, Peter Bailis, Philip Alexander Levis, Gregory C. Beroza:
Locality-Sensitive Hashing for Earthquake Detection: A Case Study Scaling Data-Driven Science. CoRR abs/1803.09835 (2018) - 2017
- [j1]Kexin Rong, Peter Bailis:
ASAP: Prioritizing Attention via Time Series Smoothing. Proc. VLDB Endow. 10(11): 1358-1369 (2017) - [c3]Peter Bailis, Edward Gan, Kexin Rong, Sahaana Suri:
Prioritizing Attention in Analytic Monitoring. CIDR 2017 - [c2]Peter Bailis, Edward Gan, Samuel Madden, Deepak Narayanan, Kexin Rong, Sahaana Suri:
MacroBase: Prioritizing Attention in Fast Data. SIGMOD Conference 2017: 541-556 - [c1]Peter Bailis, Edward Gan, Kexin Rong, Sahaana Suri:
Demonstration: MacroBase, A Fast Data Analysis Engine. SIGMOD Conference 2017: 1699-1702 - [i1]Kexin Rong, Peter Bailis:
ASAP: Automatic Smoothing for Attention Prioritization in Streaming Time Series Visualization. CoRR abs/1703.00983 (2017)
Coauthor Index
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last updated on 2024-12-02 21:27 CET by the dblp team
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