Josh Kimball

According to our database, Josh Kimball authored at least 25 papers between 2013 and 2026.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2026

Variable-Length Audio Fingerprinting.

Hongjie Chen, Hanyu Meng, Huimin Zeng, Ryan A. Rossi, Lie Lu, Josh Kimball

CoRR, March, 2026

LayoutBench: Performance Benchmarking of Cloud Storage Layouts for Multimedia Data.

Debopam Sanyal, Hongjie Chen, Alexey Tumanov, Joshua Kimball

Proceedings of the Sixth European Workshop on Machine Learning and Systems, EuroMLSys 2026, 2026

ADEPT: Interactive Visual Analytics for Audio Dataset Exploration and Preparation.

Chen Chen, Tica Lin, Josh Kimball

Proceedings of the 2026 Designing Interactive Systems Conference, 2026

2025

DPAR: Dynamic Patchification for Efficient Autoregressive Visual Generation.

Divyansh Srivastava, Akshay Mehra, Pranav Maneriker, Debopam Sanyal, Vishnu Raj, Vijay Kamarshi, Fan Du, Joshua Kimball

CoRR, December, 2025

CompanionCast: A Multi-Agent Conversational AI Framework with Spatial Audio for Social Co-Viewing Experiences.

Yiyang Wang, Chen Chen, Tica Lin, Vishnu Raj, Josh Kimball, Alex Cabral, Josiah D. Hester

CoRR, December, 2025

Measuring Time-Series Dataset Similarity using Wasserstein Distance.

Hongjie Chen, Akshay Mehra, Josh Kimball, Ryan A. Rossi

CoRR, July, 2025

Model-agnostic Coreset Selection via LLM-based Concept Bottlenecks.

Akshay Mehra, Trisha Mittal, Subhadra Gopalakrishnan, Joshua Kimball

CoRR, February, 2025

Antidote: Post-fine-tuning Safety Alignment for Large Language Models against Harmful Fine-tuning Attack.

Tiansheng Huang, Gautam Bhattacharya, Pratik Joshi, Joshua Kimball, Ling Liu

Proceedings of the Forty-second International Conference on Machine Learning, 2025

A Quantitative Metric Selection Approach for Time-series Forecasting Foundation Models.

Hongjie Chen, Akshay Mehra, Josh Kimball, Sungchul Kim

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

2024

Antidote: Post-fine-tuning Safety Alignment for Large Language Models against Harmful Fine-tuning.

Tiansheng Huang, Gautam Bhattacharya, Pratik Joshi, Josh Kimball, Ling Liu

CoRR, 2024

LIVE-ITS: LSH-based Interactive Visualization Explorer for Large-Scale Incomplete Time Series.

Hongjie Chen, Aaron D. Beachnau, Panos Thomas, Pranav Maneriker, Josh Kimball, Ryan A. Rossi

Proceedings of the IEEE International Conference on Big Data, 2024

2021

PerfDB + PerlML: Enabling Big Data-Driven Research On Fine-Grained Performance Phenomena.

Joshua Kimball

PhD thesis, 2021

A Functional Model and Analysis of Next Generation Malware Attacks and Defenses.

Calton Pu, Qingyang Wang, Yasuhiko Kanemasa, Rodrigo Alves Lima, Joshua Kimball, Shungeng Zhang, Jianshu Liu, Xuhang Gu

Proceedings of the 3rd IEEE International Conference on Trust, 2021

PerfML: Smart Management of Complex Performance Data and Analytics.

Joshua Kimball, Rodrigo Alves Lima, Abhijit Suprem, Qingyang Wang, Yasuhiko Kanemasa, Calton Pu

Proceedings of the Third IEEE International Conference on Cognitive Machine Intelligence, 2021

2020

Finding Performance Patterns from Logs with High Confidence.

Joshua Kimball, Rodrigo Alves Lima, Calton Pu

Proceedings of the Web Services - ICWS 2020, 2020

PerfDB: A Data Management System for Fine-Grained Performance Anomaly Detection.

Joshua Kimball, Rodrigo Alves Lima, Yasuhiko Kanemasa, Calton Pu

Proceedings of the 6th IEEE International Conference on Collaboration and Internet Computing, 2020

Wise Toolkit: Enabling Microservice-Based System Performance Experiments.

Rodrigo Alves Lima, Joshua Kimball, João Eduardo Ferreira, Calton Pu

Proceedings of the Cloud Computing - CLOUD 2020, 2020

2019

Systematic Construction, Execution, and Reproduction of Complex Performance Benchmarks.

Rodrigo Alves Lima, Joshua Kimball, João Eduardo Ferreira, Calton Pu

Proceedings of the Cloud Computing - CLOUD 2019, 2019

A Method and Tool for Automated Induction of Relations from Quantitative Performance Logs.

Joshua Kimball, Calton Pu

Proceedings of the Cloud Computing - CLOUD 2019, 2019

2017

Limitations of Load Balancing Mechanisms for N-Tier Systems in the Presence of Millibottlenecks.

Tao Zhu, Jack Li, Josh Kimball, Junhee Park, Chien-An Lai, Calton Pu, Qingyang Wang

Proceedings of the 37th IEEE International Conference on Distributed Computing Systems, 2017

The Millibottleneck Theory of Performance Bugs, and Its Experimental Verification.

Calton Pu, Joshua Kimball, Chien-An Lai, Tao Zhu, Jack Li, Junhee Park, Qingyang Wang, Deepal Jayasinghe, PengCheng Xiong, Simon Malkowski, Qinyi Wu, Gueyoung Jung, Younggyun Koh, Galen S. Swint

Proceedings of the 37th IEEE International Conference on Distributed Computing Systems, 2017

milliScope: A Fine-Grained Monitoring Framework for Performance Debugging of n-Tier Web Services.

Chien-An Lai, Josh Kimball, Tao Zhu, Qingyang Wang, Calton Pu

Proceedings of the 37th IEEE International Conference on Distributed Computing Systems, 2017

2014

IO Performance Interference among Consolidated n-Tier Applications: Sharing Is Better Than Isolation for Disks.

Chien-An Lai, Qingyang Wang, Josh Kimball, Jack Li, Junhee Park, Calton Pu

Proceedings of the 2014 IEEE 7th International Conference on Cloud Computing, Anchorage, AK, USA, June 27, 2014

2013

An automated approach to create, store, and analyze large-scale experimental data in clouds.

Deepal Jayasinghe, Josh Kimball, Siddharth Choudhary, Tao Zhu, Calton Pu

Proceedings of the IEEE 14th International Conference on Information Reuse & Integration, 2013

An infrastructure for automating large-scale performance studies and data processing.

Deepal Jayasinghe, Josh Kimball, Tao Zhu, Siddharth Choudhary, Calton Pu

Proceedings of the 2013 IEEE International Conference on Big Data (IEEE BigData 2013), 2013