A Novel Index Supporting High Volume Data Warehouse Insertion. - Chris Jermaine; Anindya Datta; Edward Omiecinski (VLDB, 1999)

Computing Program Modularizations Using the k-Cut Method. - Chris Jermaine (WCRE, 1999)

Approximate Query Answering in High-Dimensional Data Cubes. - Chris Jermaine; Renée J. Miller (ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, 2000)

Maintaining a Large Spatial Database with T2SM. - Chris Jermaine; Edward Omiecinski; Wai Gen Yee (ACM-GIS, 2001)

The Computational Complexity of High-Dimensional Correlation Search. - Chris Jermaine (ICDM, 2001)

Bridging the Gap between Response Time and Energy-Efficiency in Broadcast Schedule Design. - Wai Gen Yee; Shamkant B. Navathe; Edward Omiecinski; Chris Jermaine (EDBT, 2002)

Lossy Reduction for Very High Dimensional Data. - Chris Jermaine; Edward Omiecinski (ICDE, 2002)

Out From Under the Trees. - Chris Jermaine; Edward Omiecinski; Wai Gen Yee (ICDE, 2002)

Efficient Data Allocation over Multiple Channels at Broadcast Servers. - Wai Gen Yee; Shamkant B. Navathe; Edward Omiecinski; Chris Jermaine (IEEE Trans. Computers, 2002)

Playing hide-and-seek with correlations. - Chris Jermaine (KDD, 2003)

Robust Estimation With Sampling and Approximate Pre-Aggregation. - Chris Jermaine (VLDB, 2003)

Online Maintenance of Very Large Random Samples. - Chris Jermaine; Abhijit Pol; Subramanian Arumugam 002 (SIGMOD Conference, 2004)

A Disk-Based Join With Probabilistic Guarantees. - Chris Jermaine; Alin Dobra; Subramanian Arumugam 002; Shantanu Joshi 001; Abhijit Pol (SIGMOD Conference, 2005)

Relational Confidence Bounds Are Easy With The Bootstrap. - Abhijit Pol; Chris Jermaine (SIGMOD Conference, 2005)

Online Estimation For Subset-Based SQL Queries. - Chris Jermaine; Alin Dobra; Abhijit Pol; Shantanu Joshi 001 (VLDB, 2005)

Finding the most interesting correlations in a database: how hard can it be?. - Chris Jermaine (Inf. Syst., 2005)

Closest-Point-of-Approach Join for Moving Object Histories. - Subramanian Arumugam 002; Chris Jermaine (ICDE, 2006)

New Sampling-Based Estimators for OLAP Queries. - Ruoming Jin; Leonid Glimcher; Chris Jermaine; Gagan Agrawal (ICDE, 2006)

Outlier detection by sampling with accuracy guarantees. - Mingxi Wu; Chris Jermaine (KDD, 2006)

Reference-based Indexing of Sequence Databases. - Jayendra Venkateswaran; Deepak Lachwani; Tamer Kahveci; Christopher M. Jermaine (VLDB, 2006)

The Sort-Merge-Shrink join. - Chris Jermaine; Alin Dobra; Subramanian Arumugam 002; Shantanu Joshi 001; Abhijit Pol (ACM Trans. Database Syst., 2006)

Statistical change detection for multi-dimensional data. - Xiuyao Song; Mingxi Wu; Christopher M. Jermaine; Sanjay Ranka (KDD, 2007)

A Bayesian Method for Guessing the Extreme Values in a Data Set. - Mingxi Wu; Chris Jermaine (VLDB, 2007)

Randomized Algorithms for Data Reconciliation in Wide Area Aggregate Query Processing. - Fei Xu; Chris Jermaine (VLDB, 2007)

Online Random Shuffling of Large Database Tables. - Christopher M. Jermaine (IEEE Trans. Knowl. Data Eng., 2007)

Conditional Anomaly Detection. - Xiuyao Song; Mingxi Wu; Christopher M. Jermaine; Sanjay Ranka (IEEE Trans. Knowl. Data Eng., 2007)

The partitioned exponential file for database storage management. - Christopher M. Jermaine; Edward Omiecinski; Wai Gen Yee (VLDB J., 2007)

Robust Stratified Sampling Plans for Low Selectivity Queries. - Shantanu Joshi 001; Christopher M. Jermaine (ICDE, 2008)

A bayesian mixture model with linear regression mixing proportions. - Xiuyao Song; Chris Jermaine; Sanjay Ranka; John Gums (KDD, 2008)

MCDB: a monte carlo approach to managing uncertain data. - Ravi Jampani; Fei Xu; Mingxi Wu; Luis Leopoldo Perez; Christopher M. Jermaine; Peter J. Haas (SIGMOD Conference, 2008)

The DBO database system. - Florin Rusu; Fei Xu; Luis Leopoldo Perez; Mingxi Wu; Ravi Jampani; Chris Jermaine; Alin Dobra (SIGMOD Conference, 2008)

Learning correlations using the mixture-of-subsets model. - Manas Somaiya; Christopher M. Jermaine; Sanjay Ranka (ACM Trans. Knowl. Discov. Data, 2008)

Materialized Sample Views for Database Approximation. - Shantanu Joshi 001; Christopher M. Jermaine (IEEE Trans. Knowl. Data Eng., 2008)

Scalable approximate query processing with the DBO engine. - Chris Jermaine; Subramanian Arumugam 002; Abhijit Pol; Alin Dobra (ACM Trans. Database Syst., 2008)

Confidence bounds for sampling-based group by estimates. - Fei Xu; Christopher M. Jermaine; Alin Dobra (ACM Trans. Database Syst., 2008)

Maintaining very large random samples using the geometric file. - Abhijit Pol; Christopher M. Jermaine; Subramanian Arumugam 002 (VLDB J., 2008)

Reference-based indexing for metric spaces with costly distance measures. - Jayendra Venkateswaran; Tamer Kahveci; Christopher M. Jermaine; Deepak Lachwani (VLDB J., 2008)

A LRT framework for fast spatial anomaly detection. - Mingxi Wu; Xiuyao Song; Chris Jermaine; Sanjay Ranka; John Gums (KDD, 2009)

Turbo-Charging Estimate Convergence in DBO. - Alin Dobra; Chris Jermaine; Florin Rusu; Fei Xu (Proc. VLDB Endow., 2009)

Sampling-based estimators for subset-based queries. - Shantanu Joshi 001; Christopher M. Jermaine (VLDB J., 2009)

Guessing the extreme values in a data set: a Bayesian method and its applications. - Mingxi Wu; Chris Jermaine (VLDB J., 2009)

Surrogate ranking for very expensive similarity queries. - Fei Xu; Ravi Jampani; Mingxi Wu; Chris Jermaine; Tamer Kahveci (ICDE, 2010)

Mixture models for learning low-dimensional roles in high-dimensional data. - Manas Somaiya; Christopher M. Jermaine; Sanjay Ranka (KDD, 2010)

The DataPath system: a data-centric analytic processing engine for large data warehouses. - Subi Arumugam; Alin Dobra; Christopher M. Jermaine; Niketan Pansare; Luis Leopoldo Perez (SIGMOD Conference, 2010)

Evaluation of probabilistic threshold queries in MCDB. - Luis Leopoldo Perez; Subi Arumugam; Christopher M. Jermaine (SIGMOD Conference, 2010)

MCDB-R: Risk Analysis in the Database. - Subi Arumugam; Ravi Jampani; Luis Leopoldo Perez; Fei Xu; Christopher M. Jermaine; Peter J. Haas (Proc. VLDB Endow., 2010)

A Model-Agnostic Framework for Fast Spatial Anomaly Detection. - Mingxi Wu; Chris Jermaine; Sanjay Ranka; Xiuyao Song; John Gums (ACM Trans. Knowl. Discov. Data, 2010)

Online Aggregation for Large MapReduce Jobs. - Niketan Pansare; Vinayak R. Borkar; Chris Jermaine; Tyson Condie (Proc. VLDB Endow., 2011)

TRIAL: A Tool for Finding Distant Structural Similarities. - Jayendra Venkateswaran; Bin Song 009; Tamer Kahveci; Chris Jermaine (IEEE ACM Trans. Comput. Biol. Bioinform., 2011)

The monte carlo database system: Stochastic analysis close to the data. - Ravi Jampani; Fei Xu; Mingxi Wu; Luis Leopoldo Perez; Chris Jermaine; Peter J. Haas (ACM Trans. Database Syst., 2011)

Topic Models over Spoken Language. - Niketan Pansare; Chris Jermaine; Peter J. Haas; Nitendra Rajput (ICDM, 2012)

The Latent Community Model for Detecting Sybils in Social Networks. - Zhuhua Cai; Chris Jermaine (NDSS, 2012)

Synopses for Massive Data: Samples, Histograms, Wavelets, Sketches. - Graham Cormode; Minos N. Garofalakis; Peter J. Haas; Chris Jermaine (Found. Trends Databases, 2012)

The Pairwise Gaussian Random Field for High-Dimensional Data Imputation. - Zhuhua Cai; Christopher M. Jermaine; Zografoula Vagena; Dionysios Logothetis; Luis Leopoldo Perez (ICDM, 2013)

Topic Models For Feature Selection in Document Clustering. - Anna Drummond; Chris Jermaine; Zografoula Vagena (SDM, 2013)

Simulation of database-valued markov chains using SimSQL. - Zhuhua Cai; Zografoula Vagena; Luis Leopoldo Perez; Subramanian Arumugam 002; Peter J. Haas; Christopher M. Jermaine (SIGMOD Conference, 2013)

Multiclass domain adaptation with iterative manifold alignment. - Brian D. Bue; Chris Jermaine (WHISPERS, 2013)

A Sampling Algebra for Aggregate Estimation. - Supriya Nirkhiwale; Alin Dobra; Christopher M. Jermaine (Proc. VLDB Endow., 2013)

History-aware query optimization with materialized intermediate views. - Luis Leopoldo Perez; Christopher M. Jermaine (ICDE, 2014)

Senders, Receivers and Authors in Document Classification. - Anna Drummond; Christopher M. Jermaine (ICDM, 2014)

Learning to Grade Student Programs in a Massive Open Online Course. - Anna Drummond; Yanxin Lu; Swarat Chaudhuri; Christopher M. Jermaine; Joe Warren; Scott Rixner (ICDM, 2014)

A comparison of platforms for implementing and running very large scale machine learning algorithms. - Zhuhua Cai; Zekai J. Gao; Shangyu Luo; Luis Leopoldo Perez; Zografoula Vagena; Christopher M. Jermaine (SIGMOD Conference, 2014)

Correlating Surgical Vital Sign Quality with 30-Day Outcomes using Regression on Time Series Segment Features. - Risa B. Myers; John C. Frenzel; Joseph R. Ruiz; Christopher M. Jermaine (SDM, 2015)

Grading the Graders: Motivating Peer Graders in a MOOC. - Yanxin Lu; Joe Warren; Christopher M. Jermaine; Swarat Chaudhuri; Scott Rixner (WWW, 2015)

Letter from the Special Issue Editor. - Chris Jermaine (IEEE Data Eng. Bull., 2015)

Guest editorial: Special section on the international conference on data engineering. - Christian S. Jensen; Christopher M. Jermaine; Xiaofang Zhou 001 (IEEE Trans. Knowl. Data Eng., 2015)

Workload-Driven Antijoin Cardinality Estimation. - Florin Rusu; Zixuan Zhuang; Mingxi Wu; Chris Jermaine (ACM Trans. Database Syst., 2015)

Distributed Algorithms for Computing Very Large Thresholded Covariance Matrices. - Zekai J. Gao; Chris Jermaine (ACM Trans. Knowl. Discov. Data, 2016)

Do Anesthesiologists Know What They Are Doing? Mining a Surgical Time-Series Database to Correlate Expert Assessment with Outcomes. - Risa B. Myers; John C. Frenzel; Joseph R. Ruiz; Christopher M. Jermaine (ACM Trans. Knowl. Discov. Data, 2016)

An experimental comparison of complex object implementations for big data systems. - Sourav Sikdar; Kia Teymourian; Chris Jermaine (SoCC, 2017)

Real-time High Performance Anomaly Detection over Data Streams: Grand Challenge. - Dimitrije Jankov; Sourav Sikdar; Rohan Mukherjee 001; Kia Teymourian; Chris Jermaine (DEBS, 2017)

The BUDS Language for Distributed Bayesian Machine Learning. - Zekai J. Gao; Shangyu Luo; Luis Leopoldo Perez; Chris Jermaine (SIGMOD Conference, 2017)

Bayesian specification learning for finding API usage errors. - Vijayaraghavan Murali; Swarat Chaudhuri; Chris Jermaine (ESEC/SIGSOFT FSE, 2017)

Data-Driven Program Completion. - Yanxin Lu; Swarat Chaudhuri; Chris Jermaine; David Melski (CoRR, 2017)

Finding Likely Errors with Bayesian Specifications. - Vijayaraghavan Murali; Swarat Chaudhuri; Chris Jermaine (CoRR, 2017)

Bayesian Sketch Learning for Program Synthesis. - Vijayaraghavan Murali; Swarat Chaudhuri; Chris Jermaine (CoRR, 2017)

Abridging source code. - Binhang Yuan; Vijayaraghavan Murali; Christopher M. Jermaine (Proc. ACM Program. Lang., 2017)

Parallel and Distributed MCMC via Shepherding Distributions. - Arkabandhu Chowdhury; Christopher M. Jermaine (AISTATS, 2018)

Neural Sketch Learning for Conditional Program Generation. - Vijayaraghavan Murali; Letao Qi; Swarat Chaudhuri; Chris Jermaine (ICLR, 2018)

Program splicing. - Yanxin Lu; Swarat Chaudhuri; Chris Jermaine; David Melski (ICSE, 2018)

PlinyCompute: A Platform for High-Performance, Distributed, Data-Intensive Tool Development. - Jia Zou 001; R. Matthew Barnett; Tania Lorido-Botran; Shangyu Luo; Carlos Monroy; Sourav Sikdar; Kia Teymourian; Binhang Yuan; Chris Jermaine (SIGMOD Conference, 2018)

Scalable Linear Algebra on a Relational Database System. - Shangyu Luo; Zekai J. Gao; Michael N. Gubanov; Luis Leopoldo Perez; Christopher M. Jermaine (SIGMOD Rec., 2018)

Distributed Learning of Deep Neural Networks using Independent Subnet Training. - Binhang Yuan; Anastasios Kyrillidis; Christopher M. Jermaine (CoRR, 2019)

Declarative Recursive Computation on an RDBMS. - Dimitrije Jankov; Shangyu Luo; Binhang Yuan; Zhuhua Cai; Jia Zou 001; Chris Jermaine; Zekai J. Gao (Proc. VLDB Endow., 2019)

Pangea: Monolithic Distributed Storage for Data Analytics. - Jia Zou 001; Arun Iyengar; Chris Jermaine (Proc. VLDB Endow., 2019)

Declarative Parameterizations of User-Defined Functions for Large-Scale Machine Learning and Optimization. - Zekai J. Gao; Niketan Pansare; Christopher M. Jermaine (IEEE Trans. Knowl. Data Eng., 2019)

MONSOON: Multi-Step Optimization and Execution of Queries with Partially Obscured Predicates. - Sourav Sikdar; Chris Jermaine (SIGMOD Conference, 2020)

Scalable linear algebra on a relational database system. - Shangyu Luo; Zekai J. Gao; Michael N. Gubanov; Luis Leopoldo Perez; Dimitrije Jankov; Christopher M. Jermaine (Commun. ACM, 2020)

Workshop on Quantification, Communication, and Interpretation of Uncertainty in Simulation and Data Science. - Ross T. Whitaker; William B. Thompson; James Berger; Baruch Fischhof; Michael F. Goodchild; Mary Hegarty; Christopher M. Jermaine; Kathryn S. McKinley; Alex Pang; Joanne Wendelberger (CoRR, 2020)

Lachesis: Automated Generation of Persistent Partitionings for Big Data Applications. - Jia Zou 001; Pratik Barhate; Amitabh Das; Arun Iyengar; Binhang Yuan; Dimitrije Jankov; Chris Jermaine (CoRR, 2020)

Tensor Relational Algebra for Machine Learning System Design. - Binhang Yuan; Dimitrije Jankov; Jia Zou 001; Yuxin Tang; Daniel Bourgeois; Chris Jermaine (CoRR, 2020)

Searching a Database of Source Codes Using Contextualized Code Search. - Rohan Mukherjee 001; Chris Jermaine; Swarat Chaudhuri (Proc. VLDB Endow., 2020)

Declarative Recursive Computation on an RDBMS: or, Why You Should Use a Database For Distributed Machine Learning. - Dimitrije Jankov; Shangyu Luo; Binhang Yuan; Zhuhua Cai; Jia Zou 001; Chris Jermaine; Zekai J. Gao (SIGMOD Rec., 2020)

Editorial. - Chris Jermaine (ACM Trans. Database Syst., 2020)

Architecture of a distributed storage that combines file system, memory and computation in a single layer. - Jia Zou 001; Arun Iyengar; Chris Jermaine (VLDB J., 2020)

Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple Classifier. - Arkabandhu Chowdhury; Mingchao Jiang; Swarat Chaudhuri; Chris Jermaine (ICCV, 2021)

Neural Program Generation Modulo Static Analysis. - Rohan Mukherjee 001; Yeming Wen; Dipak Chaudhari; Thomas W. Reps; Swarat Chaudhuri; Christopher M. Jermaine (NeurIPS, 2021)

Automatic Optimization of Matrix Implementations for Distributed Machine Learning and Linear Algebra. - Shangyu Luo; Dimitrije Jankov; Binhang Yuan; Chris Jermaine (SIGMOD Conference, 2021)

The Tensor-Relational Algebra, and Other Ideas in Machine Learning System Design. - Chris Jermaine (SSDBM, 2021)

Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple Classifier. - Arkabandhu Chowdhury; Mingchao Jiang; Chris Jermaine (CoRR, 2021)

Distributed Numerical and Machine Learning Computations via Two-Phase Execution of Aggregated Join Trees. - Dimitrije Jankov; Binhang Yuan; Shangyu Luo; Chris Jermaine (Proc. VLDB Endow., 2021)

Tensor Relational Algebra for Distributed Machine Learning System Design. - Binhang Yuan; Dimitrije Jankov; Jia Zou 001; Yuxin Tang; Daniel Bourgeois; Chris Jermaine (Proc. VLDB Endow., 2021)

Lachesis: Automated Partitioning for UDF-Centric Analytics. - Jia Zou 001; Amitabh Das; Pratik Barhate; Arun Iyengar; Binhang Yuan; Dimitrije Jankov; Chris Jermaine (Proc. VLDB Endow., 2021)

ResIST: Layer-wise decomposition of ResNets for distributed training. - Chen Dun; Cameron R. Wolfe; Christopher M. Jermaine; Anastasios Kyrillidis (UAI, 2022)

Meta-Meta Classification for One-Shot Learning. - Arkabandhu Chowdhury; Dipak Chaudhari; Swarat Chaudhuri; Chris Jermaine (WACV, 2022)

Distributed Learning of Fully Connected Neural Networks using Independent Subnet Training. - Binhang Yuan; Cameron R. Wolfe; Chen Dun; Yuxin Tang; Anastasios Kyrillidis; Chris Jermaine (Proc. VLDB Endow., 2022)

Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout. - Chen Dun; Mirian Hipolito Garcia; Chris Jermaine; Dimitrios Dimitriadis; Anastasios Kyrillidis (AISTATS, 2023)

LOFT: Finding Lottery Tickets through Filter-wise Training. - Qihan Wang; Chen Dun; Fangshuo Liao; Chris Jermaine; Anastasios Kyrillidis (AISTATS, 2023)

Federated Learning Over Images: Vertical Decompositions and Pre-Trained Backbones Are Difficult to Beat. - Erdong Hu; Yuxin Tang; Anastasios Kyrillidis; Chris Jermaine (ICCV, 2023)

Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning. - Yuxin Tang; Zhimin Ding; Dimitrije Jankov; Binhang Yuan; Daniel Bourgeois; Chris Jermaine (ICML, 2023)

Optimizing Tensor Computations: From Applications to Compilation and Runtime Techniques. - Matthias Boehm 001; Matteo Interlandi; Chris Jermaine (SIGMOD Conference Companion, 2023)

Tuning Models of Code with Compiler-Generated Reinforcement Learning Feedback. - Abhinav Jain 001; Chima Adiole; Swarat Chaudhuri; Thomas W. Reps; Chris Jermaine (CoRR, 2023)

Online Cascade Learning for Efficient Inference over Streams. - Lunyiu Nie; Zhimin Ding; Erdong Hu; Christopher M. Jermaine; Swarat Chaudhuri (ICML, 2024)

Prompt Tuning Strikes Back: Customizing Foundation Models with Low-Rank Prompt Adaptation. - Abhinav Jain 001; Swarat Chaudhuri; Thomas W. Reps; Christopher M. Jermaine (NeurIPS, 2024)

TURNIP: A "Nondeterministic" GPU Runtime with CPU RAM Offload. - Zhimin Ding; Jiawen Yao; Brianna Barrow; Tania Lorido-Botran; Christopher M. Jermaine; Yuxin Tang; Jiehui Li; Xinyu Yao; Sleem Mahmoud Abdelghafar; Daniel Bourgeois (CoRR, 2024)

RAG-Modulo: Solving Sequential Tasks using Experience, Critics, and Language Models. - Abhinav Jain 001; Chris Jermaine; Vaibhav V. Unhelkar (CoRR, 2024)

EinDecomp: Decomposition of Declaratively-Specified Machine Learning and Numerical Computations for Parallel Execution. - Daniel Bourgeois; Zhimin Ding; Dimitrije Jankov; Jiehui Li; Sleem Mahmoud Abdelghafar; Yuxin Tang; Jiawen Yao; Xinyu Yao; Chris Jermaine (Proc. VLDB Endow., 2025)

Resource-efficient Inference with Foundation Model Programs. - Lunyiu Nie; Zhimin Ding; Kevin Yu; Marco Cheung; Chris Jermaine; Swarat Chaudhuri (CoRR, 2025)

SIMCOPILOT: Evaluating Large Language Models for Copilot-Style Code Generation. - Mingchao Jiang; Abhinav Jain 001; Sophia Zorek; Chris Jermaine (CoRR, 2025)

DOPPLER: Dual-Policy Learning for Device Assignment in Asynchronous Dataflow Graphs. - Xinyu Yao; Daniel Bourgeois; Abhinav Jain 001; Yuxin Tang; Jiawen Yao; Zhimin Ding; Arlei Silva; Chris Jermaine (CoRR, 2025)