Chris Jermaine

Orcid: 0009-0001-5458-9370

Affiliations:
  • Rice University, Houston, USA


According to our database1, Chris Jermaine authored at least 113 papers between 1999 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Online Cascade Learning for Efficient Inference over Streams.
CoRR, 2024

2023
Tuning Models of Code with Compiler-Generated Reinforcement Learning Feedback.
CoRR, 2023

Optimizing Tensor Computations: From Applications to Compilation and Runtime Techniques.
Proceedings of the Companion of the 2023 International Conference on Management of Data, 2023

Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning.
Proceedings of the International Conference on Machine Learning, 2023

Federated Learning Over Images: Vertical Decompositions and Pre-Trained Backbones Are Difficult to Beat.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

LOFT: Finding Lottery Tickets through Filter-wise Training.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Distributed Learning of Fully Connected Neural Networks using Independent Subnet Training.
Proc. VLDB Endow., 2022

Meta-Meta Classification for One-Shot Learning.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

ResIST: Layer-wise decomposition of ResNets for distributed training.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021
Lachesis: Automated Partitioning for UDF-Centric Analytics.
Proc. VLDB Endow., 2021

Tensor Relational Algebra for Distributed Machine Learning System Design.
Proc. VLDB Endow., 2021

Distributed Numerical and Machine Learning Computations via Two-Phase Execution of Aggregated Join Trees.
Proc. VLDB Endow., 2021

Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple Classifier.
CoRR, 2021

The Tensor-Relational Algebra, and Other Ideas in Machine Learning System Design.
Proceedings of the SSDBM 2021: 33rd International Conference on Scientific and Statistical Database Management, 2021

Automatic Optimization of Matrix Implementations for Distributed Machine Learning and Linear Algebra.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Neural Program Generation Modulo Static Analysis.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple Classifier.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Architecture of a distributed storage that combines file system, memory and computation in a single layer.
VLDB J., 2020

Editorial.
ACM Trans. Database Syst., 2020

Declarative Recursive Computation on an RDBMS: or, Why You Should Use a Database For Distributed Machine Learning.
SIGMOD Rec., 2020

Searching a Database of Source Codes Using Contextualized Code Search.
Proc. VLDB Endow., 2020

Tensor Relational Algebra for Machine Learning System Design.
CoRR, 2020

Lachesis: Automated Generation of Persistent Partitionings for Big Data Applications.
CoRR, 2020

Workshop on Quantification, Communication, and Interpretation of Uncertainty in Simulation and Data Science.
CoRR, 2020

Scalable linear algebra on a relational database system.
Commun. ACM, 2020

MONSOON: Multi-Step Optimization and Execution of Queries with Partially Obscured Predicates.
Proceedings of the 2020 International Conference on Management of Data, 2020

2019
Declarative Parameterizations of User-Defined Functions for Large-Scale Machine Learning and Optimization.
IEEE Trans. Knowl. Data Eng., 2019

Pangea: Monolithic Distributed Storage for Data Analytics.
Proc. VLDB Endow., 2019

Declarative Recursive Computation on an RDBMS.
Proc. VLDB Endow., 2019

Distributed Learning of Deep Neural Networks using Independent Subnet Training.
CoRR, 2019

2018
Scalable Linear Algebra on a Relational Database System.
SIGMOD Rec., 2018

PlinyCompute: A Platform for High-Performance, Distributed, Data-Intensive Tool Development.
Proceedings of the 2018 International Conference on Management of Data, 2018

Program splicing.
Proceedings of the 40th International Conference on Software Engineering, 2018

Neural Sketch Learning for Conditional Program Generation.
Proceedings of the 6th International Conference on Learning Representations, 2018

Parallel and Distributed MCMC via Shepherding Distributions.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Abridging source code.
Proc. ACM Program. Lang., 2017

Bayesian Sketch Learning for Program Synthesis.
CoRR, 2017

Finding Likely Errors with Bayesian Specifications.
CoRR, 2017

Data-Driven Program Completion.
CoRR, 2017

Bayesian specification learning for finding API usage errors.
Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering, 2017

The BUDS Language for Distributed Bayesian Machine Learning.
Proceedings of the 2017 ACM International Conference on Management of Data, 2017

Real-time High Performance Anomaly Detection over Data Streams: Grand Challenge.
Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems, 2017

An experimental comparison of complex object implementations for big data systems.
Proceedings of the 2017 Symposium on Cloud Computing, SoCC 2017, Santa Clara, CA, USA, 2017

2016
Do Anesthesiologists Know What They Are Doing? Mining a Surgical Time-Series Database to Correlate Expert Assessment with Outcomes.
ACM Trans. Knowl. Discov. Data, 2016

Distributed Algorithms for Computing Very Large Thresholded Covariance Matrices.
ACM Trans. Knowl. Discov. Data, 2016

2015
Workload-Driven Antijoin Cardinality Estimation.
ACM Trans. Database Syst., 2015

Guest editorial: Special section on the international conference on data engineering.
IEEE Trans. Knowl. Data Eng., 2015

Letter from the Special Issue Editor.
IEEE Data Eng. Bull., 2015

Grading the Graders: Motivating Peer Graders in a MOOC.
Proceedings of the 24th International Conference on World Wide Web, 2015

Correlating Surgical Vital Sign Quality with 30-Day Outcomes using Regression on Time Series Segment Features.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

2014
A comparison of platforms for implementing and running very large scale machine learning algorithms.
Proceedings of the International Conference on Management of Data, 2014

Learning to Grade Student Programs in a Massive Open Online Course.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Senders, Receivers and Authors in Document Classification.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

History-aware query optimization with materialized intermediate views.
Proceedings of the IEEE 30th International Conference on Data Engineering, Chicago, 2014

2013
A Sampling Algebra for Aggregate Estimation.
Proc. VLDB Endow., 2013

Multiclass domain adaptation with iterative manifold alignment.
Proceedings of the 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2013

Simulation of database-valued markov chains using SimSQL.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2013

Topic Models For Feature Selection in Document Clustering.
Proceedings of the 13th SIAM International Conference on Data Mining, 2013

The Pairwise Gaussian Random Field for High-Dimensional Data Imputation.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012
Synopses for Massive Data: Samples, Histograms, Wavelets, Sketches.
Found. Trends Databases, 2012

The Latent Community Model for Detecting Sybils in Social Networks.
Proceedings of the 19th Annual Network and Distributed System Security Symposium, 2012

Topic Models over Spoken Language.
Proceedings of the 12th IEEE International Conference on Data Mining, 2012

2011
The monte carlo database system: Stochastic analysis close to the data.
ACM Trans. Database Syst., 2011

TRIAL: A Tool for Finding Distant Structural Similarities.
IEEE ACM Trans. Comput. Biol. Bioinform., 2011

Online Aggregation for Large MapReduce Jobs.
Proc. VLDB Endow., 2011

2010
A Model-Agnostic Framework for Fast Spatial Anomaly Detection.
ACM Trans. Knowl. Discov. Data, 2010

MCDB-R: Risk Analysis in the Database.
Proc. VLDB Endow., 2010

Evaluation of probabilistic threshold queries in MCDB.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2010

The DataPath system: a data-centric analytic processing engine for large data warehouses.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2010

Mixture models for learning low-dimensional roles in high-dimensional data.
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

Surrogate ranking for very expensive similarity queries.
Proceedings of the 26th International Conference on Data Engineering, 2010

2009
Guessing the extreme values in a data set: a Bayesian method and its applications.
VLDB J., 2009

Sampling-based estimators for subset-based queries.
VLDB J., 2009

Turbo-Charging Estimate Convergence in DBO.
Proc. VLDB Endow., 2009

A LRT framework for fast spatial anomaly detection.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

2008
Reference-based indexing for metric spaces with costly distance measures.
VLDB J., 2008

Maintaining very large random samples using the geometric file.
VLDB J., 2008

Confidence bounds for sampling-based group by estimates.
ACM Trans. Database Syst., 2008

Scalable approximate query processing with the DBO engine.
ACM Trans. Database Syst., 2008

Materialized Sample Views for Database Approximation.
IEEE Trans. Knowl. Data Eng., 2008

Learning correlations using the mixture-of-subsets model.
ACM Trans. Knowl. Discov. Data, 2008

The DBO database system.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2008

MCDB: a monte carlo approach to managing uncertain data.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2008

A bayesian mixture model with linear regression mixing proportions.
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

Robust Stratified Sampling Plans for Low Selectivity Queries.
Proceedings of the 24th International Conference on Data Engineering, 2008

2007
The partitioned exponential file for database storage management.
VLDB J., 2007

Conditional Anomaly Detection.
IEEE Trans. Knowl. Data Eng., 2007

Online Random Shuffling of Large Database Tables.
IEEE Trans. Knowl. Data Eng., 2007

Randomized Algorithms for Data Reconciliation in Wide Area Aggregate Query Processing.
Proceedings of the 33rd International Conference on Very Large Data Bases, 2007

A Bayesian Method for Guessing the Extreme Values in a Data Set.
Proceedings of the 33rd International Conference on Very Large Data Bases, 2007

Statistical change detection for multi-dimensional data.
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

2006
The Sort-Merge-Shrink join.
ACM Trans. Database Syst., 2006

Reference-based Indexing of Sequence Databases.
Proceedings of the 32nd International Conference on Very Large Data Bases, 2006

Outlier detection by sampling with accuracy guarantees.
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006

New Sampling-Based Estimators for OLAP Queries.
Proceedings of the 22nd International Conference on Data Engineering, 2006

Closest-Point-of-Approach Join for Moving Object Histories.
Proceedings of the 22nd International Conference on Data Engineering, 2006

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

Online Estimation For Subset-Based SQL Queries.
Proceedings of the 31st International Conference on Very Large Data Bases, Trondheim, Norway, August 30, 2005

Relational Confidence Bounds Are Easy With The Bootstrap.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2005

A Disk-Based Join With Probabilistic Guarantees.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2005

2004
Online Maintenance of Very Large Random Samples.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2004

2003
Robust Estimation With Sampling and Approximate Pre-Aggregation.
Proceedings of 29th International Conference on Very Large Data Bases, 2003

Playing hide-and-seek with correlations.
Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 24, 2003

2002
Efficient Data Allocation over Multiple Channels at Broadcast Servers.
IEEE Trans. Computers, 2002

Out From Under the Trees.
Proceedings of the 18th International Conference on Data Engineering, San Jose, CA, USA, February 26, 2002

Lossy Reduction for Very High Dimensional Data.
Proceedings of the 18th International Conference on Data Engineering, San Jose, CA, USA, February 26, 2002

Bridging the Gap between Response Time and Energy-Efficiency in Broadcast Schedule Design.
Proceedings of the Advances in Database Technology, 2002

2001
The Computational Complexity of High-Dimensional Correlation Search.
Proceedings of the 2001 IEEE International Conference on Data Mining, 29 November, 2001

Maintaining a Large Spatial Database with T2SM.
Proceedings of the ACM-GIS 2001, 2001

2000
Approximate Query Answering in High-Dimensional Data Cubes.
Proceedings of the 2000 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, 2000

1999
Computing Program Modularizations Using the k-Cut Method.
Proceedings of the Sixth Working Conference on Reverse Engineering, 1999

A Novel Index Supporting High Volume Data Warehouse Insertion.
Proceedings of the VLDB'99, 1999


  Loading...