Eric Bax

According to our database, Eric Bax authored at least 42 papers between 1998 and 2024.

Collaborative distances:

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

2024

Key Compression Limits for <i>k</i>-Minimum Value Sketches.

Charlie Dickens, Eric Bax, Alexander Saydakov

CoRR, 2024

Continuous Monitoring via Repeated Significance.

Eric Bax, Arundhyoti Sarkar, Alex Shtoff

CoRR, 2024

Early Stopping Based on Repeated Significance.

Eric Bax, Arundhyoti Sarkar, Alex Shtoff

CoRR, 2024

Pre- and Post-Auction Discounts in First-Price Auctions.

Miguel Alcobendas, Eric Bax

CoRR, 2024

2023

Generative AI: Citations for Trust and Consensus.

Eric Bax, Melissa Gerber, Lisa Giaffo, Arundhyoti Sarkar, Nikki Thompson, Will Wagner, Kimberly Williams

Proceedings of the Future Technologies Conference, 2023

Matching Noisy Keys for Obfuscation.

Charlie Dickens, Eric Bax

Proceedings of the IEEE International Conference on Big Data, 2023

2022

Multiple Statistics: Marking Significance.

Eric Bax, Arundhyoti Sarkar, Natalie Bax

Proceedings of the IEEE International Conference on Big Data, 2022

Even Large Samples Have Challenges: Rare Events, Gaps, and Tails.

Eric Bax, Charlotte Bax

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Selecting a number of voters for a voting ensemble.

Eric Bax

CoRR, 2021

Bounding Means of Discrete Distributions.

Eric Bax, Frédéric Ouimet

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

When to Re-Draw a Sample, and Why.

Eric Bax

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Heavy Tails Make Happy Buyers.

Eric Bax

CoRR, 2020

SAFE - Secure Aggregated Frequency Estimates.

Eric Bax, Charlotte Bax

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

Speculate-correct error bounds for k-nearest neighbor classifiers.

Eric Bax, Lingjie Weng, Xu Tian

Mach. Learn., 2019

Collecting Charges for Ad Impact on User Experience for Different Price Types.

Eric Bax

CoRR, 2019

Data Consortia.

Eric Bax, John Donald, Melissa Gerber, Lisa Giaffo, Tanisha Sharma, Nikki Thompson, Kimberly Williams

CoRR, 2019

Computing a Data Dividend.

Eric Bax

CoRR, 2019

Ensemble Validation: Selectivity has a Price, but Variety is Free.

Eric Bax, Farshad Kooti

Proceedings of the International Joint Conference on Neural Networks, 2019

Sharp Frequency Bounds for Sample-Based Queries.

Eric Bax, John Donald

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2017

iPhone's Digital Marketplace: Characterizing the Big Spenders.

Farshad Kooti, Mihajlo Grbovic, Luca Maria Aiello, Eric Bax, Kristina Lerman

Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

2016

Validation of matching.

Ya Le, Eric Bax, Nicola Barbieri, David García-Soriano, Jitesh Mehta, James Li

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

2015

Selecting Weight Functions to Spur Competition in Quasi-Proportional Auctions.

Zheng Wen, Eric Bax, James Li

CoRR, 2015

VCG Payments for Portfolio Allocations in Online Advertising.

James Li, Eric Bax, Nilanjan Roy, Andrea Leistra

CoRR, 2015

Portfolio Allocation for Sellers in Online Advertising.

Ragavendran Gopalakrishnan, Eric Bax, Krishna Prasad Chitrapura, Sachin Garg

CoRR, 2015

Exponential Weight Functions for Quasi-Proportional Auctions.

Eric Bax, James Li, Zheng Wen

CoRR, 2015

Some Theory For Practical Classifier Validation.

Eric Bax, Ya Le

CoRR, 2015

Improved error bounds based on worst likely assignments.

Eric Bax

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014

Pigovian Taxes Can Increase Platform Competitiveness: The Case of Online Display Advertising.

Valeria Stourm, Eric Bax

CoRR, 2014

Validation of Network Reconciliation.

Ya Le, Eric Bax, Nicola Barbieri, David García-Soriano, Jitesh Mehta, James Li

CoRR, 2014

Validation of k-Nearest Neighbor Classifiers Using Inclusion and Exclusion.

Eric Bax, Lingjie Weng, Xu Tian

CoRR, 2014

2012

Validation of k-Nearest Neighbor Classifiers.

Eric Bax

IEEE Trans. Inf. Theory, 2012

Validation of Network Classifiers.

James Li, Abdullah Sonmez, Zehra Cataltepe, Eric Bax

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2012

2008

An Error Bound Based on a Worst Likely Assignment.

Eric Bax, Augusto Callejas

J. Mach. Learn. Res., 2008

Nearly Uniform Validation Improves Compression-Based Error Bounds.

Eric Bax

J. Mach. Learn. Res., 2008

2005

An Event Processing Language (EPL) for Building Sense and Respond Applications.

Elli Albek, Eric Bax, Greg Billock, K. Mani Chandy, Ian Swett

Proceedings of the 19th International Parallel and Distributed Processing Symposium (IPDPS 2005), 2005

2000

Validation of nearest neighbor classifiers.

Eric Bax

IEEE Trans. Inf. Theory, 2000

Using Validation by Inference to Select a Hypothesis Function.

Eric Bax

Proceedings of the 15th International Conference on Pattern Recognition, 2000

1999

Partition-based and sharp uniform error bounds.

Eric Bax

IEEE Trans. Neural Networks, 1999

Improved Hoeffding-style performance guarantees for accurate classifiers.

Eric Bax

Pattern Recognit. Lett., 1999

Validation of fusion through linear programming.

Eric Bax

Proceedings of the International Joint Conference Neural Networks, 1999

1998

Finite-difference algorithms for counting problems.

Eric Bax

PhD thesis, 1998

Validation of average error rate over classifiers.

Eric Bax

Pattern Recognit. Lett., 1998