Benjamin Coleman

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 35

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Publications

Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, Jianmo Ni, Lichan Hong, Ed H. Chi, James Caverlee, Julian J. McAuley, Derek Zhiyuan Cheng
How to Train Data-Efficient LLMs. CoRR (2024)
Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng
Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. CoRR (2023)
Gaurav Gupta, Jonah Yi, Benjamin Coleman, Chen Luo, Vihan Lakshman, Anshumali Shrivastava
CAPS: A Practical Partition Index for Filtered Similarity Search. CoRR (2023)
Nicholas Meisburger, Vihan Lakshman, Benito Geordie, Joshua Engels, David Torres Ramos, Pratik Pranav, Benjamin Coleman, Benjamin Meisburger, Shubh Gupta, Yashwanth Adunukota, Siddharth Jain, Tharun Medini, Anshumali Shrivastava
BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware. CIKM (2023)
Zichang Liu, Zhaozhuo Xu, Benjamin Coleman, Anshumali Shrivastava
One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning. NeurIPS (2023)
Joshua Engels, Benjamin Coleman, Vihan Lakshman, Anshumali Shrivastava
DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries. NeurIPS (2023)
Shabnam Daghaghi, Benjamin Coleman, Benito Geordie, Anshumali Shrivastava
Adaptive Sampling for Deep Learning via Efficient Nonparametric Proxies. CoRR (2023)
Benjamin Coleman, David Torres Ramos, Vihan Lakshman, Chen Luo, Anshumali Shrivastava
CARAMEL: A Succinct Read-Only Lookup Table via Compressed Static Functions. CoRR (2023)
Nicholas Meisburger, Vihan Lakshman, Benito Geordie, Joshua Engels, David Torres Ramos, Pratik Pranav, Benjamin Coleman, Benjamin Meisburger, Shubh Gupta, Yashwanth Adunukota, Tharun Medini, Anshumali Shrivastava
BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Neural Networks on Commodity CPU Hardware. CoRR (2023)
Derek Zhiyuan Cheng, Ruoxi Wang, Wang-Cheng Kang, Benjamin Coleman, Yin Zhang, Jianmo Ni, Jonathan Valverde, Lichan Hong, Ed H. Chi
Efficient Data Representation Learning in Google-scale Systems. RecSys (2023)
Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng
Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. NeurIPS (2023)
Joshua Engels, Benjamin Coleman, Vihan Lakshman, Anshumali Shrivastava
DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries. CoRR (2022)
Benjamin Coleman, Benito Geordie, Li Chou, Ryan A. Leo Elworth, Todd J. Treangen, Anshumali Shrivastava
One-Pass Diversified Sampling with Application to Terabyte-Scale Genomic Sequence Streams. ICML (2022)
Benjamin Coleman, Santiago Segarra, Alexander J. Smola, Anshumali Shrivastava
Graph Reordering for Cache-Efficient Near Neighbor Search. NeurIPS (2022)
Zichang Liu, Benjamin Coleman, Tianyi Zhang, Anshumali Shrivastava
Retaining Knowledge for Learning with Dynamic Definition. NeurIPS (2022)
Benjamin Coleman, Anshumali Shrivastava
A One-Pass Distributed and Private Sketch for Kernel Sums with Applications to Machine Learning at Scale. CCS (2021)
John Chen, Benjamin Coleman, Anshumali Shrivastava
Revisiting Consistent Hashing with Bounded Loads. AAAI (2021)
Mazhar Sher, Benjamin Coleman, Massimo Caputi, Waseem Asghar
Development of a Point-of-Care Assay for HIV-1 Viral Load Using Higher Refractive Index Antibody-Coated Microbeads. Sensors 21 (5) (2021)
Joshua Engels, Benjamin Coleman, Anshumali Shrivastava
Practical Near Neighbor Search via Group Testing. NeurIPS (2021)
Benjamin Coleman, Santiago Segarra, Anshumali Shrivastava, Alex Smola
Graph Reordering for Cache-Efficient Near Neighbor Search. CoRR (2021)
Zichang Liu, Benjamin Coleman, Anshumali Shrivastava
Efficient Inference via Universal LSH Kernel. CoRR (2021)
Aditya Desai, Benjamin Coleman, Anshumali Shrivastava
Density Sketches for Sampling and Estimation. CoRR (2021)
Gaurav Gupta, Minghao Yan, Benjamin Coleman, Bryce Kille, Ryan A. Leo Elworth, Tharun Medini, Todd J. Treangen, Anshumali Shrivastava
Fast Processing and Querying of 170TB of Genomics Data via a Repeated And Merged BloOm Filter (RAMBO). SIGMOD Conference (2021)
Joshua Engels, Benjamin Coleman, Anshumali Shrivastava
Practical Near Neighbor Search via Group Testing. CoRR (2021)
Benjamin Coleman, Gaurav Gupta, John Chen, Anshumali Shrivastava
STORM: Foundations of End-to-End Empirical Risk Minimization on the Edge. CoRR (2020)
Benjamin Coleman, Anshumali Shrivastava
A One-Pass Private Sketch for Most Machine Learning Tasks. CoRR (2020)
Benjamin Coleman, Richard G. Baraniuk, Anshumali Shrivastava
Sub-linear Memory Sketches for Near Neighbor Search on Streaming Data. ICML (2020)
Louis Abraham, Gary Bécigneul, Benjamin Coleman, Bernhard Schölkopf, Anshumali Shrivastava, Alexander J. Smola
Bloom Origami Assays: Practical Group Testing. CoRR (2020)
Benjamin Coleman, Anshumali Shrivastava
Sub-linear RACE Sketches for Approximate Kernel Density Estimation on Streaming Data. WWW (2020)
Gaurav Gupta, Minghao Yan, Benjamin Coleman, Bryce Kille, Ryan A. Leo Elworth, Tharun Medini, Todd J. Treangen, Anshumali Shrivastava
Fast Processing and Querying of 170TB of Genomics Data via a Repeated And Merged BloOm Filter (RAMBO). CoRR (2019)
John Chen, Benjamin Coleman, Anshumali Shrivastava
Revisiting Consistent Hashing with Bounded Loads. CoRR (2019)
Benjamin Coleman, Anshumali Shrivastava
Sub-linear RACE Sketches for Approximate Kernel Density Estimation on Streaming Data. CoRR (2019)
Benjamin Coleman, Anshumali Shrivastava, Richard G. Baraniuk
RACE: Sub-Linear Memory Sketches for Approximate Near-Neighbor Search on Streaming Data. CoRR (2019)
Gaurav Gupta, Benjamin Coleman, Tharun Medini, Vijai Mohan, Anshumali Shrivastava
RAMBO: Repeated And Merged Bloom Filter for Multiple Set Membership Testing (MSMT) in Sub-linear time. CoRR (2019)
Iván Dotú, Scott I. Adamson, Benjamin Coleman, Cyril Fournier, Emma Ricart-Altimiras, Eduardo Eyras, Jeffrey H. Chuang
SARNAclust: Semi-automatic detection of RNA protein binding motifs from immunoprecipitation data. PLoS Comput. Biol. 14 (3) (2018)