default search action
Benjamin Coleman
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [c15]Noveen Sachdeva
, Benjamin Coleman
Improving Data Efficiency for Recommenders and LLMs. RecSys 2024: 790-792 - [i19]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 abs/2402.09668 (2024) - 2023
- [c14]Nicholas Meisburger, Vihan Lakshman
BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware. CIKM 2023: 4738-4744 - [c13]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 - [c12]Joshua Engels, Benjamin Coleman, Vihan Lakshman, Anshumali Shrivastava:
DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries. NeurIPS 2023 - [c11]Zichang Liu, Zhaozhuo Xu, Benjamin Coleman, Anshumali Shrivastava:
One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning. NeurIPS 2023 - [c10]Derek Zhiyuan Cheng
Efficient Data Representation Learning in Google-scale Systems. RecSys 2023: 267-271 - [i18]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 abs/2303.17727 (2023) - [i17]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 abs/2305.12102 (2023) - [i16]Benjamin Coleman, David Torres Ramos, Vihan Lakshman, Chen Luo, Anshumali Shrivastava:
CARAMEL: A Succinct Read-Only Lookup Table via Compressed Static Functions. CoRR abs/2305.16545 (2023) - [i15]Gaurav Gupta, Jonah Yi, Benjamin Coleman, Chen Luo, Vihan Lakshman, Anshumali Shrivastava:
CAPS: A Practical Partition Index for Filtered Similarity Search. CoRR abs/2308.15014 (2023) - [i14]Shabnam Daghaghi, Benjamin Coleman, Benito Geordie, Anshumali Shrivastava:
Adaptive Sampling for Deep Learning via Efficient Nonparametric Proxies. CoRR abs/2311.13583 (2023) - 2022
- [c9]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: 4202-4218 - [c8]Benjamin Coleman, Santiago Segarra, Alexander J. Smola, Anshumali Shrivastava:
Graph Reordering for Cache-Efficient Near Neighbor Search. NeurIPS 2022 - [c7]Zichang Liu, Benjamin Coleman, Tianyi Zhang, Anshumali Shrivastava:
Retaining Knowledge for Learning with Dynamic Definition. NeurIPS 2022 - [i13]Joshua Engels, Benjamin Coleman, Vihan Lakshman, Anshumali Shrivastava:
DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries. CoRR abs/2210.15748 (2022) - 2021
- [j2]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): 1819 (2021) - [c6]John Chen, Benjamin Coleman, Anshumali Shrivastava:
Revisiting Consistent Hashing with Bounded Loads. AAAI 2021: 3976-3983 - [c5]Benjamin Coleman, Anshumali Shrivastava:
A One-Pass Distributed and Private Sketch for Kernel Sums with Applications to Machine Learning at Scale. CCS 2021: 3252-3265 - [c4]Joshua Engels, Benjamin Coleman, Anshumali Shrivastava:
Practical Near Neighbor Search via Group Testing. NeurIPS 2021: 9950-9962 - [c3]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: 2226-2234 - [i12]Aditya Desai, Benjamin Coleman, Anshumali Shrivastava:
Density Sketches for Sampling and Estimation. CoRR abs/2102.12301 (2021) - [i11]Benjamin Coleman, Santiago Segarra, Anshumali Shrivastava, Alex Smola:
Graph Reordering for Cache-Efficient Near Neighbor Search. CoRR abs/2104.03221 (2021) - [i10]Zichang Liu, Benjamin Coleman, Anshumali Shrivastava:
Efficient Inference via Universal LSH Kernel. CoRR abs/2106.11426 (2021) - [i9]Joshua Engels, Benjamin Coleman, Anshumali Shrivastava:
Practical Near Neighbor Search via Group Testing. CoRR abs/2106.11565 (2021) - 2020
- [c2]Benjamin Coleman, Richard G. Baraniuk, Anshumali Shrivastava:
Sub-linear Memory Sketches for Near Neighbor Search on Streaming Data. ICML 2020: 2089-2099 - [c1]Benjamin Coleman, Anshumali Shrivastava:
Sub-linear RACE Sketches for Approximate Kernel Density Estimation on Streaming Data. WWW 2020: 1739-1749 - [i8]Benjamin Coleman, Anshumali Shrivastava:
A One-Pass Private Sketch for Most Machine Learning Tasks. CoRR abs/2006.09352 (2020) - [i7]Benjamin Coleman, Gaurav Gupta, John Chen, Anshumali Shrivastava:
STORM: Foundations of End-to-End Empirical Risk Minimization on the Edge. CoRR abs/2006.14554 (2020) - [i6]Louis Abraham, Gary Bécigneul, Benjamin Coleman, Bernhard Schölkopf, Anshumali Shrivastava, Alexander J. Smola:
Bloom Origami Assays: Practical Group Testing. CoRR abs/2008.02641 (2020)
2010 – 2019
- 2019
- [i5]Benjamin Coleman, Anshumali Shrivastava, Richard G. Baraniuk:
RACE: Sub-Linear Memory Sketches for Approximate Near-Neighbor Search on Streaming Data. CoRR abs/1902.06687 (2019) - [i4]John Chen, Benjamin Coleman, Anshumali Shrivastava:
Revisiting Consistent Hashing with Bounded Loads. CoRR abs/1908.08762 (2019) - [i3]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 abs/1910.02611 (2019) - [i2]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 abs/1910.04358 (2019) - [i1]Benjamin Coleman, Anshumali Shrivastava:
Sub-linear RACE Sketches for Approximate Kernel Density Estimation on Streaming Data. CoRR abs/1912.02283 (2019) - 2018
- [j1]Iván Dotú, Scott I. Adamson
SARNAclust: Semi-automatic detection of RNA protein binding motifs from immunoprecipitation data. PLoS Comput. Biol. 14(3) (2018)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-23 20:35 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: