Benjamin Coleman

43 papers A* 11A 3Journal 27Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AgenticTagger: Structured Item Representation for Recommendation with LLM Agents. CoRR Zhouhang Xie, Bo Peng, Zhankui He, Ziqi Chen, Alice Han, Isabella Ye, Benjamin Coleman, Noveen Sachdeva, Fernando Pereira, Julian J. McAuley, Wang-Cheng Kang, Derek Zhiyuan Cheng, Beidou Wang, Randolph Brown
2026	J	`jnl`	AutoCSF: Provably Space-Efficient Indexing of Skewed Key-Value Workloads via Filter-Augmented Compressed Static Functions. CoRR David Torres Ramos, Vihan Lakshman, Chen Luo, Todd J. Treangen, Benjamin Coleman
2026	—	`conf`	Down with the Hierarchy: The 'H' in HNSW Stands for "Hubs". ECIR (3) Blaise Munyampirwa, Vihan Lakshman, Benjamin Coleman
2026	J	`jnl`	PACEvolve: Enabling Long-Horizon Progress-Aware Consistent Evolution. CoRR Minghao Yan, Bo Peng, Benjamin Coleman, Ziqi Chen, Zhouhang Xie, Shuo Chen, Zhankui He, Noveen Sachdeva, Isabella Ye, Weili Wang, Chi Wang, Ed H. Chi, Fernando Pereira, Wang-Cheng Kang, Derek Zhiyuan Cheng, Beidou Wang
2025	J	`jnl`	Breaking the Curse of Dimensionality: On the Stability of Modern Vector Retrieval. CoRR Vihan Lakshman, Blaise Munyampirwa, Julian Shun, Benjamin Coleman
2025	J	`jnl`	Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory. CoRR Tianxin Wei, Noveen Sachdeva, Benjamin Coleman, Zhankui He, Yuanchen Bei, Xuying Ning, Mengting Ai, Yunzhe Li, Jingrui He, Ed H. Chi, Chi Wang, Shuo Chen, Fernando Pereira, Wang-Cheng Kang, Derek Zhiyuan Cheng
2024	J	`jnl`	Down with the Hierarchy: The 'H' in HNSW Stands for "Hubs". CoRR Blaise Munyampirwa, Vihan Lakshman, Benjamin Coleman
2024	J	`jnl`	How to Train Data-Efficient LLMs. CoRR Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, Jianmo Ni, Lichan Hong, Ed H. Chi, James Caverlee, Julian J. McAuley, Derek Zhiyuan Cheng
2024	A	`conf`	Improving Data Efficiency for Recommenders and LLMs. RecSys Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, Jianmo Ni, James Caverlee, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng
2023	J	`jnl`	Adaptive Sampling for Deep Learning via Efficient Nonparametric Proxies. CoRR Shabnam Daghaghi, Benjamin Coleman, Benito Geordie, Anshumali Shrivastava
2023	J	`jnl`	BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Neural Networks on Commodity CPU Hardware. CoRR 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
2023	A	`conf`	BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware. CIKM 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
2023	J	`jnl`	CAPS: A Practical Partition Index for Filtered Similarity Search. CoRR Gaurav Gupta, Jonah Yi, Benjamin Coleman, Chen Luo, Vihan Lakshman, Anshumali Shrivastava
2023	J	`jnl`	CARAMEL: A Succinct Read-Only Lookup Table via Compressed Static Functions. CoRR Benjamin Coleman, David Torres Ramos, Vihan Lakshman, Chen Luo, Anshumali Shrivastava
2023	A*	`conf`	DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries. NeurIPS Joshua Engels, Benjamin Coleman, Vihan Lakshman, Anshumali Shrivastava
2023	A	`conf`	Efficient Data Representation Learning in Google-scale Systems. RecSys Derek Zhiyuan Cheng, Ruoxi Wang, Wang-Cheng Kang, Benjamin Coleman, Yin Zhang, Jianmo Ni, Jonathan Valverde, Lichan Hong, Ed H. Chi
2023	A*	`conf`	One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning. NeurIPS Zichang Liu, Zhaozhuo Xu, Benjamin Coleman, Anshumali Shrivastava
2023	A*	`conf`	Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. NeurIPS Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng
2023	J	`jnl`	Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. CoRR Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng
2022	J	`jnl`	DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries. CoRR Joshua Engels, Benjamin Coleman, Vihan Lakshman, Anshumali Shrivastava
2022	A*	`conf`	Graph Reordering for Cache-Efficient Near Neighbor Search. NeurIPS Benjamin Coleman, Santiago Segarra, Alexander J. Smola, Anshumali Shrivastava
2022	A*	`conf`	One-Pass Diversified Sampling with Application to Terabyte-Scale Genomic Sequence Streams. ICML Benjamin Coleman, Benito Geordie, Li Chou, Ryan A. Leo Elworth, Todd J. Treangen, Anshumali Shrivastava
2022	A*	`conf`	Retaining Knowledge for Learning with Dynamic Definition. NeurIPS Zichang Liu, Benjamin Coleman, Tianyi Zhang, Anshumali Shrivastava
2021	A*	`conf`	A One-Pass Distributed and Private Sketch for Kernel Sums with Applications to Machine Learning at Scale. CCS Benjamin Coleman, Anshumali Shrivastava
2021	J	`jnl`	Density Sketches for Sampling and Estimation. CoRR Aditya Desai, Benjamin Coleman, Anshumali Shrivastava
2021	J	`jnl`	Development of a Point-of-Care Assay for HIV-1 Viral Load Using Higher Refractive Index Antibody-Coated Microbeads. Sensors Mazhar Sher, Benjamin Coleman, Massimo Caputi, Waseem Asghar
2021	J	`jnl`	Efficient Inference via Universal LSH Kernel. CoRR Zichang Liu, Benjamin Coleman, Anshumali Shrivastava
2021	—	`conf`	Fast Processing and Querying of 170TB of Genomics Data via a Repeated And Merged BloOm Filter (RAMBO). SIGMOD Conference Gaurav Gupta, Minghao Yan, Benjamin Coleman, Bryce Kille, Ryan A. Leo Elworth, Tharun Medini, Todd J. Treangen, Anshumali Shrivastava
2021	J	`jnl`	Graph Reordering for Cache-Efficient Near Neighbor Search. CoRR Benjamin Coleman, Santiago Segarra, Anshumali Shrivastava, Alex Smola
2021	A*	`conf`	Practical Near Neighbor Search via Group Testing. NeurIPS Joshua Engels, Benjamin Coleman, Anshumali Shrivastava
2021	J	`jnl`	Practical Near Neighbor Search via Group Testing. CoRR Joshua Engels, Benjamin Coleman, Anshumali Shrivastava
2021	A*	`conf`	Revisiting Consistent Hashing with Bounded Loads. AAAI John Chen, Benjamin Coleman, Anshumali Shrivastava
2020	J	`jnl`	A One-Pass Private Sketch for Most Machine Learning Tasks. CoRR Benjamin Coleman, Anshumali Shrivastava
2020	J	`jnl`	Bloom Origami Assays: Practical Group Testing. CoRR Louis Abraham, Gary Bécigneul, Benjamin Coleman, Bernhard Schölkopf, Anshumali Shrivastava, Alexander J. Smola
2020	J	`jnl`	STORM: Foundations of End-to-End Empirical Risk Minimization on the Edge. CoRR Benjamin Coleman, Gaurav Gupta, John Chen, Anshumali Shrivastava
2020	A*	`conf`	Sub-linear Memory Sketches for Near Neighbor Search on Streaming Data. ICML Benjamin Coleman, Richard G. Baraniuk, Anshumali Shrivastava
2020	A*	`conf`	Sub-linear RACE Sketches for Approximate Kernel Density Estimation on Streaming Data. WWW Benjamin Coleman, Anshumali Shrivastava
2019	J	`jnl`	Fast Processing and Querying of 170TB of Genomics Data via a Repeated And Merged BloOm Filter (RAMBO). CoRR Gaurav Gupta, Minghao Yan, Benjamin Coleman, Bryce Kille, Ryan A. Leo Elworth, Tharun Medini, Todd J. Treangen, Anshumali Shrivastava
2019	J	`jnl`	RACE: Sub-Linear Memory Sketches for Approximate Near-Neighbor Search on Streaming Data. CoRR Benjamin Coleman, Anshumali Shrivastava, Richard G. Baraniuk
2019	J	`jnl`	RAMBO: Repeated And Merged Bloom Filter for Multiple Set Membership Testing (MSMT) in Sub-linear time. CoRR Gaurav Gupta, Benjamin Coleman, Tharun Medini, Vijai Mohan, Anshumali Shrivastava
2019	J	`jnl`	Revisiting Consistent Hashing with Bounded Loads. CoRR John Chen, Benjamin Coleman, Anshumali Shrivastava
2019	J	`jnl`	Sub-linear RACE Sketches for Approximate Kernel Density Estimation on Streaming Data. CoRR Benjamin Coleman, Anshumali Shrivastava
2018	J	`jnl`	SARNAclust: Semi-automatic detection of RNA protein binding motifs from immunoprecipitation data. PLoS Comput. Biol. Iván Dotú, Scott I. Adamson, Benjamin Coleman, Cyril Fournier, Emma Ricart-Altimiras, Eduardo Eyras, Jeffrey H. Chuang