Vihan Lakshman

According to our database, Vihan Lakshman authored at least 16 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

AutoCSF: Provably Space-Efficient Indexing of Skewed Key-Value Workloads via Filter-Augmented Compressed Static Functions.

David Torres Ramos, Vihan Lakshman, Chen Luo, Todd J. Treangen, Benjamin Coleman

CoRR, March, 2026

Down with the Hierarchy: The 'H' in HNSW Stands for "Hubs".

Blaise Munyampirwa, Vihan Lakshman, Benjamin Coleman

Proceedings of the Advances in Information Retrieval, 2026

2025

Breaking the Curse of Dimensionality: On the Stability of Modern Vector Retrieval.

Vihan Lakshman, Blaise Munyampirwa, Julian Shun, Benjamin Coleman

CoRR, December, 2025

2024

On the Diminishing Returns of Width for Continual Learning.

Etash Kumar Guha, Vihan Lakshman

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

CAPS: A Practical Partition Index for Filtered Similarity Search.

Gaurav Gupta, Jonah Yi, Benjamin Coleman, Chen Luo, Vihan Lakshman, Anshumali Shrivastava

CoRR, 2023

CARAMEL: A Succinct Read-Only Lookup Table via Compressed Static Functions.

Benjamin Coleman, David Torres Ramos, Vihan Lakshman, Chen Luo, Anshumali Shrivastava

CoRR, 2023

BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Neural Networks on Commodity CPU Hardware.

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

CoRR, 2023

From Research to Production: Towards Scalable and Sustainable Neural Recommendation Models on Commodity CPU Hardware.

Anshumali Shrivastava, Vihan Lakshman, Tharun Medini, Nicholas Meisburger, Joshua Engels, David Torres Ramos, Benito Geordie, Pratik Pranav, Shubh Gupta, Yashwanth Adunukota, Siddharth Jain

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries.

Joshua Engels, Benjamin Coleman, Vihan Lakshman, Anshumali Shrivastava

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware.

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

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

ROSE: Robust Caches for Amazon Product Search.

Chen Luo, Vihan Lakshman, Anshumali Shrivastava, Tianyu Cao, Sreyashi Nag, Rahul Goutam, Hanqing Lu, Yiwei Song, Bing Yin

Proceedings of the Companion of The Web Conference 2022, Virtual Event / Lyon, France, April 25, 2022

Massive Text Normalization via an Efficient Randomized Algorithm.

Nan Jiang, Chen Luo, Vihan Lakshman, Yesh Dattatreya, Yexiang Xue

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

2021

Low-Precision Quantization for Efficient Nearest Neighbor Search.

Anthony Ko, Iman Keivanloo, Vihan Lakshman, Eric Schkufza

CoRR, 2021

Embracing Structure in Data for Billion-Scale Semantic Product Search.

Vihan Lakshman, Choon Hui Teo, Xiaowen Chu, Priyanka Nigam, Abhinandan Patni, Pooja Maknikar, S. V. N. Vishwanathan

CoRR, 2021

A Fast Randomized Algorithm for Massive Text Normalization.

Nan Jiang, Chen Luo, Vihan Lakshman, Yesh Dattatreya, Yexiang Xue

CoRR, 2021

2019

Semantic Product Search.

Priyanka Nigam, Yiwei Song, Vijai Mohan, Vihan Lakshman, Weitian Allen Ding, Ankit Shingavi, Choon Hui Teo, Hao Gu, Bing Yin

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019