Semantic Product Search. - Priyanka Nigam; Yiwei Song; Vijai Mohan; Vihan Lakshman; Weitian Allen Ding; Ankit Shingavi; Choon Hui Teo; Hao Gu; Bing Yin (KDD, 2019)

A Fast Randomized Algorithm for Massive Text Normalization. - Nan Jiang 012; Chen Luo 003; Vihan Lakshman; Yesh Dattatreya; Yexiang Xue (CoRR, 2021)

Embracing Structure in Data for Billion-Scale Semantic Product Search. - Vihan Lakshman; Choon Hui Teo; Xiaowen Chu 002; Priyanka Nigam; Abhinandan Patni; Pooja Maknikar; S. V. N. Vishwanathan (CoRR, 2021)

Low-Precision Quantization for Efficient Nearest Neighbor Search. - Anthony Ko; Iman Keivanloo; Vihan Lakshman; Eric Schkufza (CoRR, 2021)

Massive Text Normalization via an Efficient Randomized Algorithm. - Nan Jiang 012; Chen Luo 003; Vihan Lakshman; Yesh Dattatreya; Yexiang Xue (WWW, 2022)

ROSE: Robust Caches for Amazon Product Search. - Chen Luo 003; Vihan Lakshman; Anshumali Shrivastava; Tianyu Cao 001; Sreyashi Nag; Rahul Goutam; Hanqing Lu; Yiwei Song; Bing Yin (WWW (Companion Volume), 2022)

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; et al. (CIKM, 2023)

DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries. - Joshua Engels; Benjamin Coleman; Vihan Lakshman; Anshumali Shrivastava (NeurIPS, 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 (RecSys, 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)

CARAMEL: A Succinct Read-Only Lookup Table via Compressed Static Functions. - Benjamin Coleman; David Torres Ramos; Vihan Lakshman; Chen Luo 003; Anshumali Shrivastava (CoRR, 2023)

CAPS: A Practical Partition Index for Filtered Similarity Search. - Gaurav Gupta; Jonah Yi; Benjamin Coleman; Chen Luo 001; Vihan Lakshman; Anshumali Shrivastava (CoRR, 2023)

On the Diminishing Returns of Width for Continual Learning. - Etash Kumar Guha; Vihan Lakshman (ICML, 2024)

Down with the Hierarchy: The 'H' in HNSW Stands for "Hubs". - Blaise Munyampirwa; Vihan Lakshman; Benjamin Coleman (CoRR, 2024)