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2020 – today
- 2024
[c7]Etash Kumar Guha, Vihan Lakshman:
On the Diminishing Returns of Width for Continual Learning. ICML 2024- [i9]Etash Kumar Guha, Vihan Lakshman:
On the Diminishing Returns of Width for Continual Learning. CoRR abs/2403.06398 (2024) - 2023
- [c6]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: 4738-4744 - [c5]Joshua Engels, Benjamin Coleman, Vihan Lakshman, Anshumali Shrivastava:
DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries. NeurIPS 2023 - [c4]Anshumali Shrivastava, Vihan Lakshman, Tharun Medini, Nicholas Meisburger, Joshua Engels, David Torres Ramos, Benito Geordie, Pratik Pranav, Shubh Gupta, Yashwanth Adunukota, Siddharth Jain:
From Research to Production: Towards Scalable and Sustainable Neural Recommendation Models on Commodity CPU Hardware. RecSys 2023: 1071-1074 - [i8]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) - [i7]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) - [i6]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) - 2022
- [c3]Chen Luo, Vihan Lakshman, Anshumali Shrivastava, Tianyu Cao, Sreyashi Nag, Rahul Goutam, Hanqing Lu, Yiwei Song, Bing Yin:
ROSE: Robust Caches for Amazon Product Search. WWW (Companion Volume) 2022: 89-93 - [c2]Nan Jiang, Chen Luo, Vihan Lakshman, Yesh Dattatreya, Yexiang Xue:
Massive Text Normalization via an Efficient Randomized Algorithm. WWW 2022: 2946-2956 - [i5]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
- [i4]Nan Jiang, Chen Luo, Vihan Lakshman, Yesh Dattatreya, Yexiang Xue:
A Fast Randomized Algorithm for Massive Text Normalization. CoRR abs/2110.03024 (2021) - [i3]Vihan Lakshman, Choon Hui Teo, Xiaowen Chu, Priyanka Nigam, Abhinandan Patni, Pooja Maknikar, S. V. N. Vishwanathan:
Embracing Structure in Data for Billion-Scale Semantic Product Search. CoRR abs/2110.06125 (2021) - [i2]Anthony Ko, Iman Keivanloo, Vihan Lakshman, Eric Schkufza:
Low-Precision Quantization for Efficient Nearest Neighbor Search. CoRR abs/2110.08919 (2021)
2010 – 2019
- 2019
- [c1]Priyanka Nigam, Yiwei Song, Vijai Mohan, Vihan Lakshman, Weitian Allen Ding, Ankit Shingavi, Choon Hui Teo, Hao Gu, Bing Yin:
Semantic Product Search. KDD 2019: 2876-2885 - [i1]Priyanka Nigam, Yiwei Song, Vijai Mohan, Vihan Lakshman, Weitian Ding, Ankit Shingavi, Choon Hui Teo, Hao Gu, Bing Yin:
Semantic Product Search. CoRR abs/1907.00937 (2019)
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