S. V. N. Vishwanathan

Computer Science · Physical Sciences

38h-index8.1kcitations147works0.32yr avg
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Research Topics

Machine Learning and Algorithms(32), Stochastic Gradient Optimization Techniques(19), Sparse and Compressive Sensing Techniques(17), Topic Modeling(14), Neural Networks and Applications(14)

Publications147 total

Smart Robotics: An Integrated Approach to Obstacle Avoidance and Lane Following
2025
Retrieval-augmented Encoders for Extreme Multi-label Text Classification
arXiv (Cornell University)·2025Open Access
Bi-CAT: Improving Robustness of LLM-based Text Rankers to Conditional Distribution Shifts
2024Open Access
PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval Models
2024· 1 citedOpen Access
Web-Scale Semantic Product Search with Large Language Models
Lecture notes in computer science·2023· 6 citedOpen Access
Toward Understanding Privileged Features Distillation in Learning-to-Rank
arXiv (Cornell University)·2022· 4 citedOpen Access
On the Value of Behavioral Representations for Dense Retrieval
arXiv (Cornell University)·2022Open Access
Augmenting Training Data for Massive Semantic Matching Models in Low-Traffic E-commerce Stores
2022· 3 citedOpen Access
Embracing Structure in Data for Billion-Scale Semantic Product Search
arXiv (Cornell University)·2021Open Access
DS-FACTO: Doubly Separable Factorization Machines
arXiv (Cornell University)·2020Open Access
Scaling Multinomial Logistic Regression via Hybrid Parallelism
2019· 8 citedOpen Access
Whole Page Optimization with Global Constraints
2019· 16 cited
Extreme Stochastic Variational Inference: Distributed Inference for Large Scale Mixture Models
2019· 2 cited
Whole page optimization with local and global constraints
2019
Diversifying Music Recommendations
arXiv (Cornell University)·2018· 8 citedOpen Access
An Efficient Bandit Algorithm for Realtime Multivariate Optimization
2017· 111 citedOpen Access
Batch-Expansion Training: An Efficient Optimization Framework
arXiv (Cornell University)·2017· 1 citedOpen Access
Batch-Expansion Training: An Efficient Optimization Paradigm for Machine Learning.
arXiv (Cornell University)·2017· 1 citedOpen Access
Batch-Expansion Training: An Efficient Optimization Framework
arXiv (Cornell University)·2017Open Access
Colors -- Messengers of Concepts
ACM Transactions on Computer-Human Interaction·2017· 47 cited
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Frequent Co-authors

Nicol N. Schraudolph(9), Karsten Borgwardt(7), Alex Smola(7), Alexander J. Smola(5), Choon Hui Teo(4), Manik Varma(4), Hyokun Yun(4), Pinar Yanardag(3), Hsiang‐Fu Yu(3), Cho‐Jui Hsieh(3), Inderjit S. Dhillon(3), Simon Günter(3), Li Cheng(3), Shihao Ji(3), Thomas Hofmann(2), James Petterson(2), Quoc V. Le(2), Bharath Hariharan(2), Daniel Hill(2), Houssam Nassif(2)