Extreme Classification in Log Memory. - Qixuan Huang; Yiqiu Wang; Tharun Medini; Anshumali Shrivastava (CoRR, 2018)

Cross-Modal Mapping for Generalized Zero-Shot Learning by Soft-Labeling. - Shabnam Daghaghi; Anshumali Shrivastava; Tharun Medini (ViGIL@NeurIPS, 2019)

Extreme Classification in Log Memory using Count-Min Sketch: A Case Study of Amazon Search with 50M Products. - Tharun Medini; Qixuan Huang; Yiqiu Wang; Vijai Mohan; Anshumali Shrivastava (NeurIPS, 2019)

SLIDE : In Defense of Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning Systems. - Beidi Chen; Tharun Medini; Anshumali Shrivastava (CoRR, 2019)

Semantic Similarity Based Softmax Classifier for Zero-Shot Learning. - Shabnam Daghaghi; Tharun Medini; Anshumali Shrivastava (CoRR, 2019)

RAMBO: Repeated And Merged Bloom Filter for Multiple Set Membership Testing (MSMT) in Sub-linear time. - Gaurav Gupta; Benjamin Coleman; Tharun Medini; Vijai Mohan; Anshumali Shrivastava (CoRR, 2019)

SLIDE : In Defense of Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning Systems. - Beidi Chen; Tharun Medini; James Farwell; Sameh Gobriel; Tsung-Yuan Charlie Tai; Anshumali Shrivastava (MLSys, 2020)

A Constant-time Adaptive Negative Sampling. - Shabnam Daghaghi; Tharun Medini; Beidi Chen; Mengnan Zhao; Anshumali Shrivastava (CoRR, 2020)

SOLAR: Sparse Orthogonal Learned and Random Embeddings. - Tharun Medini; Beidi Chen; Anshumali Shrivastava (ICLR, 2021)

A Tale of Two Efficient and Informative Negative Sampling Distributions. - Shabnam Daghaghi; Tharun Medini; Nicholas Meisburger; Beidi Chen; Mengnan Zhao; Anshumali Shrivastava (ICML, 2021)

Fast Processing and Querying of 170TB of Genomics Data via a Repeated And Merged BloOm Filter (RAMBO). - Gaurav Gupta; Minghao Yan; Benjamin Coleman; Bryce Kille; Ryan A. Leo Elworth; Tharun Medini; Todd J. Treangen; Anshumali Shrivastava (SIGMOD Conference, 2021)

SDM-Net: A simple and effective model for generalized zero-shot learning. - Shabnam Daghaghi; Tharun Medini; Anshumali Shrivastava (UAI, 2021)

IRLI: Iterative Re-partitioning for Learning to Index. - Gaurav Gupta; Tharun Medini; Anshumali Shrivastava; Alexander J. Smola (CoRR, 2021)

Structural Contrastive Representation Learning for Zero-shot Multi-label Text Classification. - Tianyi Zhang 011; Zhaozhuo Xu; Tharun Medini; Anshumali Shrivastava (EMNLP (Findings), 2022)

BLISS: A Billion scale Index using Iterative Re-partitioning. - Gaurav Gupta; Tharun Medini; Anshumali Shrivastava; Alexander J. Smola (KDD, 2022)

Distributed SLIDE: Enabling Training Large Neural Networks on Low Bandwidth and Simple CPU-Clusters via Model Parallelism and Sparsity. - Minghao Yan; Nicholas Meisburger; Tharun Medini; Anshumali Shrivastava (CoRR, 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)

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)