Shrivastava, Anshumali

58 publications

NeurIPS 2025 70% Size, 100% Accuracy: Lossless LLM Compression for Efficient GPU Inference via Dynamic-Length Float (DFloat11) Tianyi Zhang, Mohsen Hariri, Shaochen Zhong, Vipin Chaudhary, Yang Sui, Xia Hu, Anshumali Shrivastava

NeurIPS 2025 Breaking the Frozen Subspace: Importance Sampling for Low-Rank Optimization in LLM Pretraining Haochen Zhang, Junze Yin, Guanchu Wang, Zirui Liu, Lin Yang, Tianyi Zhang, Anshumali Shrivastava, Vladimir Braverman

ICLR 2025 LeanQuant: Accurate and Scalable Large Language Model Quantization with Loss-Error-Aware Grid Tianyi Zhang, Anshumali Shrivastava

ICML 2025 Sketch to Adapt: Fine-Tunable Sketches for Efficient LLM Adaptation Tianyi Zhang, Junda Su, Aditya Desai, Oscar Wu, Zhaozhuo Xu, Anshumali Shrivastava

ICLR 2024 In Defense of Parameter Sharing for Model-Compression Aditya Desai, Anshumali Shrivastava

NeurIPS 2024 KV Cache Is 1 Bit per Channel: Efficient Large Language Model Inference with Coupled Quantization Tianyi Zhang, Jonah Yi, Zhaozhuo Xu, Anshumali Shrivastava

NeurIPS 2024 NoMAD-Attention: Efficient LLM Inference on CPUs Through Multiply-Add-Free Attention Tianyi Zhang, Jonah Yi, Bowen Yao, Zhaozhuo Xu, Anshumali Shrivastava

NeurIPS 2024 SS1: Accelerating Inference with Fast and Expressive Sketch Structured Transform Kimia Saedi, Aditya Desai, Apoorv Walia, Jihyeong Lee, Keren Zhou, Anshumali Shrivastava

ICML 2024 Soft Prompt Recovers Compressed LLMs, Transferably Zhaozhuo Xu, Zirui Liu, Beidi Chen, Shaochen Zhong, Yuxin Tang, Jue Wang, Kaixiong Zhou, Xia Hu, Anshumali Shrivastava

AISTATS 2023 A Tale of Two Efficient Value Iteration Algorithms for Solving Linear MDPs with Large Action Space Zhaozhuo Xu, Zhao Song, Anshumali Shrivastava

NeurIPS 2023 DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries Joshua Engels, Benjamin Coleman, Vihan Lakshman, Anshumali Shrivastava

ICML 2023 Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Re, Beidi Chen

UAI 2023 Graph Self-Supervised Learning via Proximity Distribution Minimization Tianyi Zhang, Zhenwei Dai, Zhaozhuo Xu, Anshumali Shrivastava

ICML 2023 Hardware-Aware Compression with Random Operation Access Specific Tile (ROAST) Hashing Aditya Desai, Keren Zhou, Anshumali Shrivastava

ICLR 2023 Learning Multimodal Data Augmentation in Feature Space Zichang Liu, Zhiqiang Tang, Xingjian Shi, Aston Zhang, Mu Li, Anshumali Shrivastava, Andrew Gordon Wilson

NeurIPS 2023 One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning Zichang Liu, Zhaozhuo Xu, Benjamin Coleman, Anshumali Shrivastava

NeurIPS 2023 Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time Zichang Liu, Aditya Desai, Fangshuo Liao, Weitao Wang, Victor Xie, Zhaozhuo Xu, Anastasios Kyrillidis, Anshumali Shrivastava

NeurIPSW 2022 Adaptive Sparse Federated Learning in Large Output Spaces via Hashing Zhaozhuo Xu, Luyang Liu, Zheng Xu, Anshumali Shrivastava

ICML 2022 DRAGONN: Distributed Randomized Approximate Gradients of Neural Networks Zhuang Wang, Zhaozhuo Xu, Xinyu Wu, Anshumali Shrivastava, T. S. Eugene Ng

NeurIPS 2022 Graph Reordering for Cache-Efficient near Neighbor Search Benjamin Coleman, Santiago Segarra, Alexander J Smola, Anshumali Shrivastava

ICML 2022 One-Pass Diversified Sampling with Application to Terabyte-Scale Genomic Sequence Streams Benjamin Coleman, Benito Geordie, Li Chou, R. A. Leo Elworth, Todd Treangen, Anshumali Shrivastava

NeurIPS 2022 Retaining Knowledge for Learning with Dynamic Definition Zichang Liu, Benjamin Coleman, Tianyi Zhang, Anshumali Shrivastava

NeurIPS 2022 The Trade-Offs of Model Size in Large Recommendation Models : 100GB to 10MB Criteo-Tb DLRM Model Aditya Desai, Anshumali Shrivastava

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

NeurIPS 2021 Breaking the Linear Iteration Cost Barrier for Some Well-Known Conditional Gradient Methods Using MaxIP Data-Structures Zhaozhuo Xu, Zhao Song, Anshumali Shrivastava

ECML-PKDD 2021 Efficient and Less Centralized Federated Learning Li Chou, Zichang Liu, Zhuang Wang, Anshumali Shrivastava

NeurIPS 2021 Locality Sensitive Teaching Zhaozhuo Xu, Beidi Chen, Chaojian Li, Weiyang Liu, Le Song, Yingyan Lin, Anshumali Shrivastava

ICLR 2021 MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan Lingjie Li, Tri Dao, Zhao Song, Anshumali Shrivastava, Christopher Re

NeurIPS 2021 Practical near Neighbor Search via Group Testing Joshua Engels, Benjamin Coleman, Anshumali Shrivastava

NeurIPS 2021 Raw Nav-Merge Seismic Data to Subsurface Properties with MLP Based Multi-Modal Information Unscrambler Aditya Desai, Zhaozhuo Xu, Menal Gupta, Anu Chandran, Antoine Vial-Aussavy, Anshumali Shrivastava

AAAI 2021 Revisiting Consistent Hashing with Bounded Loads John Chen, Benjamin Coleman, Anshumali Shrivastava

UAI 2021 SDM-Net: A Simple and Effective Model for Generalized Zero-Shot Learning Shabnam Daghaghi, Tharun Medini, Anshumali Shrivastava

ICLR 2021 SOLAR: Sparse Orthogonal Learned and Random Embeddings Tharun Medini, Beidi Chen, Anshumali Shrivastava

NeurIPS 2020 Adaptive Learned Bloom Filter (Ada-BF): Efficient Utilization of the Classifier with Application to Real-Time Information Filtering on the Web Zhenwei Dai, Anshumali Shrivastava

ICML 2020 Angular Visual Hardness Beidi Chen, Weiyang Liu, Zhiding Yu, Jan Kautz, Anshumali Shrivastava, Animesh Garg, Animashree Anandkumar

AAAI 2020 FourierSAT: A Fourier Expansion-Based Algebraic Framework for Solving Hybrid Boolean Constraints Anastasios Kyrillidis, Anshumali Shrivastava, Moshe Y. Vardi, Zhiwei Zhang

IJCAI 2020 Mutual Information Estimation Using LSH Sampling Ryan Spring, Anshumali Shrivastava

ICML 2020 Sub-Linear Memory Sketches for near Neighbor Search on Streaming Data Benjamin Coleman, Richard Baraniuk, Anshumali Shrivastava

ICMLW 2019 Angular Visual Hardness Beidi Chen, Weiyang Liu, Animesh Garg, Zhiding Yu, Anshumali Shrivastava, Anima Anandkumar

ICML 2019 Compressing Gradient Optimizers via Count-Sketches Ryan Spring, Anastasios Kyrillidis, Vijai Mohan, Anshumali Shrivastava

NeurIPS 2019 Extreme Classification in Log Memory Using Count-Min Sketch: A Case Study of Amazon Search with 50m Products Tharun Kumar Reddy Medini, Qixuan Huang, Yiqiu Wang, Vijai Mohan, Anshumali Shrivastava

NeurIPS 2019 Fast and Accurate Stochastic Gradient Estimation Beidi Chen, Yingchen Xu, Anshumali Shrivastava

AAAI 2019 Scaling-up Split-Merge MCMC with Locality Sensitive Sampling (LSS) Chen Luo, Anshumali Shrivastava

UAI 2018 Densified Winner Take All (WTA) Hashing for Sparse Datasets Beidi Chen, Anshumali Shrivastava

ICML 2018 MISSION: Ultra Large-Scale Feature Selection Using Count-Sketches Amirali Aghazadeh, Ryan Spring, Daniel Lejeune, Gautam Dasarathy, Anshumali Shrivastava, Baraniuk

NeurIPS 2018 Topkapi: Parallel and Fast Sketches for Finding Top-K Frequent Elements Ankush Mandal, He Jiang, Anshumali Shrivastava, Vivek Sarkar

ICML 2017 Optimal Densification for Fast and Accurate Minwise Hashing Anshumali Shrivastava

IJCAI 2017 RHash: Robust Hashing via L_infinity-Norm Distortion Amirali Aghazadeh, Andrew S. Lan, Anshumali Shrivastava, Richard G. Baraniuk

NeurIPS 2016 Simple and Efficient Weighted Minwise Hashing Anshumali Shrivastava

UAI 2015 Improved Asymmetric Locality Sensitive Hashing (ALSH) for Maximum Inner Product Search (MIPS) Anshumali Shrivastava, Ping Li

NeurIPS 2014 Asymmetric LSH (ALSH) for Sublinear Time Maximum Inner Product Search (MIPS) Anshumali Shrivastava, Ping Li

ICML 2014 Coding for Random Projections Ping Li, Michael Mitzenmacher, Anshumali Shrivastava

ICML 2014 Densifying One Permutation Hashing via Rotation for Fast near Neighbor Search Anshumali Shrivastava, Ping Li

UAI 2014 Improved Densification of One Permutation Hashing Anshumali Shrivastava, Ping Li

AISTATS 2014 In Defense of Minhash over Simhash Anshumali Shrivastava, Ping Li

NeurIPS 2013 Beyond Pairwise: Provably Fast Algorithms for Approximate $k$-Way Similarity Search Anshumali Shrivastava, Ping Li

ECML-PKDD 2012 Fast near Neighbor Search in High-Dimensional Binary Data Anshumali Shrivastava, Ping Li

NeurIPS 2011 Hashing Algorithms for Large-Scale Learning Ping Li, Anshumali Shrivastava, Joshua L. Moore, Arnd C. König