Anshumali Shrivastava

210 papers A* 53A 12B 3C 2Journal 112Unranked 27

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	SOCKET: SOft Collison Kernel EsTimator for Sparse Attention. CoRR Sahil Joshi, Agniva Chowdhury, Wyatt Bellinger, Amar Kanakamedala, Ekam Singh, Hoang Anh Duy Le, Aditya Desai, Anshumali Shrivastava
2026	J	`jnl`	Scout Before You Attend: Sketch-and-Walk Sparse Attention for Efficient LLM Inference. CoRR Hoang Anh Duy Le, Sahil Joshi, Zeyu Yang, Zhaozhuo Xu, Anshumali Shrivastava
2025	J	`jnl`	70% Size, 100% Accuracy: Lossless LLM Compression for Efficient GPU Inference via Dynamic-Length Float. CoRR Tianyi Zhang, Yang Sui, Shaochen Zhong, Vipin Chaudhary, Xia Hu, Anshumali Shrivastava
2025	—	`conf`	CoVE: Compressed Vocabulary Expansion Makes Better LLM-based Recommender Systems. ACL (Findings) Haochen Zhang, Tianyi Zhang, Junze Yin, Oren Gal, Anshumali Shrivastava, Vladimir Braverman
2025	J	`jnl`	CoVE: Compressed Vocabulary Expansion Makes Better LLM-based Recommender Systems. CoRR Haochen Zhang, Tianyi Zhang, Junze Yin, Oren Gal, Anshumali Shrivastava, Vladimir Braverman
2025	J	`jnl`	I3S: Importance Sampling Subspace Selection for Low-Rank Optimization in LLM Pretraining. CoRR Haochen Zhang, Junze Yin, Guanchu Wang, Zirui Liu, Tianyi Zhang, Anshumali Shrivastava, Lin Yang, Vladimir Braverman
2025	—	`conf`	IDentity with Locality: An Ideal Hash for Gene Sequence Search. KDD (1) Tianyi Zhang, Gaurav Gupta, Aditya Desai, Anshumali Shrivastava
2025	A*	`conf`	LeanQuant: Accurate and Scalable Large Language Model Quantization with Loss-error-aware Grid. ICLR Tianyi Zhang, Anshumali Shrivastava
2025	J	`jnl`	REFRAG: Rethinking RAG based Decoding. CoRR Xiaoqiang Lin, Aritra Ghosh, Bryan Kian Hsiang Low, Anshumali Shrivastava, Vijai Mohan
2025	J	`jnl`	Replacing Softmax Similarity with a Sharpened Angular Similarity: Theory and Practice of Scaling To Billion-Context Attention. CoRR Sahil Joshi, Agniva Chowdhury, Amar Kanakamedala, Ekam Singh, Evan Tu, Anshumali Shrivastava
2025	A*	`conf`	Sketch to Adapt: Fine-Tunable Sketches for Efficient LLM Adaptation. ICML Tianyi Zhang, Junda Su, Aditya Desai, Oscar Wu, Zhaozhuo Xu, Anshumali Shrivastava
2025	J	`jnl`	To Compress or Not? Pushing the Frontier of Lossless GenAI Model Weights Compression with Exponent Concentration. CoRR Zeyu Yang, Tianyi Zhang, Jianwen Xie, Chuan Li, Zhaozhuo Xu, Anshumali Shrivastava
2025	A*	`conf`	ZEN: Empowering Distributed Training with Sparsity-driven Data Synchronization. OSDI Zhuang Wang, Zhaozhuo Xu, Jingyi Xi, Yuke Wang, Anshumali Shrivastava, T. S. Eugene Ng
2024	J	`jnl`	IDentity with Locality: An ideal hash for gene sequence search. CoRR Aditya Desai, Gaurav Gupta, Tianyi Zhang, Anshumali Shrivastava
2024	A*	`conf`	In defense of parameter sharing for model-compression. ICLR Aditya Desai, Anshumali Shrivastava
2024	A*	`conf`	KV Cache is 1 Bit Per Channel: Efficient Large Language Model Inference with Coupled Quantization. NeurIPS Tianyi Zhang, Jonah Yi, Zhaozhuo Xu, Anshumali Shrivastava
2024	J	`jnl`	KV Cache is 1 Bit Per Channel: Efficient Large Language Model Inference with Coupled Quantization. CoRR Tianyi Zhang, Jonah Yi, Zhaozhuo Xu, Anshumali Shrivastava
2024	J	`jnl`	LeanQuant: Accurate Large Language Model Quantization with Loss-Error-Aware Grid. CoRR Tianyi Zhang, Anshumali Shrivastava
2024	A*	`conf`	Learning Scalable Structural Representations for Link Prediction with Bloom Signatures. WWW Tianyi Zhang, Haoteng Yin, Rongzhe Wei, Pan Li, Anshumali Shrivastava
2024	A*	`conf`	NoMAD-Attention: Efficient LLM Inference on CPUs Through Multiply-add-free Attention. NeurIPS Tianyi Zhang, Jonah Yi, Bowen Yao, Zhaozhuo Xu, Anshumali Shrivastava
2024	J	`jnl`	NoMAD-Attention: Efficient LLM Inference on CPUs Through Multiply-add-free Attention. CoRR Tianyi Zhang, Jonah Wonkyu Yi, Bowen Yao, Zhaozhuo Xu, Anshumali Shrivastava
2024	A*	`conf`	SS1: Accelerating Inference with Fast and Expressive Sketch Structured Transform. NeurIPS Aditya Desai, Kimia Saedi, Apoorv Walia, Jihyeong Lee, Keren Zhou, Anshumali Shrivastava
2024	A*	`conf`	Soft Prompt Recovers Compressed LLMs, Transferably. ICML Zhaozhuo Xu, Zirui Liu, Beidi Chen, Shaochen (Henry) Zhong, Yuxin Tang, Jue Wang, Kaixiong Zhou, Xia Hu, Anshumali Shrivastava
2024	J	`jnl`	SpaLLM: Unified Compressive Adaptation of Large Language Models with Sketching. CoRR Tianyi Zhang, Junda Su, Oscar Wu, Zhaozhuo Xu, Anshumali Shrivastava
2024	J	`jnl`	Wisdom of Committee: Distilling from Foundation Model to Specialized Application Model. CoRR Zichang Liu, Qingyun Liu, Yuening Li, Liang Liu, Anshumali Shrivastava, Shuchao Bi, Lichan Hong, Ed H. Chi, Zhe Zhao
2023	A	`conf`	A Tale of Two Efficient Value Iteration Algorithms for Solving Linear MDPs with Large Action Space. AISTATS Zhaozhuo Xu, Zhao Song, Anshumali Shrivastava
2023	J	`jnl`	A Theoretical Analysis Of Nearest Neighbor Search On Approximate Near Neighbor Graph. CoRR Anshumali Shrivastava, Zhao Song, Zhaozhuo Xu
2023	J	`jnl`	Adaptive Sampling for Deep Learning via Efficient Nonparametric Proxies. CoRR Shabnam Daghaghi, Benjamin Coleman, Benito Geordie, Anshumali Shrivastava
2023	J	`jnl`	Algorithmic Foundations of Inexact Computing. CoRR John Augustine, Dror Fried, Krishna V. Palem, Duc-Hung Pham, Anshumali Shrivastava
2023	J	`jnl`	BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Neural Networks on Commodity CPU Hardware. CoRR 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
2023	A	`conf`	BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware. CIKM 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
2023	J	`jnl`	CAPS: A Practical Partition Index for Filtered Similarity Search. CoRR Gaurav Gupta, Jonah Yi, Benjamin Coleman, Chen Luo, Vihan Lakshman, Anshumali Shrivastava
2023	J	`jnl`	CARAMEL: A Succinct Read-Only Lookup Table via Compressed Static Functions. CoRR Benjamin Coleman, David Torres Ramos, Vihan Lakshman, Chen Luo, Anshumali Shrivastava
2023	J	`jnl`	Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt. CoRR Zhaozhuo Xu, Zirui Liu, Beidi Chen, Yuxin Tang, Jue Wang, Kaixiong Zhou, Xia Hu, Anshumali Shrivastava
2023	J	`jnl`	Contractive error feedback for gradient compression. CoRR Bingcong Li, Shuai Zheng, Parameswaran Raman, Anshumali Shrivastava, Georgios B. Giannakis
2023	A*	`conf`	DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries. NeurIPS Joshua Engels, Benjamin Coleman, Vihan Lakshman, Anshumali Shrivastava
2023	A*	`conf`	Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. ICML Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Ré, Beidi Chen
2023	J	`jnl`	Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. CoRR Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Ré, Beidi Chen
2023	A	`conf`	From Research to Production: Towards Scalable and Sustainable Neural Recommendation Models on Commodity CPU Hardware. RecSys Anshumali Shrivastava, Vihan Lakshman, Tharun Medini, Nicholas Meisburger, Joshua Engels, David Torres Ramos, Benito Geordie, Pratik Pranav, Shubh Gupta, Yashwanth Adunukota, Siddharth Jain
2023	A	`conf`	Graph Self-supervised Learning via Proximity Distribution Minimization. UAI Tianyi Zhang, Zhenwei Dai, Zhaozhuo Xu, Anshumali Shrivastava
2023	A*	`conf`	Hardware-Aware Compression with Random Operation Access Specific Tile (ROAST) Hashing. ICML Aditya Desai, Keren Zhou, Anshumali Shrivastava
2023	J	`jnl`	Heterogeneous federated collaborative filtering using FAIR: Federated Averaging in Random Subspaces. CoRR Aditya Desai, Benjamin Meisburger, Zichang Liu, Anshumali Shrivastava
2023	J	`jnl`	In defense of parameter sharing for model-compression. CoRR Aditya Desai, Anshumali Shrivastava
2023	A*	`conf`	Learning Multimodal Data Augmentation in Feature Space. ICLR Zichang Liu, Zhiqiang Tang, Xingjian Shi, Aston Zhang, Mu Li, Anshumali Shrivastava, Andrew Gordon Wilson
2023	J	`jnl`	Learning Scalable Structural Representations for Link Prediction with Bloom Signatures. CoRR Tianyi Zhang, Haoteng Yin, Rongzhe Wei, Pan Li, Anshumali Shrivastava
2023	B	`conf`	Near Neighbor Search for Constraint Queries. IEEE Big Data Gaurav Gupta, Anup B. Rao, Tung Mai, Ryan A. Rossi, Xiang Chen, Saayan Mitra, Anshumali Shrivastava
2023	A*	`conf`	One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning. NeurIPS Zichang Liu, Zhaozhuo Xu, Benjamin Coleman, Anshumali Shrivastava
2023	A*	`conf`	Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time. NeurIPS Zichang Liu, Aditya Desai, Fangshuo Liao, Weitao Wang, Victor Xie, Zhaozhuo Xu, Anastasios Kyrillidis, Anshumali Shrivastava
2023	J	`jnl`	Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time. CoRR Zichang Liu, Aditya Desai, Fangshuo Liao, Weitao Wang, Victor Xie, Zhaozhuo Xu, Anastasios Kyrillidis, Anshumali Shrivastava
2023	J	`jnl`	Zen: Near-Optimal Sparse Tensor Synchronization for Distributed DNN Training. CoRR Zhuang Wang, Zhaozhuo Xu, Anshumali Shrivastava, T. S. Eugene Ng
2022	A*	`conf`	BLISS: A Billion scale Index using Iterative Re-partitioning. KDD Gaurav Gupta, Tharun Medini, Anshumali Shrivastava, Alexander J. Smola
2022	J	`jnl`	Coordinated Science Laboratory 70th Anniversary Symposium: The Future of Computing. CoRR Klara Nahrstedt, Naresh R. Shanbhag, Vikram S. Adve, Nancy M. Amato, Romit Roy Choudhury, Carl A. Gunter, Nam Sung Kim, Olgica Milenkovic, Sayan Mitra, Lav R. Varshney, Yurii Vlasov, Sarita V. Adve, Rashid Bashir, Andreas Cangellaris, James DiCarlo, Katie Driggs-Campbell, Nick Feamster, Mattia Gazzola, Karrie Karahalios, Sanmi Koyejo, Paul G. Kwiat, Bo Li, Negar Mehr, Ravish Mehra, Andrew Miller, Daniela Rus, Alexander G. Schwing, Anshumali Shrivastava
2022	J	`jnl`	DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries. CoRR Joshua Engels, Benjamin Coleman, Vihan Lakshman, Anshumali Shrivastava
2022	A*	`conf`	DRAGONN: Distributed Randomized Approximate Gradients of Neural Networks. ICML Zhuang Wang, Zhaozhuo Xu, Xinyu Crystal Wu, Anshumali Shrivastava, T. S. Eugene Ng
2022	J	`jnl`	Distributed SLIDE: Enabling Training Large Neural Networks on Low Bandwidth and Simple CPU-Clusters via Model Parallelism and Sparsity. CoRR Minghao Yan, Nicholas Meisburger, Tharun Medini, Anshumali Shrivastava
2022	J	`jnl`	Efficient model compression with Random Operation Access Specific Tile (ROAST) hashing. CoRR Aditya Desai, Keren Zhou, Anshumali Shrivastava
2022	A*	`conf`	Graph Reordering for Cache-Efficient Near Neighbor Search. NeurIPS Benjamin Coleman, Santiago Segarra, Alexander J. Smola, Anshumali Shrivastava
2022	—	`conf`	HALOS: Hashing Large Output Space for Cheap Inference. MLSys Zichang Liu, Zhaozhuo Xu, Alan Baonan Ji, Junyan Zhang, Jonathan Li, Beidi Chen, Anshumali Shrivastava
2022	J	`jnl`	Learning Multimodal Data Augmentation in Feature Space. CoRR Zichang Liu, Zhiqiang Tang, Xingjian Shi, Aston Zhang, Mu Li, Anshumali Shrivastava, Andrew Gordon Wilson
2022	A*	`conf`	Learning to Retrieve Relevant Experiences for Motion Planning. ICRA Constantinos Chamzas, Aedan Cullen, Anshumali Shrivastava, Lydia E. Kavraki
2022	J	`jnl`	Learning to Retrieve Relevant Experiences for Motion Planning. CoRR Constantinos Chamzas, Aedan Cullen, Anshumali Shrivastava, Lydia E. Kavraki
2022	A*	`conf`	One-Pass Diversified Sampling with Application to Terabyte-Scale Genomic Sequence Streams. ICML Benjamin Coleman, Benito Geordie, Li Chou, Ryan A. Leo Elworth, Todd J. Treangen, Anshumali Shrivastava
2022	J	`jnl`	Optimizing Learned Bloom Filters: How Much Should Be Learned? IEEE Embed. Syst. Lett. Zhenwei Dai, Anshumali Shrivastava, Pedro Reviriego, José Alberto Hernández
2022	—	`conf`	ROSE: Robust Caches for Amazon Product Search. WWW (Companion Volume) Chen Luo, Vihan Lakshman, Anshumali Shrivastava, Tianyu Cao, Sreyashi Nag, Rahul Goutam, Hanqing Lu, Yiwei Song, Bing Yin
2022	—	`conf`	Random Offset Block Embedding (ROBE) for compressed embedding tables in deep learning recommendation systems. MLSys Aditya Desai, Li Chou, Anshumali Shrivastava
2022	A*	`conf`	Retaining Knowledge for Learning with Dynamic Definition. NeurIPS Zichang Liu, Benjamin Coleman, Tianyi Zhang, Anshumali Shrivastava
2022	—	`conf`	Structural Contrastive Representation Learning for Zero-shot Multi-label Text Classification. EMNLP (Findings) Tianyi Zhang, Zhaozhuo Xu, Tharun Medini, Anshumali Shrivastava
2022	A*	`conf`	The trade-offs of model size in large recommendation models : 100GB to 10MB Criteo-tb DLRM model. NeurIPS Aditya Desai, Anshumali Shrivastava
2022	J	`jnl`	The trade-offs of model size in large recommendation models : A 10000 × compressed criteo-tb DLRM model (100 GB parameters to mere 10MB). CoRR Aditya Desai, Anshumali Shrivastava
2021	A*	`conf`	A One-Pass Distributed and Private Sketch for Kernel Sums with Applications to Machine Learning at Scale. CCS Benjamin Coleman, Anshumali Shrivastava
2021	A*	`conf`	A Tale of Two Efficient and Informative Negative Sampling Distributions. ICML Shabnam Daghaghi, Tharun Medini, Nicholas Meisburger, Beidi Chen, Mengnan Zhao, Anshumali Shrivastava
2021	—	`conf`	Accelerating SLIDE Deep Learning on Modern CPUs: Vectorization, Quantizations, Memory Optimizations, and More. MLSys Shabnam Daghaghi, Nicholas Meisburger, Mengnan Zhao, Anshumali Shrivastava
2021	J	`jnl`	Accelerating SLIDE Deep Learning on Modern CPUs: Vectorization, Quantizations, Memory Optimizations, and More. CoRR Shabnam Daghaghi, Nicholas Meisburger, Mengnan Zhao, Yong Wu, Sameh Gobriel, Charlie Tai, Anshumali Shrivastava
2021	—	`conf`	Active Sampling Count Sketch (ASCS) for Online Sparse Estimation of a Trillion Scale Covariance Matrix. SIGMOD Conference Zhenwei Dai, Aditya Desai, Reinhard Heckel, Anshumali Shrivastava
2021	J	`jnl`	Beyond Convolutions: A Novel Deep Learning Approach for Raw Seismic Data Ingestion. CoRR Zhaozhuo Xu, Aditya Desai, Menal Gupta, Anu Chandran, Antoine Vial-Aussavy, Anshumali Shrivastava
2021	A*	`conf`	Breaking the Linear Iteration Cost Barrier for Some Well-known Conditional Gradient Methods Using MaxIP Data-structures. NeurIPS Zhaozhuo Xu, Zhao Song, Anshumali Shrivastava
2021	J	`jnl`	Breaking the Linear Iteration Cost Barrier for Some Well-known Conditional Gradient Methods Using MaxIP Data-structures. CoRR Anshumali Shrivastava, Zhao Song, Zhaozhuo Xu
2021	J	`jnl`	Density Sketches for Sampling and Estimation. CoRR Aditya Desai, Benjamin Coleman, Anshumali Shrivastava
2021	J	`jnl`	Efficient Inference via Universal LSH Kernel. CoRR Zichang Liu, Benjamin Coleman, Anshumali Shrivastava
2021	—	`conf`	Efficient and Less Centralized Federated Learning. ECML/PKDD (1) Li Chou, Zichang Liu, Zhuang Wang, Anshumali Shrivastava
2021	J	`jnl`	Efficient and Less Centralized Federated Learning. CoRR Li Chou, Zichang Liu, Zhuang Wang, Anshumali Shrivastava
2021	—	`conf`	Fast Processing and Querying of 170TB of Genomics Data via a Repeated And Merged BloOm Filter (RAMBO). SIGMOD Conference Gaurav Gupta, Minghao Yan, Benjamin Coleman, Bryce Kille, Ryan A. Leo Elworth, Tharun Medini, Todd J. Treangen, Anshumali Shrivastava
2021	J	`jnl`	Federated Multiple Label Hashing (FedMLH): Communication Efficient Federated Learning on Extreme Classification Tasks. CoRR Zhenwei Dai, Chen Dun, Yuxin Tang, Anastasios Kyrillidis, Anshumali Shrivastava
2021	J	`jnl`	Graph Reordering for Cache-Efficient Near Neighbor Search. CoRR Benjamin Coleman, Santiago Segarra, Anshumali Shrivastava, Alex Smola
2021	J	`jnl`	IRLI: Iterative Re-partitioning for Learning to Index. CoRR Gaurav Gupta, Tharun Medini, Anshumali Shrivastava, Alexander J. Smola
2021	C	`conf`	Learned Bloom Filters in Adversarial Environments: A Malicious URL Detection Use-Case. HPSR Pedro Reviriego, José Alberto Hernández, Zhenwei Dai, Anshumali Shrivastava
2021	A*	`conf`	Learning Sampling Distributions Using Local 3D Workspace Decompositions for Motion Planning in High Dimensions. ICRA Constantinos Chamzas, Zachary Kingston, Carlos Quintero-Peña, Anshumali Shrivastava, Lydia E. Kavraki
2021	A*	`conf`	Locality Sensitive Teaching. NeurIPS Zhaozhuo Xu, Beidi Chen, Chaojian Li, Weiyang Liu, Le Song, Yingyan Lin, Anshumali Shrivastava
2021	A*	`conf`	MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training. ICLR Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan Lingjie Li, Tri Dao, Zhao Song, Anshumali Shrivastava, Christopher Ré
2021	A	`conf`	Neighbor Oblivious Learning (NObLe) for Device Localization and Tracking. DATE Zichang Liu, Li Chou, Anshumali Shrivastava
2021	J	`jnl`	PairConnect: A Compute-Efficient MLP Alternative to Attention. CoRR Zhaozhuo Xu, Minghao Yan, Junyan Zhang, Anshumali Shrivastava
2021	A*	`conf`	Practical Near Neighbor Search via Group Testing. NeurIPS Joshua Engels, Benjamin Coleman, Anshumali Shrivastava
2021	J	`jnl`	Practical Near Neighbor Search via Group Testing. CoRR Joshua Engels, Benjamin Coleman, Anshumali Shrivastava
2021	J	`jnl`	Random Offset Block Embedding Array (ROBE) for CriteoTB Benchmark MLPerf DLRM Model : 1000× Compression and 2.7× Faster Inference. CoRR Aditya Desai, Li Chou, Anshumali Shrivastava
2021	A*	`conf`	Raw Nav-merge Seismic Data to Subsurface Properties with MLP based Multi-Modal Information Unscrambler. NeurIPS Aditya Desai, Zhaozhuo Xu, Menal Gupta, Anu Chandran, Antoine Vial-Aussavy, Anshumali Shrivastava
2021	A*	`conf`	Revisiting Consistent Hashing with Bounded Loads. AAAI John Chen, Benjamin Coleman, Anshumali Shrivastava
2021	A	`conf`	SDM-Net: A simple and effective model for generalized zero-shot learning. UAI Shabnam Daghaghi, Tharun Medini, Anshumali Shrivastava
2021	A*	`conf`	SOLAR: Sparse Orthogonal Learned and Random Embeddings. ICLR Tharun Medini, Beidi Chen, Anshumali Shrivastava
2021	J	`jnl`	Satellite Images and Deep Learning to Identify Discrepancy in Mailing Addresses with Applications to Census 2020 in Houston. CoRR Zhaozhuo Xu, Alan Baonan Ji, Andrew Woods, Beidi Chen, Anshumali Shrivastava
2021	J	`jnl`	Semantically Constrained Memory Allocation (SCMA) for Embedding in Efficient Recommendation Systems. CoRR Aditya Desai, Yanzhou Pan, Kuangyuan Sun, Li Chou, Anshumali Shrivastava
2021	J	`jnl`	Solving hybrid Boolean constraints in continuous space via multilinear Fourier expansions. Artif. Intell. Anastasios Kyrillidis, Anshumali Shrivastava, Moshe Y. Vardi, Zhiwei Zhang
2021	J	`jnl`	Sublinear Least-Squares Value Iteration via Locality Sensitive Hashing. CoRR Anshumali Shrivastava, Zhao Song, Zhaozhuo Xu
2020	J	`jnl`	A Constant-time Adaptive Negative Sampling. CoRR Shabnam Daghaghi, Tharun Medini, Beidi Chen, Mengnan Zhao, Anshumali Shrivastava
2020	J	`jnl`	A One-Pass Private Sketch for Most Machine Learning Tasks. CoRR Benjamin Coleman, Anshumali Shrivastava
2020	J	`jnl`	Active Sampling Count Sketch (ASCS) for Online Sparse Estimation of a Trillion Scale Covariance Matrix. CoRR Zhenwei Dai, Aditya Desai, Reinhard Heckel, Anshumali Shrivastava
2020	A*	`conf`	Adaptive Learned Bloom Filter (Ada-BF): Efficient Utilization of the Classifier with Application to Real-Time Information Filtering on the Web. NeurIPS Zhenwei Dai, Anshumali Shrivastava
2020	A*	`conf`	Angular Visual Hardness. ICML Beidi Chen, Weiyang Liu, Zhiding Yu, Jan Kautz, Anshumali Shrivastava, Animesh Garg, Animashree Anandkumar
2020	J	`jnl`	Bloom Origami Assays: Practical Group Testing. CoRR Louis Abraham, Gary Bécigneul, Benjamin Coleman, Bernhard Schölkopf, Anshumali Shrivastava, Alexander J. Smola
2020	J	`jnl`	Climbing the WOL: Training for Cheaper Inference. CoRR Zichang Liu, Zhaozhuo Xu, Alan Baonan Ji, Jonathan Li, Beidi Chen, Anshumali Shrivastava
2020	J	`jnl`	Distributed Tera-Scale Similarity Search with MPI: Provably Efficient Similarity Search over billions without a Single Distance Computation. CoRR Nicholas Meisburger, Anshumali Shrivastava
2020	A*	`conf`	FourierSAT: A Fourier Expansion-Based Algebraic Framework for Solving Hybrid Boolean Constraints. AAAI Anastasios Kyrillidis, Anshumali Shrivastava, Moshe Y. Vardi, Zhiwei Zhang
2020	J	`jnl`	Learning Sampling Distributions Using Local 3D Workspace Decompositions for Motion Planning in High Dimensions. CoRR Constantinos Chamzas, Zachary Kingston, Carlos Quintero-Peña, Anshumali Shrivastava, Lydia E. Kavraki
2020	A*	`conf`	Mutual Information Estimation using LSH Sampling. IJCAI Ryan Spring, Anshumali Shrivastava
2020	J	`jnl`	Neighbor Oblivious Learning (NObLe) for Device Localization and Tracking. CoRR Zichang Liu, Li Chou, Anshumali Shrivastava
2020	J	`jnl`	Privacy Adversarial Network: Representation Learning for Mobile Data Privacy. CoRR Sicong Liu, Junzhao Du, Anshumali Shrivastava, Lin Zhong
2020	—	`conf`	SLIDE : In Defense of Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning Systems. MLSys Beidi Chen, Tharun Medini, James Farwell, Sameh Gobriel, Tsung-Yuan Charlie Tai, Anshumali Shrivastava
2020	J	`jnl`	SOLAR: Sparse Orthogonal Learned and Random Embeddings. CoRR Tharun Medini, Beidi Chen, Anshumali Shrivastava
2020	J	`jnl`	STORM: Foundations of End-to-End Empirical Risk Minimization on the Edge. CoRR Benjamin Coleman, Gaurav Gupta, John Chen, Anshumali Shrivastava
2020	A*	`conf`	Sub-linear Memory Sketches for Near Neighbor Search on Streaming Data. ICML Benjamin Coleman, Richard G. Baraniuk, Anshumali Shrivastava
2020	A*	`conf`	Sub-linear RACE Sketches for Approximate Kernel Density Estimation on Streaming Data. WWW Benjamin Coleman, Anshumali Shrivastava
2019	J	`jnl`	Adaptive Learned Bloom Filter (Ada-BF): Efficient Utilization of the Classifier. CoRR Zhenwei Dai, Anshumali Shrivastava
2019	J	`jnl`	Angular Visual Hardness. CoRR Beidi Chen, Weiyang Liu, Animesh Garg, Zhiding Yu, Anshumali Shrivastava, Jan Kautz, Anima Anandkumar
2019	J	`jnl`	Better accuracy with quantified privacy: representations learned via reconstructive adversarial network. CoRR Sicong Liu, Anshumali Shrivastava, Junzhao Du, Lin Zhong
2019	A*	`conf`	Compressing Gradient Optimizers via Count-Sketches. ICML Ryan Spring, Anastasios Kyrillidis, Vijai Mohan, Anshumali Shrivastava
2019	J	`jnl`	Compressing Gradient Optimizers via Count-Sketches. CoRR Ryan Spring, Anastasios Kyrillidis, Vijai Mohan, Anshumali Shrivastava
2019	—	`conf`	Cross-Modal Mapping for Generalized Zero-Shot Learning by Soft-Labeling. ViGIL@NeurIPS Shabnam Daghaghi, Anshumali Shrivastava, Tharun Medini
2019	A*	`conf`	Extreme Classification in Log Memory using Count-Min Sketch: A Case Study of Amazon Search with 50M Products. NeurIPS Tharun Medini, Qixuan Huang, Yiqiu Wang, Vijai Mohan, Anshumali Shrivastava
2019	J	`jnl`	Extreme Classification in Log Memory using Count-Min Sketch: A Case Study of Amazon Search with 50M Products. CoRR Tharun Medini, Qixuan Huang, Yiqiu Wang, Vijai Mohan, Anshumali Shrivastava
2019	J	`jnl`	Fast Processing and Querying of 170TB of Genomics Data via a Repeated And Merged BloOm Filter (RAMBO). CoRR Gaurav Gupta, Minghao Yan, Benjamin Coleman, Bryce Kille, Ryan A. Leo Elworth, Tharun Medini, Todd J. Treangen, Anshumali Shrivastava
2019	A*	`conf`	Fast and Accurate Stochastic Gradient Estimation. NeurIPS Beidi Chen, Yingchen Xu, Anshumali Shrivastava
2019	J	`jnl`	FourierSAT: A Fourier Expansion-Based Algebraic Framework for Solving Hybrid Boolean Constraints. CoRR Anastasios Kyrillidis, Anshumali Shrivastava, Moshe Y. Vardi, Zhiwei Zhang
2019	J	`jnl`	Learning Feasibility for Task and Motion Planning in Tabletop Environments. IEEE Robotics Autom. Lett. Andrew M. Wells, Neil T. Dantam, Anshumali Shrivastava, Lydia E. Kavraki
2019	J	`jnl`	Lsh-sampling Breaks the Computation Chicken-and-egg Loop in Adaptive Stochastic Gradient Estimation. CoRR Beidi Chen, Yingchen Xu, Anshumali Shrivastava
2019	J	`jnl`	Privacy Adversarial Network: Representation Learning for Mobile Data Privacy. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Sicong Liu, Junzhao Du, Anshumali Shrivastava, Lin Zhong
2019	J	`jnl`	RACE: Sub-Linear Memory Sketches for Approximate Near-Neighbor Search on Streaming Data. CoRR Benjamin Coleman, Anshumali Shrivastava, Richard G. Baraniuk
2019	J	`jnl`	RAMBO: Repeated And Merged Bloom Filter for Multiple Set Membership Testing (MSMT) in Sub-linear time. CoRR Gaurav Gupta, Benjamin Coleman, Tharun Medini, Vijai Mohan, Anshumali Shrivastava
2019	J	`jnl`	Revisiting Consistent Hashing with Bounded Loads. CoRR John Chen, Benjamin Coleman, Anshumali Shrivastava
2019	J	`jnl`	SLIDE : In Defense of Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning Systems. CoRR Beidi Chen, Tharun Medini, Anshumali Shrivastava
2019	A*	`conf`	Scaling-Up Split-Merge MCMC with Locality Sensitive Sampling (LSS). AAAI Chen Luo, Anshumali Shrivastava
2019	J	`jnl`	Semantic Similarity Based Softmax Classifier for Zero-Shot Learning. CoRR Shabnam Daghaghi, Tharun Medini, Anshumali Shrivastava
2019	J	`jnl`	Sub-Linear Privacy-Preserving Near-Neighbor Search. IACR Cryptol. ePrint Arch. M. Sadegh Riazi, Beidi Chen, Anshumali Shrivastava, Dan S. Wallach, Farinaz Koushanfar
2019	J	`jnl`	Sub-linear RACE Sketches for Approximate Kernel Density Estimation on Streaming Data. CoRR Benjamin Coleman, Anshumali Shrivastava
2019	A*	`conf`	Using Local Experiences for Global Motion Planning. ICRA Constantinos Chamzas, Anshumali Shrivastava, Lydia E. Kavraki
2019	J	`jnl`	Using Local Experiences for Global Motion Planning. CoRR Constantinos Chamzas, Anshumali Shrivastava, Lydia E. Kavraki
2018	A*	`conf`	Arrays of (locality-sensitive) Count Estimators (ACE): Anomaly Detection on the Edge. WWW Chen Luo, Anshumali Shrivastava
2018	A	`conf`	Densified Winner Take All (WTA) Hashing for Sparse Datasets. UAI Beidi Chen, Anshumali Shrivastava
2018	J	`jnl`	Extreme Classification in Log Memory. CoRR Qixuan Huang, Yiqiu Wang, Tharun Medini, Anshumali Shrivastava
2018	B	`conf`	Jaccard Affiliation Graph (JAG) Model For Explaining Overlapping Community Behaviors. ASONAM Chen Luo, Anshumali Shrivastava
2018	—	`conf`	Lsh-Sampling breaks the Computational chicken-and-egg Loop in adaptive stochastic Gradient estimation. ICLR (Workshop) Beidi Chen, Yingchen Xu, Anshumali Shrivastava
2018	A*	`conf`	MISSION: Ultra Large-Scale Feature Selection using Count-Sketches. ICML Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava, Richard G. Baraniuk
2018	J	`jnl`	MISSION: Ultra Large-Scale Feature Selection using Count-Sketches. CoRR Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava, Richard G. Baraniuk
2018	J	`jnl`	Probabilistic Blocking with An Application to the Syrian Conflict. CoRR Rebecca C. Steorts, Anshumali Shrivastava
2018	C	`conf`	Probabilistic Blocking with an Application to the Syrian Conflict. PSD Rebecca C. Steorts, Anshumali Shrivastava
2018	—	`conf`	Randomized Algorithms Accelerated over CPU-GPU for Ultra-High Dimensional Similarity Search. SIGMOD Conference Yiqiu Wang, Anshumali Shrivastava, Jonathan Wang, Junghee Ryu
2018	—	`conf`	Scalable Estimation via LSH Samplers (LSS). ICLR (Workshop) Ryan Spring, Anshumali Shrivastava
2018	J	`jnl`	Scaling-up Split-Merge MCMC with Locality Sensitive Sampling (LSS). CoRR Chen Luo, Anshumali Shrivastava
2018	A*	`conf`	TINET: Learning Invariant Networks via Knowledge Transfer. KDD Chen Luo, Zhengzhang Chen, Lu-An Tang, Anshumali Shrivastava, Zhichun Li, Haifeng Chen, Jieping Ye
2018	A*	`conf`	Topkapi: Parallel and Fast Sketches for Finding Top-K Frequent Elements. NeurIPS Ankush Mandal, He Jiang, Anshumali Shrivastava, Vivek Sarkar
2018	—	`conf`	Training 100, 000 Classes on a Single Titan X in 7 Hours or 15 Minutes with 25 Titan Xs. WWW (Companion Volume) Anshumali Shrivastava
2018	J	`jnl`	Want to bring a community together? Create more sub-communities. CoRR Chen Luo, Anshumali Shrivastava
2017	J	`jnl`	A New Unbiased and Efficient Class of LSH-Based Samplers and Estimators for Partition Function Computation in Log-Linear Models. CoRR Ryan Spring, Anshumali Shrivastava
2017	J	`jnl`	Accelerating Dependency Graph Learning from Heterogeneous Categorical Event Streams via Knowledge Transfer. CoRR Chen Luo, Zhengzhang Chen, Lu-An Tang, Anshumali Shrivastava, Zhichun Li
2017	J	`jnl`	Arrays of (locality-sensitive) Count Estimators (ACE): High-Speed Anomaly Detection via Cache Lookups. CoRR Chen Luo, Anshumali Shrivastava
2017	J	`jnl`	FLASH: Randomized Algorithms Accelerated over CPU-GPU for Ultra-High Dimensional Similarity Search. CoRR Yiqiu Wang, Anshumali Shrivastava, Junghee Ryu
2017	A	`conf`	Location detection for navigation using IMUs with a map through coarse-grained machine learning. DATE E. J. Jose Gonzalez, Chen Luo, Anshumali Shrivastava, Krishna V. Palem, Yongshik Moon, Soonhyun Noh, Daedong Park, Seongsoo Hong
2017	A*	`conf`	Optimal Densification for Fast and Accurate Minwise Hashing. ICML Anshumali Shrivastava
2017	J	`jnl`	Optimal Densification for Fast and Accurate Minwise Hashing. CoRR Anshumali Shrivastava
2017	A*	`conf`	RHash: Robust Hashing via L_infinity-norm Distortion. IJCAI Amirali Aghazadeh, Andrew S. Lan, Anshumali Shrivastava, Richard G. Baraniuk
2017	A*	`conf`	Scalable and Sustainable Deep Learning via Randomized Hashing. KDD Ryan Spring, Anshumali Shrivastava
2017	J	`jnl`	Unique Entity Estimation with Application to the Syrian Conflict. CoRR Beidi Chen, Anshumali Shrivastava, Rebecca C. Steorts
2016	J	`jnl`	2-Bit Random Projections, NonLinear Estimators, and Approximate Near Neighbor Search. CoRR Ping Li, Michael Mitzenmacher, Anshumali Shrivastava
2016	—	`conf`	CaPSuLe: A camera-based positioning system using learning. SoCC Yongshik Moon, Soonhyun Noh, Daedong Park, Chen Luo, Anshumali Shrivastava, Seongsoo Hong, Krishna V. Palem
2016	J	`jnl`	Exact Weighted Minwise Hashing in Constant Time. CoRR Anshumali Shrivastava
2016	J	`jnl`	Near-Isometric Binary Hashing for Large-scale Datasets. CoRR Amirali Aghazadeh, Andrew S. Lan, Anshumali Shrivastava, Richard G. Baraniuk
2016	J	`jnl`	Revisiting Winner Take All (WTA) Hashing for Sparse Datasets. CoRR Beidi Chen, Anshumali Shrivastava
2016	—	`conf`	SSH (Sketch, Shingle, & Hash) for Indexing Massive-Scale Time Series. NIPS Time Series Workshop Chen Luo, Anshumali Shrivastava
2016	J	`jnl`	SSH (Sketch, Shingle, & Hash) for Indexing Massive-Scale Time Series. CoRR Chen Luo, Anshumali Shrivastava
2016	J	`jnl`	Scalable and Sustainable Deep Learning via Randomized Hashing. CoRR Ryan Spring, Anshumali Shrivastava
2016	—	`conf`	Simple and Efficient Weighted Minwise Hashing. NIPS Anshumali Shrivastava
2016	J	`jnl`	Sub-linear Privacy-preserving Search with Untrusted Server and Semi-honest Parties. CoRR M. Sadegh Riazi, Beidi Chen, Anshumali Shrivastava, Dan S. Wallach, Farinaz Koushanfar
2016	—	`conf`	Time Adaptive Sketches (Ada-Sketches) for Summarizing Data Streams. SIGMOD Conference Anshumali Shrivastava, Arnd Christian König, Mikhail Bilenko
2015	A*	`conf`	Asymmetric Minwise Hashing for Indexing Binary Inner Products and Set Containment. WWW Anshumali Shrivastava, Ping Li
2015	J	`jnl`	Blocking Methods Applied to Casualty Records from the Syrian Conflict. CoRR Peter Sadosky, Anshumali Shrivastava, Megan Price, Rebecca C. Steorts
2015	A	`conf`	Improved Asymmetric Locality Sensitive Hashing (ALSH) for Maximum Inner Product Search (MIPS). UAI Anshumali Shrivastava, Ping Li
2015	—	`—`	Probabilistic Hashing Techniques for Big Data. Anshumali Shrivastava
2014	J	`jnl`	A New Space for Comparing Graphs. CoRR Anshumali Shrivastava, Ping Li
2014	B	`conf`	A new space for comparing graphs. ASONAM Anshumali Shrivastava, Ping Li
2014	J	`jnl`	An Improved Scheme for Asymmetric LSH. CoRR Anshumali Shrivastava, Ping Li
2014	—	`conf`	Asymmetric LSH (ALSH) for Sublinear Time Maximum Inner Product Search (MIPS). NIPS Anshumali Shrivastava, Ping Li
2014	J	`jnl`	Asymmetric LSH (ALSH) for Sublinear Time Maximum Inner Product Search (MIPS). CoRR Anshumali Shrivastava, Ping Li
2014	J	`jnl`	Asymmetric Minwise Hashing. CoRR Anshumali Shrivastava, Ping Li
2014	J	`jnl`	Coding for Random Projections and Approximate Near Neighbor Search. CoRR Ping Li, Michael Mitzenmacher, Anshumali Shrivastava
2014	A*	`conf`	Coding for Random Projections. ICML Ping Li, Michael Mitzenmacher, Anshumali Shrivastava
2014	A*	`conf`	Densifying One Permutation Hashing via Rotation for Fast Near Neighbor Search. ICML Anshumali Shrivastava, Ping Li
2014	J	`jnl`	Graph Kernels via Functional Embedding. CoRR Anshumali Shrivastava, Ping Li
2014	A	`conf`	Improved Densification of One Permutation Hashing. UAI Anshumali Shrivastava, Ping Li
2014	J	`jnl`	Improved Densification of One Permutation Hashing. CoRR Anshumali Shrivastava, Ping Li
2014	J	`jnl`	In Defense of MinHash Over SimHash. CoRR Anshumali Shrivastava, Ping Li
2014	A	`conf`	In Defense of Minhash over Simhash. AISTATS Anshumali Shrivastava, Ping Li
2013	—	`conf`	Beyond Pairwise: Provably Fast Algorithms for Approximate NIPS Anshumali Shrivastava, Ping Li
2013	J	`jnl`	Coding for Random Projections. CoRR Ping Li, Michael Mitzenmacher, Anshumali Shrivastava
2013	—	`conf`	b-bit minwise hashing in practice. Internetware Ping Li, Anshumali Shrivastava, Arnd Christian König
2012	—	`conf`	Fast Near Neighbor Search in High-Dimensional Binary Data. ECML/PKDD (1) Anshumali Shrivastava, Ping Li
2012	A	`conf`	Fast multi-task learning for query spelling correction. CIKM Xu Sun, Anshumali Shrivastava, Ping Li
2012	—	`conf`	GPU-based minwise hashing: GPU-based minwise hashing. WWW (Companion Volume) Ping Li, Anshumali Shrivastava, Arnd Christian König
2012	—	`conf`	Query spelling correction using multi-task learning. WWW (Companion Volume) Xu Sun, Anshumali Shrivastava, Ping Li
2012	J	`jnl`	b-Bit Minwise Hashing in Practice: Large-Scale Batch and Online Learning and Using GPUs for Fast Preprocessing with Simple Hash Functions. CoRR Ping Li, Anshumali Shrivastava, Arnd Christian König
2011	J	`jnl`	Hashing Algorithms for Large-Scale Learning CoRR Ping Li, Anshumali Shrivastava, Joshua L. Moore, Arnd Christian König
2011	—	`conf`	Hashing Algorithms for Large-Scale Learning. NIPS Ping Li, Anshumali Shrivastava, Joshua L. Moore, Arnd Christian König
2011	J	`jnl`	Training Logistic Regression and SVM on 200GB Data Using b-Bit Minwise Hashing and Comparisons with Vowpal Wabbit (VW) CoRR Ping Li, Anshumali Shrivastava, Arnd Christian König