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IRLI: Iterative Re-partitioning for Learning to Index


Mar 17, 2021
Gaurav Gupta, Tharun Medini, Anshumali Shrivastava, Alexander J Smola

* 12 pages 

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Accelerating SLIDE Deep Learning on Modern CPUs: Vectorization, Quantizations, Memory Optimizations, and More


Mar 06, 2021
Shabnam Daghaghi, Nicholas Meisburger, Mengnan Zhao, Yong Wu, Sameh Gobriel, Charlie Tai, Anshumali Shrivastava


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Beyond Convolutions: A Novel Deep Learning Approach for Raw Seismic Data Ingestion


Feb 26, 2021
Zhaozhuo Xu, Aditya Desai, Menal Gupta, Anu Chandran, Antoine Vial-Aussavy, Anshumali Shrivastava


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Semantically Constrained Memory Allocation (SCMA) for Embedding in Efficient Recommendation Systems


Feb 24, 2021
Aditya Desai, Yanzhou Pan, Kuangyuan Sun, Li Chou, Anshumali Shrivastava


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Density Sketches for Sampling and Estimation


Feb 24, 2021
Aditya Desai, Benjamin Coleman, Anshumali Shrivastava


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A Constant-time Adaptive Negative Sampling


Dec 31, 2020
Shabnam Daghaghi, Tharun Medini, Beidi Chen, Mengnan Zhao, Anshumali Shrivastava


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Neighbor Oblivious Learning (NObLe) for Device Localization and Tracking


Nov 23, 2020
Zichang Liu, Li Chou, Anshumali Shrivastava


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Learning Sampling Distributions Using Local 3D Workspace Decompositions for Motion Planning in High Dimensions


Oct 29, 2020
Constantinos Chamzas, Zachary Kingston, Carlos Quintero-Peña, Anshumali Shrivastava, Lydia E. Kavraki


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SOLAR: Sparse Orthogonal Learned and Random Embeddings


Aug 30, 2020
Tharun Medini, Beidi Chen, Anshumali Shrivastava

* Under review at NeurIPS 2020 

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Distributed Tera-Scale Similarity Search with MPI: Provably Efficient Similarity Search over billions without a Single Distance Computation


Aug 17, 2020
Nicholas Meisburger, Anshumali Shrivastava


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Tera-SLASH: A Distributed Energy-Efficient MPI based LSH System for Tera-Scale Similarity Search


Aug 05, 2020
Nicholas Meisburger, Anshumali Shrivastava


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Bloom Origami Assays: Practical Group Testing


Jul 21, 2020
Louis Abraham, Gary Becigneul, Benjamin Coleman, Bernhard Scholkopf, Anshumali Shrivastava, Alexander Smola

* arXiv admin note: text overlap with arXiv:2005.06413 

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Climbing the WOL: Training for Cheaper Inference


Jul 03, 2020
Zichang Liu, Zhaozhuo Xu, Alan Ji, Jonathan Li, Beidi Chen, Anshumali Shrivastava


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STORM: Foundations of End-to-End Empirical Risk Minimization on the Edge


Jun 25, 2020
Benjamin Coleman, Gaurav Gupta, John Chen, Anshumali Shrivastava


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A One-Pass Private Sketch for Most Machine Learning Tasks


Jun 16, 2020
Benjamin Coleman, Anshumali Shrivastava

* 10 pages, 4 figures 

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Privacy Adversarial Network: Representation Learning for Mobile Data Privacy


Jun 08, 2020
Sicong Liu, Junzhao Du, Anshumali Shrivastava, Lin Zhong


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Angular Visual Hardness


Jan 04, 2020
Beidi Chen, Weiyang Liu, Animesh Garg, Zhiding Yu, Anshumali Shrivastava, Jan Kautz, Anima Anandkumar

* Tech Report (24 pages) 

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Sub-linear RACE Sketches for Approximate Kernel Density Estimation on Streaming Data


Dec 04, 2019
Benjamin Coleman, Anshumali Shrivastava


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FourierSAT: A Fourier Expansion-Based Algebraic Framework for Solving Hybrid Boolean Constraints


Dec 02, 2019
Anastasios Kyrillidis, Anshumali Shrivastava, Moshe Y. Vardi, Zhiwei Zhang

* The paper was accepted by Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020) 

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Lsh-sampling Breaks the Computation Chicken-and-egg Loop in Adaptive Stochastic Gradient Estimation


Oct 30, 2019
Beidi Chen, Yingchen Xu, Anshumali Shrivastava


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Extreme Classification in Log Memory using Count-Min Sketch: A Case Study of Amazon Search with 50M Products


Oct 28, 2019
Tharun Medini, Qixuan Huang, Yiqiu Wang, Vijai Mohan, Anshumali Shrivastava

* Published at NeurIPS 2019. arXiv admin note: text overlap with arXiv:1810.04254 

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Adaptive Learned Bloom Filter (Ada-BF): Efficient Utilization of the Classifier


Oct 21, 2019
Zhenwei Dai, Anshumali Shrivastava

* 14 pages, 6 figures 

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Semantic Similarity Based Softmax Classifier for Zero-Shot Learning


Sep 10, 2019
Shabnam Daghaghi, Tharun Medini, Anshumali Shrivastava


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RACE: Sub-Linear Memory Sketches for Approximate Near-Neighbor Search on Streaming Data


Apr 09, 2019
Benjamin Coleman, Anshumali Shrivastava, Richard G. Baraniuk


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Using Local Experiences for Global Motion Planning


Mar 20, 2019
Constantinos Chamzas, Anshumali Shrivastava, Lydia E. Kavraki

* 6 pages, to appear in International Conference on Robotics and Automation (ICRA), 2019 

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SLIDE : In Defense of Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning Systems


Mar 07, 2019
Beidi Chen, Tharun Medini, Anshumali Shrivastava


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Compressing Gradient Optimizers via Count-Sketches


Feb 26, 2019
Ryan Spring, Anastasios Kyrillidis, Vijai Mohan, Anshumali Shrivastava

* Initially submitted to WWW 2019 (November 2018) 

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