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Learning to Retrieve Relevant Experiences for Motion Planning



Constantinos Chamzas , Aedan Cullen , Anshumali Shrivastava , Lydia E. Kavraki

* Accepted in International Conference on Robotics and Automation (ICRA), 2022. Code will be released soon 

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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


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Breaking the Linear Iteration Cost Barrier for Some Well-known Conditional Gradient Methods Using MaxIP Data-structures



Anshumali Shrivastava , Zhao Song , Zhaozhuo Xu

* NeurIPS 2021 

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Federated Multiple Label Hashing (FedMLH): Communication Efficient Federated Learning on Extreme Classification Tasks



Zhenwei Dai , Chen Dun , Yuxin Tang , Anastasios Kyrillidis , Anshumali Shrivastava

* 10 pages, 5 figures 

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Random Offset Block Embedding Array (ROBE) for CriteoTB Benchmark MLPerf DLRM Model : 1000$\times$ Compression and 2.7$\times$ Faster Inference



Aditya Desai , Li Chou , Anshumali Shrivastava


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Efficient Inference via Universal LSH Kernel



Zichang Liu , Benjamin Coleman , Anshumali Shrivastava


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PairConnect: A Compute-Efficient MLP Alternative to Attention



Zhaozhuo Xu , Minghao Yan , Junyan Zhang , Anshumali Shrivastava


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Sublinear Least-Squares Value Iteration via Locality Sensitive Hashing



Anshumali Shrivastava , Zhao Song , Zhaozhuo Xu


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IRLI: Iterative Re-partitioning for Learning to Index



Gaurav Gupta , Tharun Medini , Anshumali Shrivastava , Alexander J Smola

* 12 pages 

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