Papers citing 'A New Unbiased and Efficient Class of LSH-Based Samplers and Estimators for Partition Function Computation in Log-Linear Models'

Title
Improved Stochastic Optimization of LogSumExp E. Gladin Alexey Kroshnin Jia Jie Zhu Pavel Dvurechensky 76 0 0 29 Sep 2025
Real-time Indexing for Large-scale Recommendation by Streaming Vector Quantization Retriever Xingyan Bin Jianfei Cui Wujie Yan Zhichen Zhao Xintian Han Chongyang Yan Feng Zhang Xun Zhou Qi Wu Zuotao Liu 81 6 0 15 Jan 2025
Hierarchical Structured Neural Network: Efficient Retrieval Scaling for Large Scale Recommendation Kaushik Rangadurai Siyang Yuan Minhui Huang Yiqun Liu Golnaz Ghasemiesfeh ... Vidhoon Viswanathan Yan Dong Liang Wang Lin Yang Chonglin Sun 166 0 0 10 Jan 2025
Scalable Cross-Entropy Loss for Sequential Recommendations with Large Item CatalogsACM Conference on Recommender Systems (RecSys), 2024 Gleb Mezentsev Danil I. Gusak Ivan Oseledets Evgeny Frolov 160 14 0 27 Sep 2024
RECE: Reduced Cross-Entropy Loss for Large-Catalogue Sequential RecommendersInternational Conference on Information and Knowledge Management (CIKM), 2024 Danil I. Gusak Gleb Mezentsev Ivan Oseledets Evgeny Frolov 269 8 0 05 Aug 2024
Memory MosaicsInternational Conference on Learning Representations (ICLR), 2024 Jianyu Zhang Niklas Nolte Ranajoy Sadhukhan Beidi Chen Léon Bottou VLM 309 7 0 10 May 2024
LookupFFN: Making Transformers Compute-lite for CPU inferenceInternational Conference on Machine Learning (ICML), 2024 Zhanpeng Zeng Michael Davies Pranav Pulijala Karthikeyan Sankaralingam Vikas Singh 135 10 0 12 Mar 2024
Adaptive and Dynamic Multi-Resolution Hashing for Pairwise Summations Lianke Qin Aravind Reddy Zhao Song Zhaozhuo Xu Danyang Zhuo 195 14 0 21 Dec 2022
Training Overparametrized Neural Networks in Sublinear Time Yichuan Deng Han Hu Zhao Song Omri Weinstein Danyang Zhuo BDL 231 29 0 09 Aug 2022
Cooperative Retriever and Ranker in Deep RecommendersThe Web Conference (WWW), 2022 Xunpeng Huang Defu Lian Jin Chen Liu Zheng Xing Xie Enhong Chen VLM AI4TS 86 15 0 28 Jun 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 154 6 0 29 Jan 2022
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling Zhanpeng Zeng Yunyang Xiong Sathya Ravi Shailesh Acharya G. Fung Vikas Singh 156 21 0 18 Nov 2021
Fast Variational AutoEncoder with Inverted Multi-Index for Collaborative Filtering Jin Chen Defu Lian Binbin Jin Xunpeng Huang Kai Zheng Enhong Chen BDL 208 28 0 13 Sep 2021
Efficient Inference via Universal LSH Kernel Zichang Liu Benjamin Coleman Anshumali Shrivastava 60 1 0 21 Jun 2021
Kernel approximation on algebraic varietiesSIAM Journal on applied algebra and geometry (SIAM J. Appl. Algebra Geom.), 2021 Jason M. Altschuler P. Parrilo 117 6 0 04 Jun 2021
A Tale of Two Efficient and Informative Negative Sampling DistributionsInternational Conference on Machine Learning (ICML), 2020 Shabnam Daghaghi Tharun Medini Nicholas Meisburger Beidi Chen Mengnan Zhao Anshumali Shrivastava 108 10 0 31 Dec 2020
Deep Retrieval: Learning A Retrievable Structure for Large-Scale Recommendations Weihao Gao Xiangjun Fan Chong-Jun Wang Jiankai Sun Kai Jia Wen Xiao Ruofan Ding Xingyan Bin Hui Yang Xiaobing Liu CML 186 26 0 12 Jul 2020
Climbing the WOL: Training for Cheaper Inference Zichang Liu Zhaozhuo Xu A. Ji Jonathan Li Beidi Chen Anshumali Shrivastava TPM 191 7 0 02 Jul 2020
Sub-linear RACE Sketches for Approximate Kernel Density Estimation on Streaming Data Benjamin Coleman Anshumali Shrivastava 95 37 0 04 Dec 2019
Lsh-sampling Breaks the Computation Chicken-and-egg Loop in Adaptive Stochastic Gradient Estimation Beidi Chen Yingchen Xu Anshumali Shrivastava 148 16 0 30 Oct 2019
SLIDE : In Defense of Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning Systems Beidi Chen Tharun Medini James Farwell Sameh Gobriel Charlie Tai Anshumali Shrivastava 213 111 0 07 Mar 2019
Sub-linear Memory Sketches for Near Neighbor Search on Streaming Data Benjamin Coleman Richard G. Baraniuk Anshumali Shrivastava 133 7 0 18 Feb 2019
Doubly Sparse: Sparse Mixture of Sparse Experts for Efficient Softmax Inference Shun Liao Ting Chen Tian Lin Denny Zhou Chong-Jun Wang MoE 77 2 0 30 Jan 2019
Scaling-up Split-Merge MCMC with Locality Sensitive Sampling (LSS) Chen Luo Anshumali Shrivastava 175 12 0 21 Feb 2018
FLASH: Randomized Algorithms Accelerated over CPU-GPU for Ultra-High Dimensional Similarity Search Yiqiu Wang Anshumali Shrivastava Jonathan Wang Junghee Ryu FedML 122 28 0 04 Sep 2017
Arrays of (locality-sensitive) Count Estimators (ACE): High-Speed Anomaly Detection via Cache Lookups Chen Luo Anshumali Shrivastava 98 8 0 20 Jun 2017
Scalable and Sustainable Deep Learning via Randomized Hashing Ryan Spring Anshumali Shrivastava 250 135 0 26 Feb 2016