Anshumali Shrivastava
52 papers · 2011–2025 · 10 venues · across top CS/AI venues
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Machine Learning
(41)
Application Areas
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Artificial Intelligence
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Computer Science
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Deep Learning
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(14)
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(8)
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Keywords
locality sensitive hashing
(12)
model compression
(10)
nearest neighbor search
(8)
minwise hashing
(5)
similarity search
(4)
approximate nearest neighbor
(4)
representation learning
(3)
distributed training
(3)
neural network optimization
(3)
large language model
(3)
near neighbor search
(3)
parameter sharing
(3)
inference optimization
(3)
memory efficiency
(3)
maximum inner product search
(3)
memory optimization
(3)
stochastic gradient descent
(2)
model quantization
(2)
contrastive learning
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large-scale learning
(2)
Papers
CoVE: Compressed Vocabulary Expansion Makes Better LLM-based Recommender Systems
ACL 2025
LeanQuant: Accurate and Scalable Large Language Model Quantization with Loss-error-aware Grid
ICLR 2025
Sketch to Adapt: Fine-Tunable Sketches for Efficient LLM Adaptation
ICML 2025
ZEN: Empowering Distributed Training with Sparsity-driven Data Synchronization
OSDI 2025
In defense of parameter sharing for model-compression
ICLR 2024
KV Cache is 1 Bit Per Channel: Efficient Large Language Model Inference with Coupled Quantization
NeurIPS 2024
NoMAD-Attention: Efficient LLM Inference on CPUs Through Multiply-add-free Attention
NeurIPS 2024
Soft Prompt Recovers Compressed LLMs, Transferably
ICML 2024
SS1: Accelerating Inference with Fast and Expressive Sketch Structured Transform
NeurIPS 2024
A Tale of Two Efficient Value Iteration Algorithms for Solving Linear MDPs with Large Action Space
AISTATS 2023
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time
ICML 2023
DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries
NeurIPS 2023
Graph Self-supervised Learning via Proximity Distribution Minimization
UAI 2023
Hardware-Aware Compression with Random Operation Access Specific Tile (ROAST) Hashing
ICML 2023
Learning Multimodal Data Augmentation in Feature Space
ICLR 2023
One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning
NeurIPS 2023
Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time
NeurIPS 2023
DRAGONN: Distributed Randomized Approximate Gradients of Neural Networks
ICML 2022
Graph Reordering for Cache-Efficient Near Neighbor Search
NeurIPS 2022
One-Pass Diversified Sampling with Application to Terabyte-Scale Genomic Sequence Streams
ICML 2022
Retaining Knowledge for Learning with Dynamic Definition
NeurIPS 2022
Structural Contrastive Representation Learning for Zero-shot Multi-label Text Classification
EMNLP 2022
The trade-offs of model size in large recommendation models : 100GB to 10MB Criteo-tb DLRM model
NeurIPS 2022
A Tale of Two Efficient and Informative Negative Sampling Distributions
ICML 2021
Breaking the Linear Iteration Cost Barrier for Some Well-known Conditional Gradient Methods Using MaxIP Data-structures
NeurIPS 2021
Locality Sensitive Teaching
NeurIPS 2021
MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training
ICLR 2021
Practical Near Neighbor Search via Group Testing
NeurIPS 2021
Raw Nav-merge Seismic Data to Subsurface Properties with MLP based Multi-Modal Information Unscrambler
NeurIPS 2021
Revisiting Consistent Hashing with Bounded Loads
AAAI 2021
SDM-Net: A simple and effective model for generalized zero-shot learning
UAI 2021
SOLAR: Sparse Orthogonal Learned and Random Embeddings
ICLR 2021
Adaptive Learned Bloom Filter (Ada-BF): Efficient Utilization of the Classifier with Application to Real-Time Information Filtering on the Web
NeurIPS 2020
Angular Visual Hardness
ICML 2020
FourierSAT: A Fourier Expansion-Based Algebraic Framework for Solving Hybrid Boolean Constraints
AAAI 2020
Mutual Information Estimation using LSH Sampling
IJCAI 2020
Sub-linear Memory Sketches for Near Neighbor Search on Streaming Data
ICML 2020
Compressing Gradient Optimizers via Count-Sketches
ICML 2019
Extreme Classification in Log Memory using Count-Min Sketch: A Case Study of Amazon Search with 50M Products
NeurIPS 2019
Fast and Accurate Stochastic Gradient Estimation
NeurIPS 2019
Scaling-Up Split-Merge MCMC with Locality Sensitive Sampling (LSS)
AAAI 2019
MISSION: Ultra Large-Scale Feature Selection using Count-Sketches
ICML 2018
Topkapi: Parallel and Fast Sketches for Finding Top-K Frequent Elements
NeurIPS 2018
Optimal Densification for Fast and Accurate Minwise Hashing
ICML 2017
RHash: Robust Hashing via L_infinity-norm Distortion
IJCAI 2017
Simple and Efficient Weighted Minwise Hashing
NeurIPS 2016
Asymmetric LSH (ALSH) for Sublinear Time Maximum Inner Product Search (MIPS)
NeurIPS 2014
Coding for Random Projections
ICML 2014
Densifying One Permutation Hashing via Rotation for Fast Near Neighbor Search
ICML 2014
In Defense of Minhash over Simhash
AISTATS 2014
Beyond Pairwise: Provably Fast Algorithms for Approximate k-Way Similarity Search
NeurIPS 2013
Hashing Algorithms for Large-Scale Learning
NeurIPS 2011