AZ
Amir Zandieh
cs.LGcs.DScs.AIstat.MLcs.NAmath.NAcs.CLcs.CVeess.SPcs.IT
On Valency
published · living versionsW_24yjzasy·v1 · currentpublished
GINGER: Spicing Up Graph-Based Vector Search
with Daniel Salwasser, Lars Gottesbüren, Laxman Dhulipala, Jakub Łącki +5
1 version
Preprints & journals
22 papers in the corpus · 2014–2026ECO: Quantized Training without Full-Precision Master Weights2601.22101v1 · Mahdi Nikdan, Amir Zandieh, Dan Alistarh et al.2026 · 0 citationsarXiv
PolarQuant: Quantizing KV Caches with Polar Transformation2502.02617v1 · Insu Han, Praneeth Kacham, Amin Karbasi et al.2025 · 0 citationsarXiv
QJL: 1-Bit Quantized JL Transform for KV Cache Quantization with Zero Overhead2406.03482v2 · Amir Zandieh, Majid Daliri, Insu Han2024 · 4 citationsarXiv
SubGen: Token Generation in Sublinear Time and Memory2402.06082v1 · Amir Zandieh, Insu Han, Vahab Mirrokni et al.2024 · 1 citationarXiv
HyperAttention: Long-context Attention in Near-Linear Time2310.05869v3 · Insu Han, Rajesh Jayaram, Amin Karbasi et al.2023 · 10 citationsarXiv
KDEformer: Accelerating Transformers via Kernel Density Estimation2302.02451v2 · Amir Zandieh, Insu Han, Majid Daliri et al.2023 · 8 citationsarXiv
Fast Neural Kernel Embeddings for General Activations2209.04121v1 · Insu Han, Amir Zandieh, Jaehoon Lee et al.2022 · 7 citationsarXiv
Near Optimal Reconstruction of Spherical Harmonic Expansions2202.12995v1 · Amir Zandieh, Insu Han, Haim Avron2022 · 0 citationsarXiv
Leverage Score Sampling for Tensor Product Matrices in Input Sparsity Time2202.04515v2 · David P. Woodruff, Amir Zandieh2022 · 1 citationarXiv
Random Gegenbauer Features for Scalable Kernel Methods2202.03474v1 · Insu Han, Amir Zandieh, Haim Avron2022 · 0 citationsarXiv
Traversing the FFT Computation Tree for Dimension-Independent Sparse Fourier Transforms2107.07347v2 · Karl Bringmann, Michael Kapralov, Mikhail Makarov et al.2021 · 1 citationarXiv
Scaling Neural Tangent Kernels via Sketching and Random Features2106.07880v2 · Amir Zandieh, Insu Han, Haim Avron et al.2021 · 13 citationsarXiv
Learning with Neural Tangent Kernels in Near Input Sparsity Time2104.00415v2 · Amir Zandieh2021 · 0 citationsarXiv
Near Input Sparsity Time Kernel Embeddings via Adaptive Sampling2007.03927v2 · David P. Woodruff, Amir Zandieh2020 · 7 citationsarXiv
Scaling up Kernel Ridge Regression via Locality Sensitive Hashing2003.09756v1 · Michael Kapralov, Navid Nouri, Ilya Razenshteyn et al.2020 · 5 citationsarXiv
Oblivious Sketching of High-Degree Polynomial Kernels1909.01410v5 · Thomas D. Ahle, Michael Kapralov, Jakob B. T. Knudsen et al.2019 · 44 citationsarXiv
Dimension-independent Sparse Fourier Transform1902.10633v1 · Michael Kapralov, Ameya Velingker, Amir Zandieh2019 · 20 citationsarXiv
A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms1812.08723v1 · Haim Avron, Michael Kapralov, Cameron Musco et al.2018 · 29 citationsarXiv
Beyond -Approximation for Submodular Maximization on Massive Data Streams1808.01842v1 · Ashkan Norouzi-Fard, Jakub Tarnawski, Slobodan Mitrovi'c et al.2018 · 40 citationsProc. of 35th International Conference on Machine Learning (ICML), 2018, pages 3829-3838
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees1804.09893v2 · Haim Avron, Michael Kapralov, Cameron Musco et al.2018 · 84 citationsarXiv
An Adaptive Sublinear-Time Block Sparse Fourier Transform1702.01286v2 · Volkan Cevher, Michael Kapralov, Jonathan Scarlett et al.2017 · 14 citationsarXiv
Reconstruction of Sub-Nyquist Random Sampling for Sparse and Multi-Band Signals1411.6587v2 · Amir Zandieh, Alireza Zareian, Masoumeh Azghani et al.2014 · 2 citationsarXiv
Career total: 31 works. 22 are in this corpus.
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