Amir Zandieh

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 36

Top Topics

Random Sampling

Kernel Ridge Regression

Posterior Marginals

Massive Data Streams

Top Venues

Publications

Amir Zandieh, Insu Han, Vahab Mirrokni, Amin Karbasi
SubGen: Token Generation in Sublinear Time and Memory. CoRR (2024)
Amir Zandieh, Majid Daliri, Insu Han
QJL: 1-Bit Quantized JL Transform for KV Cache Quantization with Zero Overhead. CoRR (2024)
Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh
HyperAttention: Long-context Attention in Near-Linear Time. ICLR (2024)
Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh
HyperAttention: Long-context Attention in Near-Linear Time. CoRR (2023)
Amir Zandieh, Insu Han, Majid Daliri, Amin Karbasi
KDEformer: Accelerating Transformers via Kernel Density Estimation. CoRR (2023)
Karl Bringmann, Michael Kapralov, Mikhail Makarov, Vasileios Nakos, Amir Yagudin, Amir Zandieh
Traversing the FFT Computation Tree for Dimension-Independent Sparse Fourier Transforms. SODA (2023)
Amir Zandieh, Insu Han, Haim Avron
Near Optimal Reconstruction of Spherical Harmonic Expansions. NeurIPS (2023)
Amir Zandieh, Insu Han, Majid Daliri, Amin Karbasi
KDEformer: Accelerating Transformers via Kernel Density Estimation. ICML (2023)
Insu Han, Amir Zandieh, Haim Avron
Random Gegenbauer Features for Scalable Kernel Methods. ICML (2022)
David P. Woodruff, Amir Zandieh
Leverage Score Sampling for Tensor Product Matrices in Input Sparsity Time. ICML (2022)
David P. Woodruff, Amir Zandieh
Leverage Score Sampling for Tensor Product Matrices in Input Sparsity Time. CoRR (2022)
Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi
Fast Neural Kernel Embeddings for General Activations. CoRR (2022)
Amir Zandieh, Insu Han, Haim Avron
Near Optimal Reconstruction of Spherical Harmonic Expansions. CoRR (2022)
Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi
Fast Neural Kernel Embeddings for General Activations. NeurIPS (2022)
Insu Han, Amir Zandieh, Haim Avron
Random Gegenbauer Features for Scalable Kernel Methods. CoRR (2022)
Amir Zandieh, Insu Han, Haim Avron, Neta Shoham, Chaewon Kim, Jinwoo Shin
Scaling Neural Tangent Kernels via Sketching and Random Features. NeurIPS (2021)
Amir Zandieh, Insu Han, Haim Avron, Neta Shoham, Chaewon Kim, Jinwoo Shin
Scaling Neural Tangent Kernels via Sketching and Random Features. CoRR (2021)
Karl Bringmann, Michael Kapralov, Mikhail Makarov, Vasileios Nakos, Amir Yagudin, Amir Zandieh
Sparse Fourier Transform by traversing Cooley-Tukey FFT computation graphs. CoRR (2021)
Amir Zandieh
Learning with Neural Tangent Kernels in Near Input Sparsity Time. CoRR (2021)
Thomas D. Ahle, Michael Kapralov, Jakob Bæk Tejs Knudsen, Rasmus Pagh, Ameya Velingker, David P. Woodruff, Amir Zandieh
Oblivious Sketching of High-Degree Polynomial Kernels. SODA (2020)
David P. Woodruff, Amir Zandieh
Near Input Sparsity Time Kernel Embeddings via Adaptive Sampling. CoRR (2020)
David P. Woodruff, Amir Zandieh
Near Input Sparsity Time Kernel Embeddings via Adaptive Sampling. ICML (2020)
Amir Zandieh, Navid Nouri, Ameya Velingker, Michael Kapralov, Ilya P. Razenshteyn
Scaling up Kernel Ridge Regression via Locality Sensitive Hashing. AISTATS (2020)
Michael Kapralov, Navid Nouri, Ilya P. Razenshteyn, Ameya Velingker, Amir Zandieh
Scaling up Kernel Ridge Regression via Locality Sensitive Hashing. CoRR (2020)
Michael Kapralov, Ameya Velingker, Amir Zandieh
Dimension-independent Sparse Fourier Transform. CoRR (2019)
Andisheh Amrollahi, Amir Zandieh, Michael Kapralov, Andreas Krause
Efficiently Learning Fourier Sparse Set Functions. NeurIPS (2019)
Michael Kapralov, Rasmus Pagh, Ameya Velingker, David P. Woodruff, Amir Zandieh
Oblivious Sketching of High-Degree Polynomial Kernels. CoRR (2019)
Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
A universal sampling method for reconstructing signals with simple Fourier transforms. STOC (2019)
Michael Kapralov, Ameya Velingker, Amir Zandieh
Dimension-independent Sparse Fourier Transform. SODA (2019)
Ashkan Norouzi-Fard, Jakub Tarnawski, Slobodan Mitrovic, Amir Zandieh, Aidasadat Mousavifar, Ola Svensson
Beyond 1/2-Approximation for Submodular Maximization on Massive Data Streams. ICML (2018)
Ashkan Norouzi-Fard, Jakub Tarnawski, Slobodan Mitrovic, Amir Zandieh, Aida Mousavifar, Ola Svensson
Beyond 1/2-Approximation for Submodular Maximization on Massive Data Streams. CoRR (2018)
Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms. CoRR (2018)
Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. CoRR (2018)
Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. ICML (2017)
Volkan Cevher, Michael Kapralov, Jonathan Scarlett, Amir Zandieh
An Adaptive Sublinear-Time Block Sparse Fourier Transform. CoRR (2017)
Volkan Cevher, Michael Kapralov, Jonathan Scarlett, Amir Zandieh
An adaptive sublinear-time block sparse fourier transform. STOC (2017)
Amir Zandieh, Alireza Zareian, Masoumeh Azghani, Farokh Marvasti
Reconstruction of Sub-Nyquist Random Sampling for Sparse and Multi-Band Signals. CoRR (2014)