Amir Zandieh - RankMe

43 papers A* 17A 1Journal 24

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	ECO: Quantized Training without Full-Precision Master Weights. CoRR Mahdi Nikdan, Amir Zandieh, Dan Alistarh, Vahab Mirrokni
2025	J	`jnl`	BalanceKV: KV Cache Compression through Discrepancy Theory. CoRR Insu Han, Michael Kapralov, Ekaterina Kochetkova, Kshiteej Sheth, Amir Zandieh
2025	J	`jnl`	PolarQuant: Quantizing KV Caches with Polar Transformation. CoRR Insu Han, Praneeth Kacham, Amin Karbasi, Vahab Mirrokni, Amir Zandieh
2025	A*	`conf`	QJL: 1-Bit Quantized JL Transform for KV Cache Quantization with Zero Overhead. AAAI Amir Zandieh, Majid Daliri, Insu Han
2025	J	`jnl`	TurboQuant: Online Vector Quantization with Near-optimal Distortion Rate. CoRR Amir Zandieh, Majid Daliri, Majid Hadian, Vahab Mirrokni
2024	A*	`conf`	HyperAttention: Long-context Attention in Near-Linear Time. ICLR Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh
2024	J	`jnl`	QJL: 1-Bit Quantized JL Transform for KV Cache Quantization with Zero Overhead. CoRR Amir Zandieh, Majid Daliri, Insu Han
2024	J	`jnl`	SubGen: Token Generation in Sublinear Time and Memory. CoRR Amir Zandieh, Insu Han, Vahab Mirrokni, Amin Karbasi
2023	J	`jnl`	HyperAttention: Long-context Attention in Near-Linear Time. CoRR Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh
2023	A*	`conf`	KDEformer: Accelerating Transformers via Kernel Density Estimation. ICML Amir Zandieh, Insu Han, Majid Daliri, Amin Karbasi
2023	J	`jnl`	KDEformer: Accelerating Transformers via Kernel Density Estimation. CoRR Amir Zandieh, Insu Han, Majid Daliri, Amin Karbasi
2023	A*	`conf`	Near Optimal Reconstruction of Spherical Harmonic Expansions. NeurIPS Amir Zandieh, Insu Han, Haim Avron
2023	A*	`conf`	Traversing the FFT Computation Tree for Dimension-Independent Sparse Fourier Transforms. SODA Karl Bringmann, Michael Kapralov, Mikhail Makarov, Vasileios Nakos, Amir Yagudin, Amir Zandieh
2022	A*	`conf`	Fast Neural Kernel Embeddings for General Activations. NeurIPS Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi
2022	J	`jnl`	Fast Neural Kernel Embeddings for General Activations. CoRR Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi
2022	A*	`conf`	Leverage Score Sampling for Tensor Product Matrices in Input Sparsity Time. ICML David P. Woodruff, Amir Zandieh
2022	J	`jnl`	Leverage Score Sampling for Tensor Product Matrices in Input Sparsity Time. CoRR David P. Woodruff, Amir Zandieh
2022	J	`jnl`	Near Optimal Reconstruction of Spherical Harmonic Expansions. CoRR Amir Zandieh, Insu Han, Haim Avron
2022	A*	`conf`	Random Gegenbauer Features for Scalable Kernel Methods. ICML Insu Han, Amir Zandieh, Haim Avron
2022	J	`jnl`	Random Gegenbauer Features for Scalable Kernel Methods. CoRR Insu Han, Amir Zandieh, Haim Avron
2021	J	`jnl`	Learning with Neural Tangent Kernels in Near Input Sparsity Time. CoRR Amir Zandieh
2021	A*	`conf`	Scaling Neural Tangent Kernels via Sketching and Random Features. NeurIPS Amir Zandieh, Insu Han, Haim Avron, Neta Shoham, Chaewon Kim, Jinwoo Shin
2021	J	`jnl`	Scaling Neural Tangent Kernels via Sketching and Random Features. CoRR Amir Zandieh, Insu Han, Haim Avron, Neta Shoham, Chaewon Kim, Jinwoo Shin
2021	J	`jnl`	Sparse Fourier Transform by traversing Cooley-Tukey FFT computation graphs. CoRR Karl Bringmann, Michael Kapralov, Mikhail Makarov, Vasileios Nakos, Amir Yagudin, Amir Zandieh
2020	—	`—`	Fourier Sampling in Signal Processing and Numerical Linear Algebra. Amir Zandieh
2020	A*	`conf`	Near Input Sparsity Time Kernel Embeddings via Adaptive Sampling. ICML David P. Woodruff, Amir Zandieh
2020	J	`jnl`	Near Input Sparsity Time Kernel Embeddings via Adaptive Sampling. CoRR David P. Woodruff, Amir Zandieh
2020	A*	`conf`	Oblivious Sketching of High-Degree Polynomial Kernels. SODA Thomas D. Ahle, Michael Kapralov, Jakob Bæk Tejs Knudsen, Rasmus Pagh, Ameya Velingker, David P. Woodruff, Amir Zandieh
2020	A	`conf`	Scaling up Kernel Ridge Regression via Locality Sensitive Hashing. AISTATS Amir Zandieh, Navid Nouri, Ameya Velingker, Michael Kapralov, Ilya P. Razenshteyn
2020	J	`jnl`	Scaling up Kernel Ridge Regression via Locality Sensitive Hashing. CoRR Michael Kapralov, Navid Nouri, Ilya P. Razenshteyn, Ameya Velingker, Amir Zandieh
2019	A*	`conf`	A universal sampling method for reconstructing signals with simple Fourier transforms. STOC Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
2019	A*	`conf`	Dimension-independent Sparse Fourier Transform. SODA Michael Kapralov, Ameya Velingker, Amir Zandieh
2019	J	`jnl`	Dimension-independent Sparse Fourier Transform. CoRR Michael Kapralov, Ameya Velingker, Amir Zandieh
2019	A*	`conf`	Efficiently Learning Fourier Sparse Set Functions. NeurIPS Andisheh Amrollahi, Amir Zandieh, Michael Kapralov, Andreas Krause
2019	J	`jnl`	Oblivious Sketching of High-Degree Polynomial Kernels. CoRR Thomas D. Ahle, Michael Kapralov, Jakob Bæk Tejs Knudsen, Rasmus Pagh, Ameya Velingker, David P. Woodruff, Amir Zandieh
2018	J	`jnl`	A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms. CoRR Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
2018	A*	`conf`	Beyond 1/2-Approximation for Submodular Maximization on Massive Data Streams. ICML Ashkan Norouzi-Fard, Jakub Tarnawski, Slobodan Mitrovic, Amir Zandieh, Aidasadat Mousavifar, Ola Svensson
2018	J	`jnl`	Beyond 1/2-Approximation for Submodular Maximization on Massive Data Streams. CoRR Ashkan Norouzi-Fard, Jakub Tarnawski, Slobodan Mitrovic, Amir Zandieh, Aida Mousavifar, Ola Svensson
2018	J	`jnl`	Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. CoRR Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
2017	J	`jnl`	An Adaptive Sublinear-Time Block Sparse Fourier Transform. CoRR Volkan Cevher, Michael Kapralov, Jonathan Scarlett, Amir Zandieh
2017	A*	`conf`	An adaptive sublinear-time block sparse fourier transform. STOC Volkan Cevher, Michael Kapralov, Jonathan Scarlett, Amir Zandieh
2017	A*	`conf`	Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. ICML Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
2014	J	`jnl`	Reconstruction of Sub-Nyquist Random Sampling for Sparse and Multi-Band Signals. CoRR Amir Zandieh, Alireza Zareian, Masoumeh Azghani, Farokh Marvasti