Insu Han

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 32

Top Topics

Point Processes

Low Rank Matrix Approximation

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)
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)
Insu Han, Mike Gartrell, Elvis Dohmatob, Amin Karbasi
Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes. CoRR (2022)
Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi
Fast Neural Kernel Embeddings for General Activations. CoRR (2022)
Insu Han, Mike Gartrell, Elvis Dohmatob, Amin Karbasi
Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes. ICML (2022)
Amir Zandieh, Insu Han, Haim Avron
Near Optimal Reconstruction of Spherical Harmonic Expansions. CoRR (2022)
Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi
Scalable Sampling for Nonsymmetric Determinantal Point Processes. ICLR (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)
Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi
Scalable Sampling for Nonsymmetric Determinantal Point Processes. 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)
Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes. ICLR (2021)
Insu Han, Haim Avron, Neta Shoham, Chaewon Kim, Jinwoo Shin
Random Features for the Neural Tangent Kernel. CoRR (2021)
Insu Han, Jennifer Gillenwater
MAP Inference for Customized Determinantal Point Processes via Maximum Inner Product Search. AISTATS (2020)
Insu Han, Haim Avron, Jinwoo Shin
Polynomial Tensor Sketch for Element-wise Function of Low-Rank Matrix. ICML (2020)
Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes. CoRR (2020)
Insu Han, Haim Avron, Jinwoo Shin
Polynomial Tensor Sketch for Element-wise Function of Low-Rank Matrix. CoRR (2019)
Insu Han, Haim Avron, Jinwoo Shin
Stochastic Chebyshev Gradient Descent for Spectral Optimization. NeurIPS (2018)
Insu Han, Haim Avron, Jinwoo Shin
Optimizing Spectral Sums using Randomized Chebyshev Expansions. CoRR (2018)
Insu Han, Prabhanjan Kambadur, KyoungSoo Park, Jinwoo Shin
Faster Greedy MAP Inference for Determinantal Point Processes. ICML (2017)
Insu Han, Dmitry Malioutov, Haim Avron, Jinwoo Shin
Approximating Spectral Sums of Large-Scale Matrices using Stochastic Chebyshev Approximations. SIAM J. Sci. Comput. 39 (4) (2017)
Insu Han, Prabhanjan Kambadur, KyoungSoo Park, Jinwoo Shin
Faster Greedy MAP Inference for Determinantal Point Processes. CoRR (2017)
Insu Han, Dmitry Malioutov, Haim Avron, Jinwoo Shin
Approximating the Spectral Sums of Large-scale Matrices using Chebyshev Approximations. CoRR (2016)
Insu Han, Dmitry Malioutov, Jinwoo Shin
Large-scale log-determinant computation through stochastic Chebyshev expansions. ICML (2015)
Insu Han, Dmitry Malioutov, Jinwoo Shin
Large-scale Log-determinant Computation through Stochastic Chebyshev Expansions. CoRR (2015)