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Insu Han
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Cited by
Year
Large-scale log-determinant computation through stochastic Chebyshev expansions
I Han, D Malioutov, J Shin
International Conference on Machine Learning, 908-917, 2015
912015
Approximating spectral sums of large-scale matrices using stochastic Chebyshev approximations
I Han, D Malioutov, H Avron, J Shin
SIAM Journal on Scientific Computing 39 (4), A1558-A1585, 2017
762017
Faster greedy MAP inference for determinantal point processes
I Han, P Kambadur, K Park, J Shin
International Conference on Machine Learning, 1384-1393, 2017
162017
Stochastic chebyshev gradient descent for spectral optimization
I Han, H Avron, J Shin
Advances in Neural Information Processing Systems 31, 2018
132018
Scalable learning and MAP inference for nonsymmetric determinantal point processes
M Gartrell, I Han, E Dohmatob, J Gillenwater, VE Brunel
arXiv preprint arXiv:2006.09862, 2020
122020
Scaling neural tangent kernels via sketching and random features
A Zandieh, I Han, H Avron, N Shoham, C Kim, J Shin
Advances in Neural Information Processing Systems 34, 1062-1073, 2021
102021
MAP inference for customized determinantal point processes via maximum inner product search
I Han, J Gillenwater
International Conference on Artificial Intelligence and Statistics, 2797-2807, 2020
92020
Polynomial tensor sketch for element-wise function of low-rank matrix
I Han, H Avron, J Shin
International Conference on Machine Learning, 3984-3993, 2020
62020
Random features for the neural tangent kernel
I Han, H Avron, N Shoham, C Kim, J Shin
arXiv preprint arXiv:2104.01351, 2021
42021
Fast neural kernel embeddings for general activations
I Han, A Zandieh, J Lee, R Novak, L Xiao, A Karbasi
arXiv preprint arXiv:2209.04121, 2022
22022
Scalable sampling for nonsymmetric determinantal point processes
I Han, M Gartrell, J Gillenwater, E Dohmatob, A Karbasi
arXiv preprint arXiv:2201.08417, 2022
22022
Stochastic gradient descent
SL Team
22016
Scalable mcmc sampling for nonsymmetric determinantal point processes
I Han, M Gartrell, E Dohmatob, A Karbasi
International Conference on Machine Learning, 8213-8229, 2022
12022
Random gegenbauer features for scalable kernel methods
I Han, A Zandieh, H Avron
International Conference on Machine Learning, 8330-8358, 2022
12022
Optimizing Spectral Sums using Randomized Chebyshev Expansions
I Han, H Avron, J Shin
arXiv preprint arXiv:1802.06355, 2018, 2018
12018
Near Optimal Reconstruction of Spherical Harmonic Expansions
A Zandieh, I Han, H Avron
arXiv preprint arXiv:2202.12995, 2022
2022
{Approximating spectral sums of large-scale matrices: application to determinantal point processes
I Han
한국과학기술원, 2017
2017
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Articles 1–17