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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
1072015
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
822017
Kdeformer: Accelerating transformers via kernel density estimation
A Zandieh, I Han, M Daliri, A Karbasi
International Conference on Machine Learning, 40605-40623, 2023
342023
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
292021
Hyperattention: Long-context attention in near-linear time
I Han, R Jayaram, A Karbasi, V Mirrokni, DP Woodruff, A Zandieh
arXiv preprint arXiv:2310.05869, 2023
192023
Faster greedy MAP inference for determinantal point processes
I Han, P Kambadur, K Park, J Shin
International Conference on Machine Learning, 1384-1393, 2017
172017
Stochastic chebyshev gradient descent for spectral optimization
I Han, H Avron, J Shin
Advances in Neural Information Processing Systems 31, 2018
162018
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
142020
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
132020
Fast neural kernel embeddings for general activations
I Han, A Zandieh, J Lee, R Novak, L Xiao, A Karbasi
Advances in neural information processing systems 35, 35657-35671, 2022
112022
Random features for the neural tangent kernel
I Han, H Avron, N Shoham, C Kim, J Shin
arXiv preprint arXiv:2104.01351, 2021
92021
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
82020
BrainLM: A foundation model for brain activity recordings
J Ortega Caro, AH Oliveira Fonseca, C Averill, SA Rizvi, M Rosati, ...
bioRxiv, 2023.09. 12.557460, 2023
32023
Random gegenbauer features for scalable kernel methods
I Han, A Zandieh, H Avron
International Conference on Machine Learning, 8330-8358, 2022
32022
Scalable sampling for nonsymmetric determinantal point processes
I Han, M Gartrell, J Gillenwater, E Dohmatob, A Karbasi
arXiv preprint arXiv:2201.08417, 2022
32022
Cell2sentence: Teaching large language models the language of biology
D Levine, S Lévy, SA Rizvi, N Pallikkavaliyaveetil, X Chen, D Zhang, ...
bioRxiv, 2023.09. 11.557287, 2023
22023
Scalable mcmc sampling for nonsymmetric determinantal point processes
I Han, M Gartrell, E Dohmatob, A Karbasi
International Conference on Machine Learning, 8213-8229, 2022
22022
Stochastic gradient descent
SL Team
22016
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
Advances in Neural Information Processing Systems 36, 2024
2024
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