Insu Han
17 papers · 2015–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (6) π Academic Marathon (10) π§ Keyword Pioneer π Interdisciplinary Bridge π Cross-Pollinator (10)
π
Cross-Pollinator
(10)
πΊοΈ
Taxonomy Completionist
(33)
π
Triple Crown
π
Grand Slam
π§¬
Topic Evolution
π
Century Club
(17)
ποΈ
Keyword Collector
(75)
π₯
Unstoppable
(6)
π
Trend Setter
Conferences
ICML (7)
NIPS (4)
ICLR (3)
AAAI (1)
AISTATS (1)
EMNLP (1)
Top co-authors
Keywords
kernel methods
(3)
neural tangent kernel
(3)
determinantal point process
(3)
map inference
(2)
trace estimator
(2)
kernel regression
(2)
random feature
(2)
chebyshev expansion
(2)
attention mechanism
(1)
approximate inference
(1)
sequence modeling
(1)
signal reconstruction
(1)
variance reduction
(1)
gaussian process
(1)
markov chain monte carlo
(1)
stochastic gradient descent
(1)
spectral norm
(1)
gaussian kernel
(1)
kernel density estimation
(1)
kernel approximation
(1)
Papers
Mamba Drafters for Speculative Decoding
EMNLP 2025
QJL: 1-Bit Quantized JL Transform for KV Cache Quantization with Zero Overhead
AAAI 2025
HyperAttention: Long-context Attention in Near-Linear Time
ICLR 2024
Cell2Sentence: Teaching Large Language Models the Language of Biology
ICML 2024
Near Optimal Reconstruction of Spherical Harmonic Expansions
NIPS 2023
KDEformer: Accelerating Transformers via Kernel Density Estimation
ICML 2023
Scalable Sampling for Nonsymmetric Determinantal Point Processes
ICLR 2022
Fast Neural Kernel Embeddings for General Activations
NIPS 2022
Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes
ICML 2022
Random Gegenbauer Features for Scalable Kernel Methods
ICML 2022
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
ICLR 2021
Scaling Neural Tangent Kernels via Sketching and Random Features
NIPS 2021
MAP Inference for Customized Determinantal Point Processes via Maximum Inner Product Search
AISTATS 2020
Polynomial Tensor Sketch for Element-wise Function of Low-Rank Matrix
ICML 2020
Stochastic Chebyshev Gradient Descent for Spectral Optimization
NIPS 2018
Faster Greedy MAP Inference for Determinantal Point Processes
ICML 2017
Large-scale log-determinant computation through stochastic Chebyshev expansions
ICML 2015