Insu Han
17 papers · 2015–2025 · 6 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (34) π Conference Polyglot Β· Silver π Academic Marathon Β· Half π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Triple Crown
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Grand Slam
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Topic Evolution
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Century Club Β· Bronze
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Keyword Collector
(91)
π₯
Unstoppable Β· Bronze
Top co-authors
Research topics
Machine Learning
(14)
Mathematics & Optimization
(10)
Optimization & Theory Β· Machine Learning
(8)
Optimization
(7)
Artificial Intelligence
(6)
Core Methods
(6)
Mathematics
(6)
Application Areas
(5)
Bayesian & Probabilistic Β· Machine Learning
(5)
Deep Learning
(4)
Architectures
(4)
Core AI
(4)
Natural Language Processing
(2)
Bayesian & Probabilistic Β· Artificial Intelligence
(2)
Optimization & Theory Β· Deep Learning
(2)
Keywords
determinantal point process
(4)
neural tangent kernel
(3)
kernel methods
(3)
kernel regression
(2)
efficient inference
(2)
large language model
(2)
rejection sampling
(2)
random feature
(2)
trace estimator
(2)
chebyshev expansion
(2)
kernel matrix
(2)
map inference
(2)
gene expression
(1)
signal reconstruction
(1)
scalable learning
(1)
gaussian process
(1)
approximate inference
(1)
sequence modeling
(1)
markov chain monte carlo
(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
Cell2Sentence: Teaching Large Language Models the Language of Biology
ICML 2024
HyperAttention: Long-context Attention in Near-Linear Time
ICLR 2024
KDEformer: Accelerating Transformers via Kernel Density Estimation
ICML 2023
Near Optimal Reconstruction of Spherical Harmonic Expansions
NeurIPS 2023
Fast Neural Kernel Embeddings for General Activations
NeurIPS 2022
Random Gegenbauer Features for Scalable Kernel Methods
ICML 2022
Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes
ICML 2022
Scalable Sampling for Nonsymmetric Determinantal Point Processes
ICLR 2022
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
ICLR 2021
Scaling Neural Tangent Kernels via Sketching and Random Features
NeurIPS 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
NeurIPS 2018
Faster Greedy MAP Inference for Determinantal Point Processes
ICML 2017
Large-scale log-determinant computation through stochastic Chebyshev expansions
ICML 2015