Krzysztof M Choromanski
14 papers · 2013–2023 · 1 venue · across top CS/AI venues
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Research topics
Machine Learning
(14)
Optimization & Theory Β· Machine Learning
(9)
Mathematics & Optimization
(7)
Deep Learning
(6)
Core Methods
(6)
Optimization
(5)
Architectures
(4)
Artificial Intelligence
(3)
Core AI
(3)
Optimization & Theory Β· Deep Learning
(3)
Computer Science
(2)
Reinforcement Learning
(2)
Application Areas
(2)
Foundations
(2)
Learning Types
(2)
Keywords
kernel approximation
(5)
neural network optimization
(2)
black-box optimization
(2)
orthogonal matrix
(2)
gaussian kernel
(2)
random feature
(2)
sampling algorithm
(2)
softmax kernel
(2)
variance reduction
(2)
compressed sensing
(2)
reinforcement learning
(2)
utility optimization
(1)
sample efficiency
(1)
privacy preservation
(1)
structured matrix
(1)
monte carlo sampling
(1)
optimal transport
(1)
graph coloring
(1)
policy optimization
(1)
gradient descent
(1)
Papers
Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel
NeurIPS 2023
Mnemosyne: Learning to Train Transformers with Transformers
NeurIPS 2023
Quasi-Monte Carlo Graph Random Features
NeurIPS 2023
Chefs' Random Tables: Non-Trigonometric Random Features
NeurIPS 2022
Sub-Linear Memory: How to Make Performers SLiM
NeurIPS 2021
Demystifying Orthogonal Monte Carlo and Beyond
NeurIPS 2020
Effective Diversity in Population Based Reinforcement Learning
NeurIPS 2020
Ode to an ODE
NeurIPS 2020
From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization
NeurIPS 2019
Geometrically Coupled Monte Carlo Sampling
NeurIPS 2018
On Blackbox Backpropagation and Jacobian Sensing
NeurIPS 2017
The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings
NeurIPS 2017
Orthogonal Random Features
NeurIPS 2016
Adaptive Anonymity via b-Matching
NeurIPS 2013