Aleksei Ustimenko
8 papers · 2019–2024 · 2 venues · across top CS/AI venues
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Achievements
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🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (16) 🐣 Hot Topic Early Bird
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The Questioner
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Research topics
Machine Learning
(7)
Core Methods
(5)
Optimization & Theory
(4)
Artificial Intelligence
(2)
Mathematics & Optimization
(2)
Bayesian & Probabilistic · Machine Learning
(2)
Bayesian & Probabilistic · Artificial Intelligence
(2)
Computer Science
(1)
Deep Learning
(1)
Application Areas
(1)
Applications
(1)
Models
(1)
Optimization
(1)
Probability
(1)
Keywords
gradient boosting
(4)
learning to rank
(3)
stochastic gradient descent
(1)
bayesian inference
(1)
uncertainty quantification
(1)
information retrieval
(1)
out-of-domain detection
(1)
gaussian process
(1)
global optimization
(1)
discrete optimization
(1)
markov chain
(1)
kernel ridge regression
(1)
ranking optimization
(1)
ensemble method
(1)
schrödinger equation
(1)
stochastic differential equation
(1)
stochastic gradient langevin dynamics
(1)
ranking loss
(1)
generative diffusion model
(1)
langevin diffusion
(1)
Papers
Deep Stochastic Mechanics
ICML 2024
Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting
ICLR 2024
Gradient Boosting Performs Gaussian Process Inference
ICLR 2023
Which Tricks are Important for Learning to Rank?
ICML 2023
SGLB: Stochastic Gradient Langevin Boosting
ICML 2021
Uncertainty in Gradient Boosting via Ensembles
ICLR 2021
StochasticRank: Global Optimization of Scale-Free Discrete Functions
ICML 2020
Learning to select for a predefined ranking
ICML 2019