Kevin Tian
28 papers · 2017–2026 · 3 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (51) π Academic Marathon Β· Sprint π Conference Polyglot Β· Bronze π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Deep Specialist
(11)
π§¬
Topic Evolution
π₯
Unstoppable Β· Silver
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Prolific Year Β· Productive
ποΈ
Keyword Collector
(149)
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Century Club Β· Bronze
Venues
Top co-authors
Research topics
Machine Learning
(26)
Optimization & Theory
(23)
Mathematics & Optimization
(19)
Optimization
(18)
Core Methods
(10)
Artificial Intelligence
(6)
Learning Types
(6)
Bayesian & Probabilistic Β· Machine Learning
(5)
Mathematics
(5)
Bayesian & Probabilistic Β· Artificial Intelligence
(3)
Core AI
(3)
Security & Privacy
(2)
Differential Privacy
(2)
Computer Science
(1)
Deep Learning
(1)
Keywords
convex optimization
(6)
sample complexity
(5)
markov chain monte carlo
(4)
mixing time
(4)
differential privacy
(4)
principal component analysis
(3)
sparse recovery
(2)
gradient descent
(2)
variable selection
(2)
parallel algorithm
(2)
stochastic method
(2)
generalized linear model
(2)
log-concave distribution
(2)
restricted isometry property
(2)
hamiltonian monte carlo
(2)
earth mover distance
(2)
semidefinite programming
(1)
spectral clustering
(1)
stochastic gradient
(1)
wasserstein distance
(1)
Papers
Functional Stochastic Localization
COLT 2026
On the Curse of Dimensionality in Private Sparse Covariance Estimation and PCA
COLT 2026
Separating Oblivious and Adaptive Models of Variable Selection (Extended Abstract)
COLT 2026
Simultaneous Blackwell Approachability and Applications to Multiclass Omniprediction
COLT 2026
Spike-and-Slab Posterior Sampling in High Dimensions
COLT 2025
Black-Box k-to-1-PCA Reductions: Theory and Applications
COLT 2024
Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization
COLT 2024
Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random
NeurIPS 2024
Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions
NeurIPS 2024
Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting
NeurIPS 2024
Testing Calibration in Nearly-Linear Time
NeurIPS 2024
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler
COLT 2023
Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling
ICML 2023
Revisiting Area Convexity: Faster Box-Simplex Games and Spectrahedral Generalizations
NeurIPS 2023
Semi-Random Sparse Recovery in Nearly-Linear Time
COLT 2023
Structured Semidefinite Programming for Recovering Structured Preconditioners
NeurIPS 2023
Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods
COLT 2022
List-Decodable Mean Estimation in Nearly-PCA Time
NeurIPS 2021
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions
NeurIPS 2021
Robust Regression Revisited: Acceleration and Improved Estimation Rates
NeurIPS 2021
Structured Logconcave Sampling with a Restricted Gaussian Oracle
COLT 2021
Acceleration with a Ball Optimization Oracle
NeurIPS 2020
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo
COLT 2020
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing
NeurIPS 2020
A Direct tilde{O}(1/epsilon) Iteration Parallel Algorithm for Optimal Transport
NeurIPS 2019
Variance Reduction for Matrix Games
NeurIPS 2019
CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions
ICML 2018
Learning Populations of Parameters
NeurIPS 2017