Xunpeng Huang
9 papers · 2017–2026 · 6 venues · across top CS/AI venues
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Research topics
Machine Learning
(9)
Optimization & Theory Β· Machine Learning
(7)
Mathematics & Optimization
(6)
Optimization
(5)
Deep Learning
(4)
Optimization & Theory Β· Deep Learning
(3)
Bayesian & Probabilistic
(2)
Learning Types
(2)
Models
(2)
Artificial Intelligence
(1)
Data Science & Analytics
(1)
Applications
(1)
Core AI
(1)
Core Methods
(1)
Learning Paradigms
(1)
Keywords
diffusion model
(3)
stochastic optimization
(2)
convergence rate
(2)
total variation distance
(2)
few-shot learning
(1)
online learning
(1)
stochastic gradient
(1)
collaborative filtering
(1)
stochastic gradient descent
(1)
in-context learning
(1)
kl divergence
(1)
incremental learning
(1)
neural network optimization
(1)
markov chain monte carlo
(1)
markov chain
(1)
matrix factorization
(1)
variance reduction
(1)
monte carlo sampling
(1)
stochastic process
(1)
low-rank approximation
(1)
Papers
Almost Linear Convergence under Minimal Score Assumptions: Quantized Transition Diffusion
COLT 2026
What Makes In-context Learning Effective for Mathematical Reasoning
ICML 2025
Faster Sampling via Stochastic Gradient Proximal Sampler
ICML 2024
Faster Sampling without Isoperimetry via Diffusion-based Monte Carlo
COLT 2024
Reverse Diffusion Monte Carlo
ICLR 2024
Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference
NeurIPS 2024
ACMo: Angle-Calibrated Moment Methods for Stochastic Optimization
AAAI 2021
SPAN: A Stochastic Projected Approximate Newton Method
AAAI 2020
Incremental Matrix Factorization: A Linear Feature Transformation Perspective
IJCAI 2017