Ya-Ping Hsieh
17 papers · 2015–2025 · 6 venues · across top CS/AI venues
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Achievements
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🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (32) 🌍 Conference Polyglot · Silver 🐣 Hot Topic Early Bird 🏃 Academic Marathon · Half
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Prolific Year · Productive
🔥
Unstoppable · Bronze
💎
Century Club · Bronze
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Keyword Collector
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Research topics
Machine Learning
(14)
Mathematics & Optimization
(12)
Optimization & Theory · Machine Learning
(11)
Optimization
(10)
Deep Learning
(5)
Learning Types
(4)
Artificial Intelligence
(3)
Mathematics
(3)
Models
(3)
Core AI
(2)
Optimization & Theory · Deep Learning
(2)
Computer Science
(1)
Reinforcement Learning
(1)
Application Areas
(1)
Bayesian & Probabilistic
(1)
Keywords
mirror descent
(4)
langevin dynamics
(3)
riemannian optimization
(2)
stochastic approximation
(2)
optimal transport
(2)
diffusion model
(2)
convergence analysis
(2)
gradient descent
(2)
dynamical system
(2)
non-convex optimization
(2)
stochastic gradient
(1)
convex optimization
(1)
game theory
(1)
latent dirichlet allocation
(1)
variational inference
(1)
generative modeling
(1)
robust reinforcement learning
(1)
neural network training
(1)
stochastic optimization
(1)
deep learning
(1)
Papers
Provable Maximum Entropy Manifold Exploration via Diffusion Models
ICML 2025
Sinkhorn Flow as Mirror Flow: A Continuous-Time Framework for Generalizing the Sinkhorn Algorithm
AISTATS 2024
A Dynamical System View of Langevin-Based Non-Convex Sampling
NeurIPS 2023
Aligned Diffusion Schrödinger Bridges
UAI 2023
Riemannian stochastic optimization methods avoid strict saddle points
NeurIPS 2023
Stochastic Approximation Algorithms for Systems of Interacting Particles
NeurIPS 2023
The Schrödinger Bridge between Gaussian Measures has a Closed Form
AISTATS 2023
The Dynamics of Riemannian Robbins-Monro Algorithms
COLT 2022
The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets
ICML 2021
Conditional gradient methods for stochastically constrained convex minimization
ICML 2020
Robust Reinforcement Learning via Adversarial training with Langevin Dynamics
NeurIPS 2020
Finding Mixed Nash Equilibria of Generative Adversarial Networks
ICML 2019
Dimension-free Information Concentration via Exp-Concavity
ALT 2018
Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games
ICML 2018
Mirrored Langevin Dynamics
NeurIPS 2018
An Efficient Streaming Algorithm for the Submodular Cover Problem
NeurIPS 2016
Preconditioned Spectral Descent for Deep Learning
NeurIPS 2015