Dong Yin
14 papers · 2017–2025 · 6 venues · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (26)
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Century Club · Bronze
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Unstoppable · Bronze
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Research topics
Machine Learning
(12)
Optimization & Theory
(8)
Learning Types
(6)
Reinforcement Learning
(4)
Methods
(4)
Artificial Intelligence
(3)
Deep Learning
(2)
Mathematics & Optimization
(2)
Architectures
(2)
Learning Paradigms
(2)
Optimization
(2)
Application Areas
(1)
Applications
(1)
Core AI
(1)
Core Methods
(1)
Keywords
non-convex optimization
(2)
neural network
(2)
linear function approximation
(2)
function approximation
(2)
policy iteration
(2)
byzantine-robust distributed learning
(2)
multi-task learning
(1)
sample efficiency
(1)
continual learning
(1)
off-policy evaluation
(1)
maximum entropy
(1)
computer vision
(1)
stochastic gradient descent
(1)
model robustness
(1)
adversarial training
(1)
neural network training
(1)
distributed learning
(1)
model aggregation
(1)
distributed optimization
(1)
data augmentation
(1)
Papers
Step-by-Step Reasoning for Math Problems via Twisted Sequential Monte Carlo
ICLR 2025
Confident Least Square Value Iteration with Local Access to a Simulator
AISTATS 2022
Efficient local planning with linear function approximation
ALT 2022
Wide Neural Networks Forget Less Catastrophically
ICML 2022
Improved Regret Bound and Experience Replay in Regularized Policy Iteration
ICML 2021
A Maximum-Entropy Approach to Off-Policy Evaluation in Average-Reward MDPs
NeurIPS 2020
An Efficient Framework for Clustered Federated Learning
NeurIPS 2020
Stochastic Gradient and Langevin Processes
ICML 2020
A Fourier Perspective on Model Robustness in Computer Vision
NeurIPS 2019
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning
ICML 2019
Rademacher Complexity for Adversarially Robust Generalization
ICML 2019
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
ICML 2018
Gradient Diversity: a Key Ingredient for Scalable Distributed Learning
AISTATS 2018
Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks
JMLR 2017