Zebang Shen
29 papers · 2015–2025 · 7 conferences · across top CS/AI conferences
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Conferences
AISTATS (6)
IJCAI (6)
AAAI (5)
NIPS (5)
ICLR (3)
ICML (3)
COLT (1)
Top co-authors
Keywords
optimal transport
(3)
convergence rate
(3)
markov chain monte carlo
(2)
gradient estimator
(2)
functional gradient descent
(2)
federated learning
(2)
variance reduction
(2)
stochastic gradient descent
(2)
stochastic optimization
(2)
generative adversarial network
(2)
stochastic gradient
(2)
convex optimization
(2)
decentralized optimization
(2)
policy gradient
(2)
projection-free optimization
(2)
sinkhorn divergence
(2)
wasserstein distance
(2)
bayesian inference
(1)
variational inference
(1)
langevin dynamics
(1)
Papers
Learning to Steer Markovian Agents under Model Uncertainty
ICLR 2025
Provable Maximum Entropy Manifold Exploration via Diffusion Models
ICML 2025
Solving Zero-Sum Markov Games with Continuous State via Spectral Dynamic Embedding
NIPS 2024
Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs
NIPS 2023
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning
ICLR 2023
CDMA: A Practical Cross-Device Federated Learning Algorithm for General Minimax Problems
AAAI 2023
Federated Functional Gradient Boosting
AISTATS 2022
From One to All: Learning to Match Heterogeneous and Partially Overlapped Graphs
AAAI 2022
An Agnostic Approach to Federated Learning with Class Imbalance
ICLR 2022
Self-Consistency of the Fokker Planck Equation
COLT 2022
A Hybrid Stochastic Gradient Hamiltonian Monte Carlo Method
AAAI 2021
Accelerating Stratified Sampling SGD by Reconstructing Strata
IJCAI 2020
Sinkhorn Barycenter via Functional Gradient Descent
NIPS 2020
Sinkhorn Natural Gradient for Generative Models
NIPS 2020
Efficient Projection-Free Online Methods with Stochastic Recursive Gradient
AAAI 2020
Aggregated Gradient Langevin Dynamics
AAAI 2020
One Sample Stochastic Frank-Wolfe
AISTATS 2020
Multitask Metric Learning: Theory and Algorithm
AISTATS 2019
Decentralized Gradient Tracking for Continuous DR-Submodular Maximization
AISTATS 2019
Complexities in Projection-Free Stochastic Non-convex Minimization
AISTATS 2019
Hessian Aided Policy Gradient
ICML 2019
Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match
NIPS 2019
Towards Memory-Friendly Deterministic Incremental Gradient Method
AISTATS 2018
JUMP: a Jointly Predictor for User Click and Dwell Time
IJCAI 2018
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication
ICML 2018
Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization
IJCAI 2017
Tensor Completion with Side Information: A Riemannian Manifold Approach
IJCAI 2017
Adaptive Variance Reducing for Stochastic Gradient Descent
IJCAI 2016
Simple Atom Selection Strategy for Greedy Matrix Completion
IJCAI 2015