Ziv Goldfeld
15 papers · 2019–2024 · 5 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+7 more ↓ Show less ↑
🌉 Interdisciplinary Bridge 🏃 Academic Marathon (5) 🧭 Keyword Pioneer 🌍 Conference Polyglot (5) 🐝 Cross-Pollinator (11)
🏃
Academic Marathon
(5)
🌉
Interdisciplinary Bridge
🏆
Keyword Champion
(2)
🔥
Unstoppable
(6)
💎
Century Club
(15)
⚡
Prolific Year
(5)
🗃️
Keyword Collector
(67)
Conferences
NIPS (6)
AISTATS (4)
ICML (2)
JMLR (2)
COLT (1)
Top co-authors
Keywords
wasserstein distance
(7)
optimal transport
(5)
robust estimation
(3)
mutual information
(3)
minimax optimality
(2)
entropic regularization
(2)
minimum distance estimation
(2)
convergence rate
(2)
sliced mutual information
(2)
distributionally robust optimization
(2)
gaussian smoothing
(2)
information theory
(2)
entropic gromov-wasserstein
(1)
sliced wasserstein distance
(1)
variational inference
(1)
high-dimensional inference
(1)
representation learning
(1)
canonical correlation analysis
(1)
function approximation
(1)
dimensionality reduction
(1)
Papers
Entropic Gromov-Wasserstein Distances: Stability and Algorithms
JMLR 2024
Robust Distribution Learning with Local and Global Adversarial Corruptions (extended abstract)
COLT 2024
Max-Sliced Mutual Information
NIPS 2023
Outlier-Robust Wasserstein DRO
NIPS 2023
Outlier-Robust Optimal Transport: Duality, Structure, and Statistical Analysis
AISTATS 2022
Cycle Consistent Probability Divergences Across Different Spaces
AISTATS 2022
$k$-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension
NIPS 2022
Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances
NIPS 2022
Neural Estimation of Statistical Divergences
JMLR 2022
Non-asymptotic Performance Guarantees for Neural Estimation of f-Divergences
AISTATS 2021
Sliced Mutual Information: A Scalable Measure of Statistical Dependence
NIPS 2021
Smooth $p$-Wasserstein Distance: Structure, Empirical Approximation, and Statistical Applications
ICML 2021
Gaussian-Smoothed Optimal Transport: Metric Structure and Statistical Efficiency
AISTATS 2020
Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance
NIPS 2020
Estimating Information Flow in Deep Neural Networks
ICML 2019